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SYSTEMATIC REVIEW article

A systematic review of factors that influence youths career choices—the role of culture.

• 1 College of Medicine and Dentistry, James Cook University, Townsville, QLD, Australia
• 2 College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, QLD, Australia
• 3 College of Arts, Society and Education, James Cook University, Cairns, QLD, Australia

Good career planning leads to life fulfillment however; cultural heritage can conflict with youths' personal interests. This systematic review examined existing literature on factors that influence youths' career choices in both collectivist and individualistic cultural settings from around the globe with the aim of identifying knowledge gaps and providing direction for future research. A systematic review strategy using the Joana Briggs Institute's format was conducted. The ERIC, PsychInfo, Scopus, and Informit Platform databases were searched for articles published between January 1997 and May 2018. A total of 30 articles were included in the review, findings revealed that youth from collectivist cultures were mainly influenced by family expectations, whereby higher career congruence with parents increased career confidence and self-efficacy. Personal interest was highlighted as the major factor that influenced career choice in individualistic settings, and the youth were more independent in their career decision making. Bicultural youth who were more acculturated to their host countries were more intrinsically motivated in their career decision making. Further research is imperative to guide the understanding of parental influence and diversity, particularly for bicultural youths' career prospects and their ability to use the resources available in their new environments to attain meaningful future career goals.

Introduction

Career choice is a significant issue in the developmental live of youths because it is reported to be associated with positive as well as harmful psychological, physical and socio-economic inequalities that persist well beyond the youthful age into an individual's adult life ( Robertson, 2014 ; Bubić and Ivanišević, 2016 ). The term “youth” is described by the United Nations Educational Scientific and Cultural Organisation (UNESCO) as a more fluid category than a fixed age group and it refers to young people within the period of transitioning from the dependence of childhood to adulthood independence and awareness of their interdependence as members of a community ( UNESCO, 2017 ).

The complexity of career decision-making increases as age increases ( Gati and Saka, 2001 ). Younger children are more likely to offer answers about their ideal career which may represent their envisioned utopia and phenomenal perceptions about what they want to do when they grow up ( Howard and Walsh, 2011 ). As children get older, they are more likely to describe their career choice as a dynamic interplay of their developmental stages and the prevailing environmental circumstances ( Howard and Walsh, 2011 ). Youth career decision-making is required to go through a process of understanding by defining what they want to do and exploring a variety of career options with the aid of guidance and planning ( Porfeli and Lee, 2012 ). Proper handling of the process affirms individual identity and fosters wellbeing, job satisfaction and stability ( Kunnen, 2013 ).

Many theoretical models have been proposed to explain the process of career development and decision-making, one of which is the Social Cognitive Career Theory (SCCT) by Lent et al. (1994) . According to the SCCT, career development behaviors are affected by three social cognitive processes - self-efficacy beliefs, outcome expectations and career goals and intentions which interplay with ethnicity, culture, gender, socio-economic status, social support, and any perceived barriers to shape a person's educational and career trajectories ( Lent et al., 2000 ; Blanco, 2011 ). This emphasizes the complex interplay between the personal aspirations of youths in their career choices and decision-making and the external influences which act upon them. Carpenter and Foster (1977) postulated that the earlier experiences and influences which individuals are exposed to form the bedrock of how they conceive their career aspirations ( Carpenter and Foster, 1977 ). These authors' assertion lends support to the tenets of SCCT and they have developed a three-dimensional framework to classify the factors that influence career choice. Carpenter and Foster proposed that all career-influencing factors derive from either intrinsic, extrinsic, or interpersonal dimensions. They referred to the intrinsic dimension as a set of interests related to a profession and its role in society. Extrinsic refers to the desire for social recognition and security meanwhile the interpersonal dimension is connected to the influence of others such as family, friends, and teachers ( Carpenter and Foster, 1977 ).

Further exploration by other researchers reveal that youth who are motivated by intrinsic factors are driven by their interests in certain professions, and employments that are personally satisfying ( Gokuladas, 2010 ; Kunnen, 2013 ). Therefore, intrinsic factors relate to decisions emanating from self, and the actions that follow are stimulated by interest, enjoyment, curiosity or pleasure and they include personality traits, job satisfaction, advancement in career, and learning experiences ( Ryan and Deci, 2000 ; Kunnen, 2013 ; Nyamwange, 2016 ). Extrinsic factors revolve around external regulations and the benefits associated with certain occupations ( Shoffner et al., 2015 ). Prestigious occupations, availability of jobs and well-paying employments have also been reported to motivate youth career decision-making ( Ryan and Deci, 2000 ). Consequently, extrinsically motivated youth may choose their career based on the fringe benefits associated with a particular profession such as financial remuneration, job security, job accessibility, and satisfaction ( Ryan and Deci, 2000 ; Edwards and Quinter, 2011 ; Bakar et al., 2014 ). Interpersonal factors encompass the activities of agents of socialization in one's life and these include the influence of family members, teachers/educators, peers, and societal responsibilities ( Gokuladas, 2010 ; Bossman, 2014 ; Wu et al., 2015 ). Beynon et al. reported that Chinese-Canadian students' focus in selecting a career was to bring honor to the family ( Beynon et al., 1998 ). Students who are influenced by interpersonal factors highly value the opinions of family members and significant others; they therefore consult with and depend on these people and are willing to compromise their personal interest ( Guan et al., 2015 ).

Studies have shown that cultural values have an impact on the factors that influence the career choices of youths ( Mau, 2000 ; Caldera et al., 2003 ; Wambu et al., 2017 ; Hui and Lent, 2018 ; Tao et al., 2018 ). Culture is the collective programming of the mind that distinguishes one group of people from another ( Hofstede, 2001 , p.9) ( Hofstede, 2001 ). Hofstede (1980) seminal work on culture dimensions identified four major cultural dimensions in his forty-country comparative research ( Hofstede, 1980 ). The first dimension is known as “individualism-collectivism.” In individualistic cultures, an individual is perceived as an “independent entity,” whilst in collectivistic cultures he/she is perceived as an “interdependent entity.” That said, decision-making in individualistic cultures are based on individuals ‘own wishes and desires, whilst in collectivistic cultures, decisions are made jointly with the “in-group” (such as family, significant others and peers), and the primary objective is to optimize the group's benefit. The second dimension is power distance. In high power distant cultures; power inequality in society and its organizations exist and is accepted. The third dimension - uncertainty avoidance denotes the extent to which uncertainty and ambiguity is tolerated in society. In high uncertainty avoidant cultures, it is less tolerated, whereas in low uncertainty avoidant cultures it is more tolerated. Lastly, masculinity and femininity dimension deals with the prevailing values and priorities. In masculine cultures, achievement and accumulation of wealth is valued and strongly encouraged; in feminine cultures, maintaining good interpersonal relationships is the priority.

In his later work on “Cultural Dimension Scores,” Hofstede suggested that countries' score on power distance, individualism, masculinity, uncertainty avoidance, long-term orientation, and indulgence depicts whether they are collectivist inclined or individualistic-oriented ( Hofstede, 2011 ). Countries that espoused collectivist values may score low and countries that are entrenched in individualistic values may score high on the above-mentioned six cultural dimension score models ( Hofstede, 1980 , 2001 , 2011 ). This model aids the characterization of countries into either individualistic or collectivist cultural settings.

On this basis, western countries like Australia, United Kingdom (UK) and the United States of America (USA) have been shown to align with individualism and such cultures are oriented around independence, self-reliance, freedom and individual autonomy; while African and Asian nations align more closely with collectivism in which people identify with societal interdependence and communal benefits ( Hofstede, 1980 ; Sinha, 2014 ). Research indicates that basing cultures on individualistic versus collectivist dimensions may explain the classical differences in career decision-making among youths ( Mau, 2004 ; Amit and Gati, 2013 ; Sinha, 2014 ). The normative practice in individualistic societies is for the youth to be encouraged to choose their own careers and develop competency in establishing a career path for themselves, while youths from collectivist societies may be required to conform to familial and societal standards and they are often expected to follow a pre-determined career track ( Oettingen and Zosuls, 2006 ).

The interaction between individualistic and collectivist cultures has increased in frequency over the last 20 years due to global migration. Given that different standards are prescribed for the youths' career selection from the two cultures (collectivist—relatedness, and individualistic—autonomy), making a personal career decision could be quite daunting in situations where migrant families have moved from their heritage cultures into a host country. Friction may arise between the adapting youths and their often traditionally focused and opinionated parents as the families resettle in the host countries.

According to a report by the United Nations (UN), the world counted 173–258 million international migrants from 2000 to 2017, representing 3.4 percent of the global population. Migration is defined by the International Organisation of Migration (IOM) as the movement of a person or a group of persons, either across an international border, or within a state ( IOM, 2018 ). In this era of mass migration, migrant students who accompanied their parents to another country and are still discerning their career pathways could be exposed to the unfamiliar cultural values in general and the school/educational system in particular ( Zhang et al., 2014 ). On this note, migrant students might face a daunting task in negotiating their career needs both within host countries' school systems and perhaps within their own family setups. These migrant youth undoubtedly face uncertainties and complexities as career decision-making trajectory could be different in their heritage cultures compared to the prevailing status quo of the host country's culture ( Sawitri and Creed, 2017 ; Tao et al., 2018 ). As youth plan and make career decisions, in the face of both expected and unexpected interests, goals, expectations, personal experiences as well as obligations and responsibilities, cultural undercurrents underpin what the youth can do, and how they are required to think. Some studies have examined cross-cultural variations in factors influencing the career choice of youth from both similar and dissimilar cultural settings ( Mau, 2000 ; Lee, 2001 ; Fan et al., 2012 , 2014 ; Tao et al., 2018 ). However, there may be large differences between different migrant populations.

Given the influence of cultural heritage on career choice and with the increasing numbers of transitions between cultures, it is important to examine the scope and range of research activities available in the area of youths' career choice, particularly in relation to how movements across cultures affect the youth in their career decision making. To the best of our knowledge, there is no comprehensive review of existing literature available in this area. Using the three-dimensional framework proposed by Carpenter and Foster (1977) , this systematic review aims to examine the factors influencing youths' career choices, with particular reference to cultural impact. It will also identify any gaps in the existing literature and make recommendations that will help guide future research and aid policy makers and educational counselors in developing adequately equipped and well-integrated career choice support systems that will foster a more effective workforce.

Literature Search

A systematic review strategy was devised and the literature search was conducted using the Joana Briggs Institute's (JBI) format. The search was conducted between December 2016 and May 2018, utilizing James Cook University's subscription to access the following databases: Education Resources Information Centre (ERIC), PsycINFO, Scopus and Informit. The subject and keyword searches were conducted in three parts.

1. Career and its cognate terms:

“Career development” OR “Career decision” OR “career choice” OR “Career choices” OR “Career planning” OR “Career guidance” OR Career OR Careers OR “Career advancement” OR “Career exploration” OR Vocation OR Vocations OR Vocational OR “Occupational aspiration” OR Job OR Jobs OR Occupations OR Occupation OR Occupational” AND

2. Youth and its cognate terms:

“Youth OR Youths” OR “Young adults” OR adolescent* OR teenage* OR student” AND

3. Factors and variables:

“Intrinsic OR Extrinsic OR Interpersonal OR Individualistic OR Collectivist OR Culture OR Cultures OR Cultural OR “Cross Cultural.”

The Boolean operators (OR/AND) and search filters were applied to obtain more focused results. The articles included in the final search were peer-reviewed and the references of publications sourced from these searches were hand searched to obtain additional abstracts. Searches of reference and citation lists commenced in December 2016, repeated in March, July and November 2017 and finally May 2018 to identify and include any new, relevant articles.

Inclusion and Exclusion Criteria

Only peer-reviewed articles published in English within the last 20 years (1997-2018) and with full text available were included. Studies included in the final analysis were original research articles that focused on career choices of youth from all cultures including migrant youth who are also known as bicultural (those who accompanied their parents to another country). The rationale for using the cultural concepts of collectivist and individualistic cultural settings was inspired by Hofstede's Cultural Dimensional Scores Model ( Hofstede, 2011 ). Abstracts were excluded if they focused on students below secondary school level and those already in the workforce as the study mainly focused on youth discerning their career choices and not those already in the workforce.

Data Extraction

Two of the researchers (PAT and BMA) independently assessed data for extraction, using coding sheets. Study variables compared were author and year of publication, country and continent of participant enrolment, cultural setting, study design, participant numbers, and educational level, factors influencing career choice and major outcomes. Data were crosschecked in a consensus meeting and discrepancies resolved through discussion and mutual agreement between the two reviewers. The third and fourth authors (T.I.E and D.L) were available to adjudicate if required.

Quality of Methods Assessment

In this study, two reviewers (PAT and TIE) ascertained the quality and validity of the articles using JBI Critical Appraisal (CA) tools for qualitative and cross-sectional studies ( Aromataris and Munn, 2017 ). In any event of disagreement, a third reviewer (BMA) interceded to make a judgement. Both JBI CA tools assess the methodological quality of the included studies to derive a score ranging from 0 (low quality) to 8 or 10 (high quality). Using these tools, studies with a total score between 0 and 3 were deemed of low quality, studies with a score between 4 and 6 were classed as of moderate quality and studies with scores from 7 were deemed to be of high quality (sound methodology).

Study Selection

Articles retrieved from the initial database search totaled 5,201. An additional 38 articles were retrieved from direct journal search by bibliographic search. A total of 597 records remained after duplicates and unrelated articles were removed. Of this number, 521 were excluded after abstract review mainly for not meeting the inclusion criteria, leaving 76 full text articles for eligibility check. A further 46 were excluded because they focused on career difficulties, counseling, retention, working adolescents, or the cultural setting was not stated. Applying this screening process resulted in 30 studies for inclusion in the qualitative review synthesis (see Figure 1 ).

Figure 1 . Search strategy. The figure shows the search strategy including databases assessed for this study.

Study Characteristics

All three factors (Intrinsic, Extrinsic, and Interpersonal) affecting adolescents' career choices were identified in this review (Figure 2 ). Out of the 30 articles, five (17%) explored interpersonal factors exclusively ( Cheung et al., 2013 ; Gunkel et al., 2013 ; Fan et al., 2014 ; Zhang et al., 2014 ; Fouad et al., 2016 ). Majority of the studies, 16 out of 30 (53%) explored interpersonal and intrinsic factors solely ( Mau, 2000 ; Lee, 2001 ; Caldera et al., 2003 ; Howard et al., 2009 ; Lent et al., 2010 ; Shin and Kelly, 2013 ; Cheung and Arnold, 2014 ; Sawitri et al., 2014 , 2015 ; Guan et al., 2015 ; Li et al., 2015 ; Sawitri and Creed, 2015 , 2017 ; Kim et al, 2016 ; Hui and Lent, 2018 ; Polenova et al., 2018 ).

Figure 2 . Diagrammatic illustration of the included studies highlighting the factors that influence youth career choices. The figure shows the number of studies focusing on each of the three factors (intrinsic, extrinsic and interpersonal).

No articles focused solely on extrinsic or intrinsic factors. Two studies each explored the relationship between intrinsic and extrinsic ( Choi and Kim, 2013 ; Atitsogbe et al., 2018 ) as well as extrinsic and interpersonal factors ( Yamashita et al., 1999 ; Wüst and Leko Šimić, 2017 ). The remaining five articles (17%) explored all three factors (intrinsic, extrinsic, and interpersonal, ( Bojuwoye and Mbanjwa, 2006 ; Agarwala, 2008 ; Gokuladas, 2010 ; Fan et al., 2012 ; Tao et al., 2018 ). Table 1 summarizes the 30 articles included in this review. Intrinsic factors explored in the literature include self-interest, job satisfaction, and learning experiences. Extrinsic factors include job security, guaranteed job opportunities, high salaries, prestigious professions and future benefits. Meanwhile, interpersonal factors include parental support, family cohesion, peer influence, and interaction with educators.

Table 1 . Summary of studies included in the review.

The collectivist cultural settings examined in the reviewed articles included Argentina, Burkina Faso, Bulgaria, China, Croatia, Hong Kong, India, Indonesia, Japan, Mexico, Portugal, South Africa, South Korea, Taiwan and Ukraine; while the individualistic ones were Canada, Finland, Germany, Spain, Switzerland and United States of America. Italy was considered as partly individualistic and collectivist. Fourteen studies included participants from both collectivist and individualistic cultural settings ( Mau, 2000 ; Lee, 2001 ; Caldera et al., 2003 ; Howard et al., 2009 ; Fan et al., 2012 , 2014 ; Cheung et al., 2013 ; Choi and Kim, 2013 ; Gunkel et al., 2013 ; Shin and Kelly, 2013 ; Zhang et al., 2014 ; Guan et al., 2015 ; Fouad et al., 2016 ; Wüst and Leko Šimić, 2017 ; Atitsogbe et al., 2018 ; Hui and Lent, 2018 ; Polenova et al., 2018 ; Tao et al., 2018 ). Twelve studies focused on collectivist cultural settings ( Yamashita et al., 1999 ; Bojuwoye and Mbanjwa, 2006 ; Agarwala, 2008 ; Gokuladas, 2010 ; Lent et al., 2010 ; Cheung and Arnold, 2014 ; Sawitri et al., 2014 , 2015 ; Li et al., 2015 ; Kim et al, 2016 ; Sawitri and Creed, 2017 ). Three studies examined participants who moved from collectivist to individualistic settings ( Hui and Lent, 2018 ; Polenova et al., 2018 ; Tao et al., 2018 ) and one study considered both cultural dimensions within a single setting ( Howard et al., 2009 ). Twenty-nine of the included studies used a range of quantitative designs. Participant numbers in these ranged from 80 to 2087. One study used qualitative design with 12 participants.

Quality of Methods of Included Studies

The quality assessment of methods employed in the 30 studies included in this review are outlined in Table 2 . The qualitative study was assessed using the JBI qualitative CA tool and was of sound methodology (Table 2A ). Using the JBI cross-sectional CA tool, 9 of the 29 quantitative studies (31 %) were of sound methodology (score of 6.5–7). The other 20 studies (69 %) were of moderate quality (Table 2B ).

Table 2 . Quality assessment of included articles.

Synthesis of Study Results

Table 1 and Figure 3 details the study setting and the underlying factors influencing youth career choices. Analysis of the reviewed articles revealed four major themes namely: extrinsic, intrinsic and interpersonal factors and emergent bicultural influence on career choice. These four major themes had several subthemes and are reported below.

Figure 3 . Career influencing factors. The figures shows identified career influencing factors and their distribution in cultural settings.

Extrinsic Factors

Extrinsic factors examined in the reviewed articles included financial remuneration, job security, professional prestige and job accessibility.

Financial Remuneration

Financial remuneration was identified as the most influential extrinsic factor in career choice decision. Income was considered as an important component of life, particularly among youth who had a higher level of individualism ( Agarwala, 2008 ; Wüst and Leko Šimić, 2017 ). Wüst and Leko Šimić reported that German students ranked “a high income” highest with a 3.7 out of 5 and regarded it as the most important feature of their future job in comparison to Croatian students who gave it a lower ranking of 3 out of 5 ( Wüst and Leko Šimić, 2017 ). While amongst Indian management students, it was rated as the third most important factor influencing career choice ( Agarwala, 2008 ). Financial reward was also a high motivator for career decision among Chinese migrant students in Canada ( Tao et al., 2018 ), and Korean students ( Choi and Kim, 2013 ). In contrast, the need for higher remuneration did not influence career decision making among engineering students in India ( Gokuladas, 2010 ), and Japanese senior college students ( Yamashita et al., 1999 ).

Professional Prestige

Professional prestige was identified as an important deciding factor for youth career decision making in India ( Agarwala, 2008 ), South Africa ( Bojuwoye and Mbanjwa, 2006 ), Croatia ( Wüst and Leko Šimić, 2017 ), Japan and Korea ( Yamashita et al., 1999 ), which are all collectivist settings. Prestige statuses attached to some occupations were strong incentives to career choices; was ranked as the second most important positive influence in career decision making by over half of the respondents in a South African study, indicating that these youth wanted prestigious jobs so that they could live good lives and be respected in the society ( Bojuwoye and Mbanjwa, 2006 ). Japanese and Korean students were also highly influenced by occupational prestige ( Yamashita et al., 1999 ); however, the Korean students considered it of higher importance than their Japanese counterparts.

Job Accessibility

Job accessibility was also considered as a deciding factor for youth's career decision in a collectivist Burkina Faso society where nearness to employment locations prevented students from choosing careers related to their preferred fields of endeavor ( Atitsogbe et al., 2018 ). Another study explored the perceptions of hospitality and tourism career among college students and demonstrated that Korean students are more likely to focus on current market trends such as job accessibility in comparison to their American counterparts ( Choi and Kim, 2013 ), implying that they are less flexible with their choices. However, job accessibility and vocational interest were less predictive of career explorations than personality traits in both cultural settings in a different study ( Fan et al., 2012 ).

Job Security

Job security was reported as influential in only one study where it was identified as highly important by German youth in comparison to their Croatian counterparts ( Wüst and Leko Šimić, 2017 ). They suggested that their finding are in line with the uncertainty avoidance index proposed by Hofstede (2011) which also takes on a relatively high value for Germans. They provided two major reasons for the findings—(1) “secure jobs” has a tradition for young Germans and (2) change in employment contracts in Germany; with fewer employees under 25 having permanent contracts ( Wüst and Leko Šimić, 2017 ).

Intrinsic Factors

The literature explored intrinsic factors such as personal interests, self-efficacy, outcome expectations and professional development opportunities.

Personal Interests

Personal interests in career decision-making appeared to be an important factor in the selection of a life career ( Caldera et al., 2003 ; Bojuwoye and Mbanjwa, 2006 ; Gokuladas, 2010 ; Lent et al., 2010 ; Choi and Kim, 2013 ; Atitsogbe et al., 2018 ). Bojuwoye and Mbanjwa ascertained that about fifty per cent of youth career decisions are based on their personal interests ( Bojuwoye and Mbanjwa, 2006 ), and Gokuladas maintained that students from urban areas are most likely to consider their personal interests before societal interests when making career decisions ( Gokuladas, 2010 ). Lent et al., reported that personal interest predict youth's career outcome expectations ( Lent et al., 2010 ) while Li et al., indicated that in collectivist Chinese culture, personal interests matter significantly however individual preferences are strongly influenced by social comparison ( Li et al., 2015 ). Atitsogbe et al., observed that Swiss students are more influenced by personal interests ( Atitsogbe et al., 2018 ). They reported that in Switzerland, interest differentiation was significantly associated with self-identity. This scenario was compared to the situation in the collectivist Burkina Faso culture where interest differentiation and consistency were less associated self-identity ( Atitsogbe et al., 2018 ). Similarly, Korean students were reported to focus on the prevailing market trends such as salary, job positions, and promotion opportunities in contrast to American student who were more future oriented and interested in setting individual desired goals in their reality oriented-perceptions ( Choi and Kim, 2013 ). Personal interest was also linked to career aspirations in Mexican American women ( Caldera et al., 2003 ).

Self-Efficacy

Self-efficacy was considered a vital intrinsic factor in the career decision-making process of youth ( Howard et al., 2009 ; Fan et al., 2012 ; Guan et al., 2015 ; Hui and Lent, 2018 ). Howard et al. reported individualistic and collectivist dimensions in two different regions within the same country due to economic factors ( Howard et al., 2009 ). In collectivist cultures, students' self-efficacy was linked to their level of congruence with their parents. Whereas in individualistic cultural settings, like America, families encourage students to become self-sufficient and independent ( Mau, 2000 ; Fan et al., 2012 ; Shin and Kelly, 2013 ; Guan et al., 2015 ; Hui and Lent, 2018 ).

Outcome Expectations

Two studies carried out in collectivist cultural settings reported that youth's outcome expectation are contingent/dependent on the degree of perceived congruence with parents ( Cheung and Arnold, 2014 ; Sawitri et al., 2015 ). One article that studied the outcome expectations of youth in individualistic cultural setting reported that among students in the United States, strong career maturity, confidence, and outcome expectations were culturally based ( Lee, 2001 ).

Professional Development Opportunities

The opportunity for professional development is also a major intrinsic career-influencing factor ( Lee, 2001 ; Cheung and Arnold, 2014 ; Guan et al., 2015 ). University students in China were individually matured and influenced by career development opportunities ( Cheung and Arnold, 2014 ). While American students were shown to score higher for ideal occupations ( Guan et al., 2015 ), and influenced by goal motivation and strong career maturity ( Lee, 2001 ). This is similar to high school students in Indonesia, although dependent on congruence with parents ( Sawitri and Creed, 2015 ).

Interpersonal Factors

The literature discussed the extent to which family members, teachers/educators, peers, and social responsibilities influence youth's career decision-making.

Influence of Family Members

Agarwala suggested the father was seen as the most significant individual influencing the career choice of Indian management students ( Agarwala, 2008 ). This could be understood in the context of a reasonably patriarchal society. According to the study, most of the participants' fathers were mainly professionals, which may have motivated their career selection. In another study, mothers (52.50%) were regarded as the most significant family member that impacted positively on students' career choices ( Bojuwoye and Mbanjwa, 2006 ). Fathers (18.75%) were the second most significant individual, followed by siblings or guardians (16.25%) ( Bojuwoye and Mbanjwa, 2006 ). Good rapport among family members culminating in an effective communication within the family set up is crucial for laying sound foundation for career decision making. Higher career congruence with parents also increased career confidence and self-efficacy ( Sawitri et al., 2014 , 2015 ; Sawitri and Creed, 2015 , 2017 ; Kim et al, 2016 ). Furthermore, parents' profession influences career choice as children from agricultural backgrounds tend to take on their parents' job, while those from industrialized settings have more autonomy and career decidedness ( Howard et al., 2009 ).

Other familial influence on career decision-making according to the results of the only qualitative study in our review, include parental values, parental pressure, cultural capital and family obligations ( Polenova et al., 2018 ). The study indicated the apparent Asian American cultural preference for certain professions/careers. Students indicated that, parental opinion sometimes put an emphasis on a specific career. In that study, several participants emphasized that they were not forced, but “strongly encouraged” ( Polenova et al., 2018 ).

It's not like your parents are going to put a gun to your head and say “You're going to be a doctor” but from a young age, they say things like, “You're going to be a great doctor, I can't wait until you have that stethoscope around your neck.”

Polenova et al., 2018

Teachers and Educators

Teachers and educators are significant figures in the process of youth's career decision-making ( Yamashita et al., 1999 ; Howard et al., 2009 ; Gokuladas, 2010 ; Cheung et al., 2013 ; Cheung and Arnold, 2014 ). Cheung et al. and Howard et al. reported that in both collectivist and individualistic cultures, teacher are seen as significant figures who are agents of development and could have influence on students' career decision making ( Howard et al., 2009 ; Cheung et al., 2013 ). Cheung et al. further reported that students in Hong Kong rated perceived efficacy of teachers higher than parents due to lower level of parental education ( Cheung et al., 2013 ). In addition, Cheung and Arnold demonstrated a strong student dependence on teachers followed by peers and less of parents ( Cheung and Arnold, 2014 ).

Peer Influence

Two studies carried out in both cultural settings showed peer influence as a third potent force (after parents and teachers) that can significantly impact on the career decisions of youth, especially girls ( Howard et al., 2009 ; Cheung et al., 2013 ). Other studies reported that peers are a branch of the significant others and as social agents, they influence their kinds through social comparisons and acceptance ( Yamashita et al., 1999 ; Lee, 2001 ; Bojuwoye and Mbanjwa, 2006 ; Gokuladas, 2010 ; Cheung and Arnold, 2014 ).

Social Responsibilities

The impact of social responsibility as a driving force in youth career decision-making was identified by Fouad et al. (2016) , who noted that the career decision-making of South Korean youth is influenced by societal expectations. This is supported by another research, which suggested that societal expectations influenced youth career choices in both collectivist and individualistic cultures ( Lee, 2001 ; Mau, 2004 ; Polenova et al., 2018 ; Tao et al., 2018 ).

Emergent Bicultural Influence on Youth Career Choices

Of the 30 articles, only three explored the career decision making of bicultural youths ( Hui and Lent, 2018 ; Polenova et al., 2018 ; Tao et al., 2018 ). Strong family support influenced US-born and Asian-born students as shown by a recent study ( Hui and Lent, 2018 ). Hui and Lent found that students with stronger adherence to Asian values were more likely to perceive family support to pursue science related careers ( Hui and Lent, 2018 ). High sense of obligation to parents (filial piety), internal locus of control, and personal interests were identified as factors that influenced bi-cultural Asian American students' career decision making ( Polenova et al., 2018 ). Bicultural Chinese students who were acculturated to Canada were highly intrinsically motivated (internal locus of control and self-efficacy) in their career decision-making, while those who had stronger Chinese acculturations were influenced by extrinsic (financial stability) and interpersonal (family) factors ( Tao et al., 2018 ).

This systematic review examined the existent factors influencing the career choices of the youths from different countries around the globe, from either or both collectivist and individualistic cultural settings. Intrinsic and interpersonal factors were more investigated than extrinsic factors in the reviewed articles. In these articles, intrinsic factors included personal interests, professional advancement, and personality traits. Extrinsic factors included guaranteed employment opportunities, job security, high salaries, prestigious professions and future benefits. Meanwhile, interpersonal factors are the activities of agents of socialization in one's life, such as parental support, family cohesion, status, peer influence as well as interaction with other social agents such as school counsellors, teachers and other educators ( Lent et al., 2010 ; Shin and Kelly, 2013 ; Cheung and Arnold, 2014 ; Guan et al., 2015 ; Kim et al, 2016 ).

The three factors (intrinsic, extrinsic and interpersonal) relating to career choices are pervasive in both cultures. Their level of influence on the youth differs from culture to culture and appear to be dependent on perceived parental congruence leading to self-efficacy and better career choice outcomes. The studies carried out in Canada, Finland, Germany, Spain, Switzerland and United States of America showed a high level of individualism, which typifies intrinsic motivation for career choice. Youths in individualistic cultural settings were influenced by the combinations of intrinsic (personal interest, personality trait, self-efficacy), extrinsic (job security, high salaries) and to a lesser extent, interpersonal (parental guidance) factors and are encouraged to make their own career decisions ( Mau, 2004 ; Gunkel et al., 2013 ). In contrast, studies carried out in Argentina, Burkina Faso, Bulgaria, China, Croatia, Hong Kong, India, Indonesia, Japan, Mexico, Portugal, South Africa, South Korea, Taiwan, and Ukraine showed a high level of collectivism. Youths in collectivist cultures were mainly influenced by interpersonal (honoring parental and societal expectations and parental requirements to follow a prescribed career path) and extrinsic (prestigious professions) ( Mau, 2000 ; Gunkel et al., 2013 ). The opinions of significant others matter significantly to youths from collectivist cultural settings. Whereas, in individualistic cultures, youths tend to focus on professions that offer higher income and satisfy their personal interests ( Wüst and Leko Šimić, 2017 ; Polenova et al., 2018 ).

Parental influences were found to be significant in collectivist cultural settings ( Agarwala, 2008 ; Sawitri et al., 2014 ), implying that youths from this culture value the involvement of significant others, especially parents, and other family members, during their career decision-making processes. The activities of parents and significant others are very pivotal in the lives of the youth as they navigate their career paths. Cheung et al. reported the role of significant others (teachers) in influencing youth career choices when parents are unable to suitably play such role ( Cheung et al., 2013 ). Interestingly, one article focused on two different cultural orientations within one country and reported that parents' profession influence career choice as children from agricultural backgrounds tend to take on their parents' job, while those from industrialized settings have more autonomy and career decidedness ( Howard et al., 2009 ). This finding emphasizes the complex interplay of cultural context and the environment in the career aspirations of youths ( Fouad et al., 2016 ).

The review suggests that youths of collectivist orientations, tend to subordinate personal interests to group goals, emphasizing the standards and importance of relatedness and family cohesion ( Kim et al, 2016 ). However, such patterns of behavior may be conflicted, particularly during cross-cultural transitions. Parental influence have been reported to generate difficulties within the family and discrepancies over career choice decisions are not uncommon within both cultures ( Myburgh, 2005 ; Keller and Whiston, 2008 ; Dietrich and Kracke, 2009 ; Sawitri et al., 2014 ). The conundrum is will adolescents of collectivist orientation be comfortable with their cultural ethos after resettling in a different environment with individualistic cultural beliefs and practices?

Our study revealed that when youth transfer from their heritage culture to a different cultural setting, their cultural values are challenged and their career decision-making patterns may be affected. For instance, Tao et al. reported that students of Chinese descent who were acculturated to Canada primed personal interests, self-efficacy and financial stability instead of honoring parental and societal expectations in their career decision-making ( Tao et al., 2018 ). Similarly, Asian American students with stronger adherence to Asian values had a high sense of obligation to parents ( Polenova et al., 2018 ) and were more likely to perceive family support than their counterparts who were more acculturated to American values ( Hui and Lent, 2018 ). Our data also suggest a strong interplay of individualist and collectivist cultural values coexisting in harmony and jointly influencing how the youth in the current global environment define themselves, relate to others, and decide priorities in conforming to social/societal norms. Movement across cultures (migration) leads to several changes and adjustments in an individual's life. The internal and psychological changes the youth may encounter, otherwise known as psychological acculturation, also affect their career identity ( Berry, 1997 ). Given that only three out of the 30 reviewed studies were conducted in bicultural settings ( Hui and Lent, 2018 ; Polenova et al., 2018 ; Tao et al., 2018 ), further studies are recommended to examine the career choice practices of youths who have transferred from collectivistic to individualistic cultures and vice versa.

Practical Implications for Counsellors and Policy Makers

Social Learning Theory proposes that the role of a career counselor is to help clients expand their career choices and help clarify beliefs that can interfere or promote their career plans ( Krumboltz, 1996 ). Culture has a major influence on people's beliefs therefore, it is integral that career counselors are able to provide culturally responsive career directions to guide the youth in the pursuit of their career aspirations. Providing accessible sources of support and empowering youths to openly discuss their concerns relating to career decision-making will broaden the youths' understanding and this could have a significant impact on their academic and career pathways. Family support is important for all youths as they navigate their career explorations, especially for migrants. The role of counselors is not only limited to the youths, it can also benefit the entire family. Essentially, counselors can attempt to engage not just the youths in exploring academic and vocational opportunities, but also offer avenues for families to become involved and connected to the career decision-making processes.

Cultural identities combined with the varied expectations for achievement can be an overwhelming experience for the youth. Counselors can seize this opportunity to provide companionship and direction as the youth figure out their career pathways ( Gushue et al., 2006 ; Risco and Duffy, 2011 ).

The significance of a school environment that is conducive and embraces the racial and academic identity of its students can be a huge asset to boost youth morale. Gonzalez et al. reported that students who feel culturally validated by others at school and experience positive ethnic regard, have more confidence in their career aspirations ( Gonzalez et al., 2013 ). Career counselors together with other educators and service providers hold influential positions as they can furnish academic, cultural and social support that family members alone cannot provide.

Strengths and Limitations of This Study

The major strength of this review is that it has provided increased understanding of the cultural underpinnings of the factors that influence the career choices of youths. The study has also highlighted areas of knowledge gap in the literature, such as fewer studies exploring the impact of extrinsic factors on career choice and the need for more bicultural studies. However, the conclusions drawn from this review are limited to the data that were extracted from the studies identified. We acknowledge that there are caveats with the use of the concepts “collectivist and individualistic” to describe the cultural underpinnings of different countries as there are some fluidity around their usage as suggested by Hofstede (1991 , 2001) . However, the use of these concepts was helpful in classifying the cultural background of the participants included in this review. The findings of the studies reviewed within each country may not necessarily be representative of all the cultural orientations in those countries. Furthermore, researchers from different cultures (or studying different cultures) may have chosen to study only the variables that they believe will have relevance. Nevertheless, most of the studies reviewed had large sample sizes and were conducted in various countries across the globe.

Recommendations

• Of the 30 articles reviewed, only one involved qualitative study designs. Further qualitative studies on this topic are required to provide in-depth understanding of the influences on youth's career choices and to allow causal inferences to be made.

• There were only three articles that examined the career decision-making of the bicultural youths from the perspective of the mainstream and the heritage cultures. Better career choices for the bicultural youth will enhance their self-identity and lead to commitment to duty and eventual career satisfaction. Without harnessing the potentials of youths through career education and training, the bicultural and migrant youths' face uncertainties in the future in the host country. The rippling effects of such uncertainties in the future could have a detrimental effect on the country's economy. Therefore, there is the need for increased research activities in this area in host countries. Educational system planning should be developed to encourage youth to have self-efficacy and be more involved in job-related information seeking. This will be especially efficient in progressing bicultural youths who might have migrated with their parents into a new culture.

• Sound education at school can open ways for career decisions. Interventions designed to assist youth in strengthening their academic self-efficacy, internal motivation, and goal-setting strategies can foster improved career choice outcomes.

Conclusions

The three factors investigated in this study are pervasive in influencing the career decisions of youths in both individualistic and collectivist societies. In collectivist societies, parental intervention is understood as a requirement to support their children's efforts and equip them to be responsible and economically productive. Meanwhile, the standard practice in individualistic societies is for parents to endorse their children's opinions and encourage them to choose careers that make them happy. Overall, further research is imperative to guide the understanding of parental influence and diversity in bicultural and migrant youths' career prospects and their ability to use the resources available in their new environments to attain meaningful future career goals. Additional research, particularly qualitative, is required to explore the level of family involvement in youths' career choices among migrant families in different cultural settings.

Author Contributions

PA-T and BM-A extracted the data. BM-A, TE, and DL critically appraised and validated the study findings. PA-T developed the first draft of the manuscript. BM-A, TE, DL, and KT reviewed and edited the manuscript. All authors read and approved the final manuscript for submission.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: career choice, youths, collectivist culture, individualistic culture, cross-cultures

Citation: Akosah-Twumasi P, Emeto TI, Lindsay D, Tsey K and Malau-Aduli BS (2018) A Systematic Review of Factors That Influence Youths Career Choices—the Role of Culture. Front. Educ . 3:58. doi: 10.3389/feduc.2018.00058

Received: 31 January 2018; Accepted: 28 June 2018; Published: 19 July 2018.

Reviewed by:

Copyright © 2018 Akosah-Twumasi, Emeto, Lindsay, Tsey and Malau-Aduli. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Peter Akosah-Twumasi, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Career choices, representation of work and future planning: a qualitative investigation with italian university students.

1. Introduction

2. literature review, 3. the current study, 4.1. recruitment and participants, 4.2. instrument, 4.3. coding and analysis.

“I would like to become a director, but due to family pressures, I felt compelled to make a different decision” . (Participant 19, male)

“I would like to become a photographer, but mainly for economic constraints and for work difficulties in these areas, I am following a different path” . (Participant 52, male)

“I believe I am inclined to communicate with others, to understand their perplexities and to be able to direct them towards the right path” . (Participant 1, female)

“My secret wish is to be able to turn my passion into a job or an actor” . (Participant 56, male)

“I will see myself in a work environment where I can make the most of the skills that distinguish me, such as creativity, ingenuity and interpersonal skills” . (Participant 14, female)

“The job has to do with my identity” . (Participant 2, female)

“I have a job that meets my needs, expectations and desires, as well as useful for the betterment of society” . (Participant 36)

“I aim to get a steady and well-paid job that can thus gratify me” . (Participant 29, male)

“I have always thought that the digital sector could be the future, I believe it can offer a greater job placement” . (Participant 28, male)

“My goal is to become a web designer. I have already started my online shop, and I would like to expand it” . (Participant 39, female)

“For the moment I am studying social sciences, I am sure of the academic path I have taken but I am not yet clear about the specific job I am going to do” . (Participant 3, female)

“Finding a job will allow me to start a family” . (Participant 21, female)

6. Discussions

7. limitations, implications and future directions, 8. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Domains	Sub-Domains	Categories	Commonality
Influences on career choices	External factors	Family expectations	(1)
		Environmental conditions	(10)
	Internal factors	Vocation	(10)
		Resources	(15)
Representation of work	Meaning of work	Personal development	(3)
		Social role	(27)
	Working condition	Salary	(5)
		Enjoyable work	(2)
Future Plans	Ways of career plans	Clear career plans	(24)
		Confused career plans	(12)
	Future life plans	Family	(5)

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Felaco, C.; Zammitti, A.; Marcionetti, J.; Parola, A. Career Choices, Representation of Work and Future Planning: A Qualitative Investigation with Italian University Students. Societies 2023 , 13 , 225. https://doi.org/10.3390/soc13100225

Felaco C, Zammitti A, Marcionetti J, Parola A. Career Choices, Representation of Work and Future Planning: A Qualitative Investigation with Italian University Students. Societies . 2023; 13(10):225. https://doi.org/10.3390/soc13100225

Felaco, Cristiano, Andrea Zammitti, Jenny Marcionetti, and Anna Parola. 2023. "Career Choices, Representation of Work and Future Planning: A Qualitative Investigation with Italian University Students" Societies 13, no. 10: 225. https://doi.org/10.3390/soc13100225

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Career indecision: a systematic literature review

Journal of Humanities and Applied Social Sciences

ISSN : 2632-279X

Article publication date: 29 September 2022

Issue publication date: 2 May 2023

Research has been conducted to investigate the factors that influence career indecision. This study attempted to synthesize empirical research on career indecision to (1) find the common determinants over the last two decades and (2) find the factors/areas that need to be addressed for future research on career indecision.

Design/methodology/approach

This study used the systematic literature review (SLR) methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Following the predetermined inclusion criteria, 118 articles from the Scopus database were included for review.

From this research, the authors found four main determinants for career indecision, namely (1) career-related decision-making difficulties, (2) adolescent differences, (3) individual and situational career decision-making profiles (CDMPs) and (4) level of individual readiness for career choice, which have been researched in the last two decades. Additionally, eight factors/areas were found to be addressed in future research on career indecision which include those four common determinants, the other three determinants, namely (1) individual differences, (2) contextual/environmental factors, (3) social factors, and one outcome, subjective well-being.

Research limitations/implications

The study had limitations in conducting this research, and the findings of the study provide some theoretical and future research implications.

Practical implications

The seven determinants and the only outcome provide some implications for practitioners and policymakers.

Originality/value

The study found seven determinants and one outcome of career indecision derived from empirical studies conducted during 2000–2021.

• Career decision-making
• Career indecision
• Systematic literature review

Priyashantha, K.G. , Dahanayake, W.E. and Maduwanthi, M.N. (2023), "Career indecision: a systematic literature review", Journal of Humanities and Applied Social Sciences , Vol. 5 No. 2, pp. 79-102. https://doi.org/10.1108/JHASS-06-2022-0083

Emerald Publishing Limited

Copyright © 2022, K.G. Priyashantha, W.E. Dahanayake and M.N. Maduwanthi

Published in Journal of Humanities and Applied Social Sciences . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and no commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode .

1. Introduction

Career decision-making refers to the ability of an individual's thought processes to incorporate self-knowledge with occupational knowledge to make occupational choices ( Brown and Brooks, 1996 ). Individuals confident of their passion and possessing self-identification skills and abilities can direct their informed occupational knowledge to choose the best career that suits them. This career decision-making process has become a foremost developmental task for many young adults ( Citarella, 2018 ). Nevertheless, when individuals are undecided about their preferred career directions, they become career indecisive, often deemed a critical issue among high school and university students ( Gyarteng-Mensah et al. , 2022 ; Lipshits-Braziler et al. , 2016 ).

Career indecision is “the inability to specify an educational or occupational choice” ( Kelly and Lee, 2002 ). This phenomenon has been extensively researched in vocational psychology ( Gati et al. , 2011a ; Holland and Holland, 1977 ). This phenomenon is described with different determinants grounded by decision theory ( Germeijs and De Boeck, 2002 ), self-determination theory ( Ryan and Deci, 2000 ), social cognitive career theory ( Lent et al. , 2002 ) and Gestalt psychotherapy theory ( Marco et al. , 2003 ), to name a few. The determinants emphasized many aspects. Some research shows that expanding educational and vocational options are determinants of career indecision. These options equip the students with sufficient education and skill development that determine students' commitment to a chosen career field. Such commitments can evoke anxiety and distress among the students as the wrong decision would bring negative repercussions ( Lipshits-Braziler et al. , 2016 ). Other research studies have focused on various determinants ( Dahanayake and Priyashantha, 2020 ; Maduwanthi and Priyashantha, 2018 , 2020 ). Some of these have been categorized as social ( Abu Talib and Tan, 2009 ; Jung, 2018 ), emotional ( Fabio et al. , 2013 ) and cognitive and personality-related facets ( Brown et al. , 2012 ; Gati et al. , 2011a ).

Additionally, various other determinants can be found in the empirical research landscape in various contexts. They require to be analyzed for clustering and synthesizing in a logical base. Such a synthesis will contribute to the theory and instrument development and help identify the research gaps and future research directions. Furthermore, knowing the empirically proven determinants of career indecision might benefit policymakers and career counselors in determining necessary actions and treatments ( Zobell et al. , 2019 ). Even though there were some meta-analyses ( Bian, 2021 ; Udayar et al. , 2020 ), they have limitations in addressing the determinants of career indecision in empirical studies conducted during the 2000–2020 year period. Thus, there is a solid need to synthesize such determinants.

Accordingly, this study was conducted as a systematic literature review (SLR), which systematically and quantitatively analyzed selected empirical literature on career indecision in the last two decades. The objectives of this research were to (1) find the common determinants in career indecision over the last two decades and (2) find the factors/areas that need to be addressed for future research on career indecision.

2. Methods and methodology

2.1 study selection process and methods.

The research was carried out in an SLR. The article selection, analysis and reporting of the findings were made following the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)” guidelines ( Liberati et al. , 2009 ). The PRISMA is highly recommended for SLRs as it prevents bias in article selection, analysis and reporting of the findings ( Petticrew and Roberts, 2006 ; Priyashantha et al. , 2021a , 2021b ).

The PRISMA flow diagram used to select the articles consists of three steps: “identification, screening and included.” The identification stage includes choosing search terms, criteria and databases. Accordingly, “career indecision” was the search term and criterion. Then Scopus was the database used to search the articles.

Article screening included automatic and manual screening, retrieval of screened articles and determining their eligibility for review. At this point, the inclusion criteria were applied to include the articles. The article inclusion criteria are given in Table 1 . Accordingly, the year range from 2000–2021 was selected as an inclusion criterion as no similar studies specifically targeted the period. Empirical journal articles were used as an inclusion criterion for three reasons: first, they are recommended for SLRs ( Tranfield et al. , 2003 ; Xiao and Watson, 2019 ). Second, they maintain consistency in methodological quality in getting findings ( Okoli and Schabram, 2010 ), ensuring all selected articles' internal validity ( Petticrew and Roberts, 2006 ). Finally, journal articles are treated as reliable since they undergo a rigorous peer-review procedure.

The automatic screening was done through the default limiting features of Scopus. Thus, the limiting options included the year range: 2000–2021, document type: articles, source type: journal and language: English based on the inclusion criteria. After that, the remaining articles' complete versions were downloaded and manually screened. At the manual screening, the study authors independently reviewed each abstract of the downloaded article and assessed them against the inclusion criteria. After removing unnecessary articles, the study authors manually and independently examined the remaining articles for their methodological eligibility. The eligibility assessment guarantees that articles of high methodological quality are included ( Meline, 2006 ). A detailed explanation of how many articles were excluded on each criterion is given in section 3.1 .

2.2 Article risk of bias assessment

The quality of a review is reduced due to researcher bias in article selection and analysis ( Kitchenham and Charters, 2007 ). The selection bias can be avoided by following a review protocol, a systematic, objective article selection procedure ( Priyashantha et al. , 2022 ; Xiao and Watson, 2019 ), and performing a parallel independent quality assessment of articles by two or more researchers ( Brereton et al. , 2007 ). The analysis bias can be avoided through a preliminary protocol design that predetermines the analysis methods ( Xiao and Watson, 2019 ). Thus, they all were followed in this study to avoid bias.

2.3 Methods of analysis

The analysis method used in this study was bibliometric analysis. The tools like Biblioshiny and VOSviewer were used to generate the results for analysis. Bibliometric analysis is a scientific technique for examining scientific activity in a study ( Paule-Vianez et al. , 2020 ). Two types of it include (1) evaluation, performance and scientific productivity analysis and (2) scientific maps ( Cobo et al. , 2012 ). The maps, generally called bibliometric networks, are built based on different information from an article ( Callon et al. , 1983 ). One such is the keywords in an article. The co-occurrence of keywords in an article could result in a variety of relationships between keywords ( Aparicio et al. , 2019 ). The relativization of the links between the keywords is required to obtain crucial information in a study. As a result, by default, the VOSviewer employs association strength normalization and generates a network in two dimensions known as “keyword co-occurrence network visualization” that has nodes representing each keyword located close to each other in a cluster if they are strongly related ( van Eck and Waltman, 2014 ). As a result, a cluster can be used to represent a shared theme ( Priyashantha et al. , 2021a , 2021b ). The study's first goal was to identify the common areas addressed; hence, this keyword co-occurrence analysis was used to achieve that.

The keyword density visualization is a variation of keyword co-occurrence network visualization. It was used to accomplish the study's second objective: to find the factors/areas that need to be addressed for future research in career indecision. According to the VOSviewer manual, the density of keywords at each location in the density visualization map is depicted by color ranges ranging from blue to green, yellow and red by default. The closer a location's color is red, the more keywords it has nearby and the higher its weight. The fewer keywords nearby and the lower the weights, the closer a point's color is to green. The color yellow denotes that the keywords in a point are average. Thus, the keywords in the blue and green areas are said to be focused on more research.

Biblioshiny of R software was also used to generate “basic information about the article set,” “year-by-year article publishes” and “average citations received.” The VOSviewer software created the “country-wise article publications” and “journal-wise article publishes.” These were shown to give an overview of the profile of the article set chosen for the review.

3. Results and findings

3.1 study selection.

The first stage required identifying the articles as the PRISMA article selection flow diagram was used to select the articles to be reviewed. Scopus generated 450 articles at this point for the predetermined search criteria mentioned in section 2.1 . The automatic screening functionality of Scopus was used for the initial screening of those articles. The task was completed with the inclusion criteria listed in Table 1 .

Out of the 450 articles, 66 were rejected as they did not meet the first inclusion criterion. There were 158 articles with the keyword career indecision, and the remaining 226 articles were excluded because they did not meet the second inclusion criterion. The third inclusion criterion was a focus on publications in academic journals. As a result, the books ( n  = 8), conference proceedings ( n  = 6) and book series ( n  = 2) on career indecision were excluded because they did not meet the third criterion. Then the reviews ( n  = 11), book chapters ( n  = 8), conference papers ( n  = 7) and notes ( n  = 1) were also excluded as they did not meet the fourth criterion. Other than that, the articles in other languages ( n  = 26) were excluded as they did not meet the fifth inclusion criterion, focusing on the article in English.

Then 123 articles were retained for manual screening, and their list containing title, authors, journal, publication year, abstract and received citations were downloaded into an MS Excel sheet. After that, the study authors independently assessed each abstract against the inclusion criteria and found that three articles were irrelevant according to the fourth inclusion criterion. They were excluded based on concept papers ( n  = 2) and irrelevant papers ( n  = 1). The remaining 120 articles were screened by the authors manually for their eligibility assessment. The sixth inclusion criterion mentioned in Table 1 , “empirical research that employed quantitative methodologies and meta-analyses,” was used in that task. Accordingly, three articles (qualitative reviews n  = 2 and viewpoint articles n  = 1) were excluded as they did not meet the sixth inclusion criterion. Finally, 118 articles were retained for review, and the MS Excel sheet was then adjusted to meet the bibliographic analysis. The article selection flow diagram is depicted in Figure 1 .

3.2 Article characteristics

Table 2 shows the primary information of the articles included in the review. There were 118 articles published from 2000 to 2021 in 38 journals by 232 authors in 27 countries. The average citation received per article is 20.76, and the total number of references considered for the review was 5,494. Further, the total keywords included in the review were 288.

Annual article production, average article citations received per year, the most relevant sources from which the articles are published and country-specific article publications are all essential characteristics of the article set. Thus, Figure 2 shows the annual article production, indicating a gradual increase. It also shows researchers’ increasing concern about career indecision. Figure 3 shows the average article citations received per year. It reveals a gradual decrease in citations. Citations received for an article represent its popularity. Thus, the decreasing trend of citations indicates a decrease in career indecision research's popularity. The most relevant sources of the articles published are shown in Figure 4 . It shows the 20 journals which published the highest number of articles. Accordingly, the Journal of Career Assessment (39 articles), Journal of Vocational Behavior (22 articles) and Journal of Career Development (22 articles) are first, second and third, respectively, in career indecision article publications. Besides that, career development quarterly has published seven articles. Three articles each have been published by the Journal of Counselling Psychology and the Orientation Scolaire et Professionnelle . The Australian Journal of Career Development , the Frontiers in Psychology and the International Journal for Education and Vocation have published two articles each. The rest of the journals listed in Figure 4 have published one article each. Figure 5 depicts the number of articles published in each country. The size of the colored nodes in the figure represents the number of publications in each country. As a result, the USA (39 articles), Israel (29 articles), France (9 articles) and South Korea (9 articles) rank first, second and third in country-wise publications, respectively.

Additionally, Table 3 shows the research design used for the selected articles. Out of the 118 articles, 94 used cross-sectional design, 22 used a longitudinal design and two used meta-analyses as their research design. As a result, most of the included articles represented cross-sectional design studies. Thus, Table 3 information reveals the methodological quality of the included articles.

3.3 Results of articles

This section contains the results of the articles and their synthesis. The section is divided into two sections to fulfill the study's two objectives: (1) to find the common determinants in career indecision over the last 2 decades and (2) to find the factors/areas that need to be addressed for future research in career indecision. The first objective is addressed in Section 3.3.1 , while the second is addressed in Section 3.3.2 .

3.3.1 Common determinants in career indecision over the last two decades

The keyword co-occurrence network visualization, shown in Figure 6 , was created using VOSviewer version 1.6.18 to address the study's first objective. The keywords with a minimum of five occurrences and above in the articles were considered to create it. There were 12 keywords, including the main keyword, career indecision and its interrelationships with other keywords are denoted in Figure 6 . The line thickness in the figure denotes the strength of the relationship between the keywords. The size of the node denotes the frequency of occurrences. Higher frequency denotes higher the size of the nodes. Thus, while strongly correlating career counseling, career decision-making and career decision-making difficulty with career indecision, they can be said to have frequently occurred in studies. It means that those four areas have been widely researched.

Four clusters denote the nodes in Figure 6 in different colors: red, green, blue and yellow. Different clusters portray how investigations have differed in different areas of investigations. The different clusters of keywords and their basic bibliometric information are given in Table 4 . Thus, the four clusters seem to represent the common themes of (1) career-related decision-making difficulties, (2) adolescents' differences, (3) individual and situational career decision-making profiles (CDMPs) and (4) level of individual readiness for career choice. These findings related to each theme are explained below.

3.3.1.1 Cluster 1– red: career-related decision-making difficulties

The keywords career assessment, career choice, career counseling and career decision-making difficulties fell into this cluster. As the cluster should share a common theme, including the source journals and citation information for the cluster is crucial. Accordingly, the nine journals which carried articles containing those keywords are listed in Table 4 . Furthermore, 1,110 citations were found for the articles containing those keywords. As a result of the abundance of empirical research and citations, the data in this cluster have a substantial impact. Moreover, the findings associated with each keyword are explained as follows.

Career assessment: The lack of career assessment determines career indecision ( Essig and Kelly, 2013 ). Career assessment tools include the Career Decision-Making Difficulties Questionnaire (CDDQ), the CDMPs Questionnaire ( Gati and Levin, 2014 ) and the Emotional and Personality-Related CDDQ ( Gati and Levin, 2014 ; Saka and Gati, 2007 ). Further, Career Assessment Diagnostic Inventory (CADI) ( Vidal-Brown and Thompson, 2001 ) and the Career Factor Inventory (CFI) ( Abu Talib and Tan, 2009 ) have also been used for career assessments.

Career choice: Career choice difficulties/anxiety determines career indecision ( Faria, 2013 ; Hacker et al. , 2013 ; Hagiwara and Sakurai, 2008 ). The comprehensive information gathering, analytic information processing, a more internal locus of control, more effort invested, less procrastination, greater speed of making the final decision, less dependence on others and less desire to please others are some factors affecting career choices ( Gadassi et al. , 2015 ).

Career counseling: Career counseling is an effective coping mechanism/determinant for dealing with career indecision ( Akyol and Bacanlı, 2019 ; Argyropoulou et al. , 2007 ; Maree, 2020 ; Obi, 2015 ; Stauffer et al. , 2013 ; Vertsberger and Gati, 2016 ). It is sought by its higher expected effectiveness, perceived severity of career-planning difficulties and motivation to engage in career-adjustment activities ( Braunstein-Bercovitz and Lipshits-Braziler, 2017 ). Counselors perceive productive coping and support-seeking as good strategies for career indecision. Productive coping entails six strategies: instrumental information seeking, emotional information seeking, problem-solving, flexibility, accommodation and self-regulation ( Lipshits-Braziler et al. , 2015 ). Support-seeking includes instrumental support, emotional support and delegation ( Lipshits-Braziler et al. , 2015 , 2016 , 2017a) .

Career decision-making difficulties: career decision-making difficulties determine career indecision ( Lam and Santos, 2018 ; Phang et al. , 2020 ; Silva et al. , 2021 ; Taber, 2013 ). Career decision-making difficulties are measured through CDDQ ( Akyol and Bacanlı, 2019 ; Levin et al. , 2020 ). Thus, career decision-making difficulties can be reduced through workshops and counseling programs that develop career decision-making self-efficacy ( Gadassi et al. , 2013 ).

Regarding the findings under each keyword, lack of career assessments, lack of career choice and absence of career counseling are reasonably said to be considered under the common theme of career decision-making difficulties.

3.3.1.2 Cluster 2 – green: adolescents' differences

The keywords that fell into this cluster were adolescence, career exploration, career indecision and personality. Since the subject of the investigation of this study was career indecision, the other three keywords, excluding career indecision, were considered for review. As stated in cluster 1, as these keywords should share common characteristics, evaluating the source journals and citation information for the cluster is crucial. Accordingly, we found nine journals as the sources for articles containing those keywords, while such articles received 360 citations, as listed in Table 4 . As stated in cluster 1, more citations and source journals for the cluster imply an abundance of empirical investigations, and the cluster is deemed to have a significant impact. Further, findings associated with each keyword are explained below.

Adolescence: Most career indecision research has been done with adolescents ( Citarella, 2018 ; Emmanuelle, 2009 ; Faria, 2013 ; Marcionetti and Rossier, 2017 ; Nalbantoglu Yilmaz and Cetin Gunduz, 2018 ; Vignoli, 2015 ) as they are open to different careers.

Career e xploration: Career exploration reduces career indecision ( Faria, 2013 ; Kin and Rameli, 2020 ; Marcionetti and Rossier, 2017 ; Paixão and Gamboa, 2017 ; Park et al. , 2017 ; Vignoli, 2015 ).

Personality: Personality determines career indecision ( Gadassi et al. , 2012 ; Kin and Rameli, 2020 ; Marcionetti and Rossier, 2017 ; Penn and Lent, 2019 ). Notably, emotional intelligence reduces career indecision, and ego resilience and self-control also reduce career indecision through a higher future perspective ( Park et al. , 2020 ). Besides neuroticism and conscientiousness, parents' awareness levels predict career indecision ( Faria, 2013 ; Marcionetti and Rossier, 2017 ; Penn and Lent, 2019 ).

Thus, the career exploration problems with lack of motivation, personality problems and parents' awareness levels mentioned above seem to represent the adolescents' differences.

3.3.1.3 Cluster 3 – blue: individual and situational career decision-making profiles

Two keywords, namely career decision-making and CDMPs, fell into this cluster. Since they could share common characteristics, it is essential to state the source journals and citation information for the cluster. Accordingly, four journals were identified with articles containing these keywords, with a citation count of 151, as listed in Table 4 . The information indicates a reasonably low level of publications and citations compared to the first and second clusters. Further, the findings associated with each keyword are explained as follows.

Career d ecision - m aking: Most CDMPs have been investigated with the keyword career decision-making ( Gadassi et al. , 2012 , 2013 ; Gati et al. , 2010 , 2012 ; Lam and Santos, 2018 ).

Career d ecision- m aking p rofile (CDMP): The CDMP is how individuals make career decisions ( Gati et al. , 2010 ). The CDMP has 12 individual and situational dimensions representing a continuum on a bipolar scale ( Lipshits-Braziler et al. , 2019 ). Out of the dimensions, “comprehensive information gathering,” “analytic information processing,” “internal locus of control,” “much effort invested,” “less procrastination,” “greater speed of making the final decision,” less dependence on others and “less desire to please others” results to lower career indecision ( Gadassi et al. , 2013 , 2013 , 2013 ; Ginevra et al. , 2012 ; Vertsberger and Gati, 2015 ; Willner et al. , 2015 ).

When evaluating the findings, the CDMP describes how individuals make career decisions based on situational and individual factors. Hence, considering a theme on individual and situational career decision-making profiles is reasonable.

3.3.1.4 Cluster 4 – yellow: the level of individual readiness for career choice

Decision-making self-efficacy and career maturity were the keywords that fell into this cluster. The articles associated with these two keywords have been published in seven journals. Table 4 lists the titles of those journals. In addition, the two keywords associated with each article have received 178 citations. The following subheadings explain the findings related to these two keywords.

Career d ecision- m aking s elf- e fficacy: Career decision-making self-efficacy determines career indecision negatively ( Faurie and Giacometti, 2017 ; Mao et al. , 2017 ; Park et al. , 2020 , 2021 ; Penn and Lent, 2019 ). Self-efficacy has different types: generalized self-efficacy, process-related self-efficacy, content-related self-efficacy and self-esteem, which reduces career indecision ( Udayar et al. , 2020 ).

Career m aturity: Career maturity is the ability and stability in a career ( Super, 1980 ). More career matured people make independent career-related choices ( Prideaux and Creed, 2001 ) and less career indecision ( Creed et al. , 2005 ; Park, 2015 ; Patton and Creed, 2007 ).

The findings above appear that both the keywords are related to the individual rather than contextual ( Lipshits-Braziler et al. , 2017a , b ). Moreover, meta-analytic research has proven that the lack of readiness is described by low career decision-making self-efficacy and low career-related maturity ( Brown and Rector, 2008 ; Gati and Saka, 2001 ; Xu and Bhang, 2019 ). Thus, a common theme of “level of individual readiness for career choice” is reasonable for this cluster.

As illustrated in Figure 6 , all keywords are connected to career indecision. It means that each keyword is associated with career indecision. The corresponding findings for each cluster's keywords emphasize that the keywords are determinants of career indecision. Therefore, four common themes, namely (1) career-related decision-making difficulties, (2) adolescent differences, (3) individual and situational CDMPs, and (4) level of individual readiness for career choice, developed for each cluster, can be treated as determinants of career indecision. Additionally, we identified that many journals had published articles on the first and second determinant categories rather than the third and fourth. Furthermore, the amount of citations for an article reflects its impact. As a result, more citations for each category of determinants suggest a greater influence. As a result, the first and second categories of determinants have a significant impact.

3.3.2 Factors/areas that need to be addressed for future research

To achieve the study's second objective, we checked all the keywords used in the research to see whether the factors/areas represented by the keywords could create established knowledge. The areas represented by the keywords that cannot generate established knowledge should be subjected to further research. To determine this, we created keyword co-occurrence density visualization using VOSviewer by entering all the keywords shown in Figure 7 . The density visualization map usually consists of three colors, red, yellow and green, as shown in Figure 7 .

Keywords falling into the red area imply much research related to the area represented by the keywords. Hence, there is established knowledge related to that area ( van Eck and Waltman, 2014 ). According to Figure 7 , career indecision is the only keyword that falls into the red area. Although it is implied that there has been a large amount of research related to career indecision, it is difficult to determine that there is a connection with other keywords as a number of the other keywords have fallen into the red area. Moreover, if a keyword falls in the yellow area, it implies a moderate amount of research, whereas keywords falling in the green area means very little research is done. In that case, moderate and little research does not create established knowledge. Complying with this argument, the four determinants, explained in section 3.3.1 , indicate insufficient research for established knowledge as they fall into the yellow and green areas in Figure 7 . Thus, future researchers need to conduct further research focusing on those areas.

Furthermore, while we discovered four determinants of career indecision using keywords with more than five occurrences, as shown in section 3.3.1 , we wanted to see whether keywords with fewer than five occurrences represented common areas. As a result, we utilized VOSviewer to pick keywords with fewer than five occurrences, which were then clustered into four, as shown in Table 5 .

The four clusters shown in Table 5 share the common themes of individual differences, contextual/environmental factors, social factors and outcomes of career indecision. The theme of individual differences represents 17 keywords. Articles in nine journals have reported those keywords. Since this cluster has received the highest citations compared to the other three clusters, its impact is said to be higher. The second cluster contained three keywords representing the common theme of contextual/environmental factors. Articles in three journals have reported them, and the cluster has received 35 citations. The third cluster represents the social factors, which have three keywords. Articles have reported them in three journals, and the cluster received the least number of citations. The fourth cluster represents the outcome of career indecision. The only keyword included in it was subjective well-being. An article published by the Journal of Vocational Behavior has reported it and obtained 28 citations. In addition to the journal and citation information, the main findings related to each keyword are given below.

Individual differences: Individual differences account for self-oriented perfectionism ( Gati et al. , 2011b ; Kang et al. , 2020 ; Page et al. , 2008 ), level of motivation ( Hagiwara and Sakurai, 2008 ; Jung, 2018 ), decisional procrastination ( Bańka and Hauziński, 2015 ), career decisional ambiguity tolerance ( Park et al. , 2019 ), career readiness ( Kleiman et al. , 2004 ) and valence ( Walker and Tracey, 2012 ). Additionally, emotional intelligence ( Phang et al. , 2020 ; Puffer, 2011 ), dysfunctional thinking ( Boysan and Kagan, 2016 ), perceived effectiveness of coping strategies ( Lipshits-Braziler et al. , 2017b ) and perceived nonproductive coping style ( Lipshits-Braziler et al. , 2017b ) accounts the individual differences. Furthermore, gender differences ( Atitsogbe et al. , 2018 ; Lam and Santos, 2018 ), anxious attachment ( Braunstein-Bercovitz, 2014 ), career anxiety ( Nalbantoglu Yilmaz and Cetin Gunduz, 2018 ) and decision-making strategies (aspiration and procrastination) ( Shin and Kelly, 2015 ) also represent the individual differences. Thus, all these individual differences were found to impact career indecision.

The contextual/environmental factors: The contextual/environmental factors account for the academic major of the students ( Kin and Rameli, 2020 ), barriers to careers ( Jaensch et al. , 2015 ) and level of certainty of the career ( Constantine and Flores, 2006 ). They were found to impact career indecision.

The social factors: The social factors include the parents' and counselors' emotional support ( Mao et al. , 2017 ). They were found to impact career indecision. Additionally, researchers have investigated emerging adults ( Uthayakumar et al. , 2010 ) or young adults ( Park et al. , 2021 ) as the subject of this career indecision, which was also categorized into this category.

Outcomes: The only outcome of career indecision found was subjective well-being ( Uthayakumar et al. , 2010 ).

In a nutshell, as this section deals with the study's second objective of finding factors/areas that need to be addressed in future research in career indecision, two ways were deployed with keywords. The first was the keywords with more than five occurrences, and the second was those with less than five occurrences. Analysis of keywords with more than five occurrences found four determinants as follows: (1) career-related decision-making difficulties, (2) adolescent differences, (3) individual and situational CDMPs and (4) level of individual readiness for career choice. Analysis of keywords with less than five occurrences derived four areas, including three types of determinants, namely (1) individual differences, (2) contextual/environmental factors, (3) social factors and one outcome (subjective well-being). Based on these two analyses, we found seven determinants and one outcome. Since these were systematically and logically identified through the keyword co-occurrence density visualization, as mentioned in Figure 7 , it was revealed that the findings were insufficient for established knowledge. Therefore, future researchers should focus on all these eight areas for more research.

3.4 Reporting bias assessment

The PRISMA guidelines provide a standard reporting format that eliminates biases caused due to missing the results of the included articles to be reported. Thus, the current study's report complied with the PRISMA format that avoided the authors using their format.

4. Discussion

This study was designed based on the SLR that attempted to synthesize the career indecision empirical research published during the 2000–2021 period. It was based on two objectives: (1) to find the common determinants in career indecision over the last two decades and (2) to find the factors/areas that need to be addressed for future research on career indecision. The first objective was achieved by finding four common career indecision determinants. They are (1) career-related decision-making difficulties, (2) adolescent differences, (3) individual and situational CDMPs and (4) level of individual readiness for career choice. The second objective was achieved by finding seven determinants and one outcome of career indecision recommended for future research. The seven areas of determinants include (1) career-related decision-making difficulties, (2) adolescent differences, (3) individual and situational CDMPs, (4) level of individual readiness for career choice, (5) individual differences, (6) contextual/environmental factors and (7) social factors. The only outcome of career indecision found was subjective well-being.

All seven determinants and one outcome can be integrated into a holistic model and tested by future researchers. Since each common determinant and outcome was obtained from different keywords, they might also be viewed as dimensions for each determinant and outcome. These keywords would help construct a measurement instrument to test the suggested holistic model. These are the study's main theoretical contributions.

Additionally, the study found gaps in determinants such as cultural values, institutional and technological support for dealing with career indecision, and more outcomes of career indecision.

Although this study satisfied almost all of the SLR requirements, one limitation was that the articles were drawn from a single database. Extracting more articles could have been done if more databases had been targeted. Moreover, the study selected only the empirical studies to maintain the articles' validity as they complied with the SLR methodology. The results could have been different if other article types had been selected.

5. Conclusion

Various determinants determine occupational decision-making in career-related lives. More research has been conducted to investigate the determinants that influence career indecision. This study attempted to synthesize the career indecision empirical research to (1) find the common determinants in career indecision over the last two decades and (2) find the factors/areas that need to be addressed for future research on career indecision. An SLR methodology, along with PRISMA guidelines, was adopted. Following the predetermined inclusion criteria, 118 articles were included for the review from the Scopus database.

The first objective was achieved by findings of four areas of determinants for career indecision. They include (1) career-related decision-making difficulties, (2) adolescent differences, (3) individual and situational CDMPs and (4) level of individual readiness for career choice. The second objective was achieved by finding eight areas for future research. They include all those common four determinants found for objective one, three more determinants, namely (1) individual differences, (2) contextual/environmental factors and (3) social factors, and the only outcome, subjective well-being.

6. Practicality and research implications

When the practicality of the findings is concerned, the seven determinants of career indecision imply that policymakers, decision-makers or employees must systematically assess the causes before taking ad-hoc interventions. Notably, assessing career decision-making difficulties and CDMPs, knowing individual differences and understanding contextual and social factors for career indecision will help decision-makers to make counseling interventions. Knowing those factors by the counselors will help increase their counseling sessions' effectiveness. These different determinants imply that the decision-makers and the counselors are required to follow different strategies. Knowing that there are such determinants and outcomes of career indecision encourages indecisive career employees to seek counseling interventions. Additionally, as our study found that employee well-being can be increased by reducing career indecision, the decision-makers imply investing more effort in increasing career decisiveness.

The theoretical implication includes the seven determinants, and the only outcome, subjective well-being, can be incorporated into a comprehensive conceptual model. As a result, hypotheses can be developed for each determinant and outcome as they have been found based on empirical evidence. In this manner, the model may be empirically tested, and the measuring instrument can be created by utilizing the areas represented by each keyword in each cluster.

The findings have numerous implications for future researchers. First, the seven determinants and outcomes we identified can be researched. The seven determinants include (1) career-related decision-making difficulties, (2) adolescent differences, (3) individual and situational CDMPs, (4) level of individual readiness for career choice, (5) individual differences, (6) contextual/environmental factors and (7) social factors whereas the only outcome derived was subjective well-being. The gaps identified in this research, such as the determinants of cultural values and institutional and technological support on career indecision and more individual, organizational and social outcomes, could be regarded as possible implications in future research.

PRISMA article selection flow diagram

Annual article production

Average article citations received per year

The most relevant sources the articles published

Country-wise article publications

The map of keyword co-occurrence network visualization

The map of keyword co-occurrence density visualization

Article inclusion criteria

Inclusion criterion	Focus on
1	publications from 2000–2021
2	publications with the keyword; career indecision
3	publications in academic journals
4	publications as articles
5	the articles in the English language
6	empirical research that employed quantitative methodologies and meta-analyses

Authors’ conception, 2022

Description	Results
Timespan	2000:2021
Journals	38
Articles	118
Average years from publication	8.56
Average citations per article	20.76
Average citations per year per doc	1.823
References	5,494
Authors' keywords	288
Authors	232
Countries	27

Review Data, 2022

Research design	Number of articles
Cross-sectional studies	94
Longitudinal studies	22
Meta-analyses	02
Total articles	118

Review data, 2022

Funding : No funding was available for this research.

Authors’ contributions: All authors contributed to the study conception, design, material preparation, data collection and analysis. All versions of drafts of the manuscript were written by Author 1. The other authors helped with the article selection process, and the revisions were made per the reviewers' comments. All authors read and approved the final manuscript.

Data availability: Data collected during the current study are not publicly available. However, they can be available from the corresponding author upon reasonable request.

Ethical statement: The authors confirm that this research paper meets the ethical requirements, and the authors have fully considered all foreseeable ethical implications of the research study, both intended and unintended.

Conflicts of interest: There are no conflicts of interest.

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Career Preference and Factors Influencing Career Choice among Undergraduate Pharmacy Students at University of Khartoum, Sudan

Ahmed h. arbab.

1 Department of Pharmacognosy, Faculty of Pharmacy, University of Khartoum, Khartoum 11111, Sudan; [email protected]

Yasir A. M. Eltahir

2 Department of Respiratory Care, College of Applied Sciences, Almaarefa University, Riyadh 11597, Saudi Arabia; as.ude.tscm@rehatY

3 Department of Anatomy, Faculty of Medicine, Kordofan University, Elobeid 51111, Sudan

Fatima S. Elsadig

4 Faculty of Pharmacy, University of Khartoum, Khartoum 11111, Sudan; moc.liamg@501bahihsamitaF

Bashir A. Yousef

5 Department of Pharmacology, Faculty of Pharmacy, University of Khartoum, Khartoum 11111, Sudan

Associated Data

All data used and analyzed during the current study are available from the corresponding author on reasonable request.

The pharmacy profession has expanded and adapted to changes in community needs. Although career planning and understanding the determinants of career choice are essential, there remains a lack of studies exploring factors influencing future career plans. This study was conducted to identify career preferences and factors influencing future career choices among undergraduate pharmacy students. A cross-sectional study was carried out at the Faculty of Pharmacy, University of Khartoum. A self-administered questionnaire was used to collect data from randomly selected participants. Out of 220 respondents, 85.9% were females. The average age of the respondents was 21.7 ± 1.5 years. Clinical pharmacy was selected as the most preferred future career domain (30%), followed by academia and research (12%), the pharmaceutical industry (11%), and community pharmacy (10.5). Approximately 20% of participants reported a preference for moving abroad for work. Regarding factors influencing future career domain choice, participants ranked training in the workplace (80%) and curriculum content (70%) as the top faculty-related factors, while interaction with practicing pharmacists (71.8%) and salary (78%) were the major personal-related and job-related factors. This study emphasized the importance of understanding job preferences and the factors influencing career choice, and could be useful in ensuring a future balance between professional domains and meeting society’s evolving expectations.

1. Introduction

The pharmacy profession has transformed and adapted itself to changes in the health care system and social needs. It has expanded from a drug-focused profession to include patient care and service-driven professions [ 1 , 2 ]. Until the twentieth century, pharmacists’ responsibilities were limited to compounding, quality control, and dispensing. In 1997, the World Health Organization (WHO) introduced the ‘seven-star pharmacist’ concept, covering the roles each pharmacist must perform: caregiver, decision-maker, communicator, manager, lifelong learner, teacher, and leader [ 3 ]. Two criteria, ‘researcher’ and ‘entrepreneur’, were added later, which culminated in the ‘nine-star pharmacist’ concept [ 4 ]. In 2000, the seven-star pharmacist concept was adopted in the International Pharmaceutical Federation (FIP) policy statement on good pharmacy education practice [ 5 ]. Currently, in addition to their classical roles as drug specialists, pharmacists work in multi-disciplinary settings to deliver pharmaceutical care. As a part of the health care system, their roles involve patient-oriented services, patient education, and counseling about medication and patients’ quality of life [ 6 ].

In Sudan, the pharmacy profession is locally governed by the Sudan Medical Council and Directorate General of Pharmacy. Undergraduate pharmacy education lasts for 5 years, and the student acquires a Bachelor of Pharmacy (B. Pharm) degree upon completion. This is followed by a mandatory one-year internship in a governmental pharmacy sector, and then a license is issued after passing an exam conducted by the Sudan medical council. About 67% of the pharmacist workforce is employed in private retail pharmacies; 19% are employed in the public sector, including hospitals and regulatory bodies; and less than 2% are employed within pharmaceutical manufacturing [ 7 ]. This situation highlights the need for policies that will promote equitable distribution of pharmacists among different career domains to meet community needs. Choosing a career domain within the pharmacy profession is not a straightforward process. It is influenced by internal faculty-related factors, personal/family-related factors, and career domain-related factors [ 8 ]. Although the role of the pharmacy professional has expanded, it is often observed that pharmacy students do not select preferences until they have graduated. Increasing students’ awareness about future career planning could help to achieve goals in a successful manner.

Career planning and understanding the factors influencing career decisions are crucial to facilitate students’ improvement in the area they are interested in, and will be used in their future professional life. Globally, in the United States, the Accreditation Council for Pharmacy Education (ACPE) mentions the need for recruitment policies, as part of their document on accreditation standards [ 9 ]. In Sudan, Standards for Accreditation of Medical Schools (SAMS), which are based on World Federation for Medical Education (WFME) standards, include career guidance and planning as a quality development standard for accreditation of pharmacy schools [ 10 ]. Moreover, according to World Bank statistics, Sudan spends about 2.2% of its limited gross domestic product (GDP) on education [ 11 ].

There should be a well-thought-out link between education and career progression, particularly in pharmacy colleges, due to the high diversity of pharmacy career domains and high cost of pharmacy schools. The current situation in Sudan indicates that undergraduate students who do not determine their future career orientations before graduation are beginning to work in an unplanned way after graduation, and consequently, this results in a loss of interest, low productivity at work, or even failure if they choose a profession that is incompatible with their abilities. Thus, understanding the factors that influence undergraduate pharmacy students’ choice of a particular professional domain will help undergraduate pharmacy students develop an accurate perception of pharmacy profession domains and make information-based decisions about their career choice. This could enhance recruitment strategies, job satisfaction, and retention as well as productivity. Thus, the current study was carried out to identify job preferences and the decision-influencing factors among undergraduate pharmacy students at the University of Khartoum.

2. Materials and Methods

2.1. study design and setting.

A descriptive cross-sectional study was conducted at the Faculty of Pharmacy, University of Khartoum, Sudan. The Faculty of Pharmacy was established in 1964 and remained the only one in Sudan for about three decades. The study was conducted from March to May 2021.

2.2. Study Population

The study population was undergraduate pharmacy students. Only the third-, fourth-, and fifth-year students who were registered and undertook courses in the Bachelor of Pharmacy program during the study period were included in the study. First- and second-year students are not included in the study as in the first two years of the syllabus focus on basic medical and pharmaceutical science; thus, they have yet to establish enough awareness about pharmacy profession domains.

2.3. Sample Size and Sampling

The sample size was calculated using “Raosoft”, a sample size calculation software product, with 95% confidence intervals and a 5% margin of error with an expected response distribution of 50% [ 12 ]. Based on the data obtained from the Faculty of Pharmacy, the accessible study population was 454 students (third year: 180 students, fourth year: 95 students, and fifth year: 179 students). The minimum sample size required was 209 students (third year: 83 students, fourth year: 44 students, fifth year: 82 students). Two probability sampling methods were used to select the participants: stratified and systematic sampling. The study population was divided into three strata according to the academic year of study, and then a sample size appropriate to stratum size was obtained separately from each stratum using systematic sampling. The first unit of each stratum was randomly selected.

2.4. Data Collection

A self-administered structured questionnaire was used to collect data. The questionnaire was adapted from the previous studies undertaken using a questionnaire with confirmed reliability (pilot study) and internal consistency (Cronbach’s α > 0.7) [ 8 ], and it covered pharmacy students’ career preferences and factors influencing career choice [ 8 , 13 ]. The questionnaire consisted of three parts: the first part explored the socio-demographic characteristics of the participants; the second part contained one question and 12 options investigating the career domain preferred by students; and the third part consisted of 16 questions/items designed to access factors influencing future career domain choices. These factors were arranged into three themes: faculty-related influences (curriculum course/subject content, faculty extracurricular activities, a faculty member’s advice, and visits to a workplace); personal-related influences (family members’/relatives’ advice, a family member’s career choice, a friend’s career choice, good social status, and interaction with a practicing pharmacist); and job-related influences (opportunity for self-employment, an opportunity for part-time work, an opportunity for promotion and advancement, opportunity for health insurance, job salary and incentives, job allowances, and training in a workplace). A five-point Likert scale ranging from strongly agree to strongly disagree was used to rate the participants’ responses to the third part of the questionnaire. Two senior experts revised the questionnaire to ensure its validity. The questionnaire was also pre-tested with selected students to check the validity of the questions. Suggestions obtained from these experts and students were considered as amendments in preparing the final draft. The data from the pretest were not included in the final study.

A web-based Google form was used to create the online questionnaires that were automatically hosted via a unique uniform resource locator (URL). The URL link ensured the confidentiality of data and gave participants access from anywhere via their personal smartphone, laptop, or desktop computer. Preselected study participants were invited individually to participate through their contact information. Responses were collected from 23 March 2021 to 17 April 2021 and automatically sorted in a “Google Drive” database.

2.5. Data Analysis

The Statistical Package for Social Sciences (SPSS) version 26 software (IBM Corporation, Armonk, NY, USA) was used to analyze the data. The chi-square test was used to examine significant difference or association between independent socio-demographic variables (gender, year of study) and dependent variables. Data with a p -value of 0.05 or less were considered statistically significant.

3.1. Demographic Characteristics of the Respondents

Out of 220 pharmacy students enrolled in the study, 189 (85.9%) were female. The average age of respondents was 21.7 ± 1.5 years, with a range of 19 to 29 years. About 38.6% of respondents were in the fifth year, 23.2% were in the fourth year, and 38.2% were in the third year of study.

Studying pharmacy was the first preferred choice for 161 (73.2%) of respondents at the time of application to universities, with insignificant associations between pharmacy as a first-preferred program, gender, and study year ( Table 1 ).

Participants’ choice of pharmacy as the first-preferred program in association with their demographic characteristics.

3.2. The First-Choice Career Domain of Participants

Clinical pharmacy was selected as the most-preferred career domain after graduation (n: 64; 29.9%), followed by academia and research (n: 26; 11.8%), the pharmaceutical industry (n: 24; 10.9%), community pharmacy (n: 23; 10.5%), and public health (n: 14: 6.4%). Drug quality control, medical representatives, and drug regulatory bodies were marked as the least-preferred career domains by 10 (4.5%), 7 (3.2), and 1 (0.5%) of the respondents, respectively. Importantly, about 20% of participants preferred to move abroad for work. Moreover, data analysis revealed a significant association between gender and preferred career domain ( p -value: 0.015) ( Table 2 ).

Association between preferred career domain and demographic characteristics.

* Aca & Res.: Academia and research, Clin. ph.: Clinical pharmacy, Com. ph.: Community pharmacy, Drug Q.C., Drug quality control, Drug reg.: drug regulatory bodies, Med. rep.: Medical representatives, Pha. ind.: Pharmaceutical industry, Pub. Hea.: Public health, W. out.: Working outside Sudan, No. w.: Not working. ** Significant difference between the compared groups at p -value < 0.05.

3.3. Factors Influencing Future Career Choice

Factors influencing future career domains were broadly arranged into three categories: faculty-related factors, personal/family-related factors, and job-related factors. Out of five faculty-related factors, 178 (80.9%) of respondents strongly agreed or agreed that training in a workplace (pharmacy, industry, etc.) influenced career domain choice. Regarding personal/family-related factors, 158 (71.8%) and 140 (63.6%) of respondents strongly agreed or agreed that interaction with practicing pharmacists and good social status influenced career domain choice, respectively. On the other hand, 171 (77.7%) and 162 (63.6%) of the respondents either strongly agreed or agreed that job salary and job allowances, respectively, influenced career domain choice. Furthermore, chi-square analysis revealed that gender was insignificantly associated with influencing future career domain choice decisions ( Table 3 ). Significant associations, with p -values of 0.024 and 0.017, were found between the influence of a family member’s career choice or interaction with practicing pharmacists, respectively, and the year of study ( Table 4 ).

Association between gender and different factors influencing career choice.

Association between the year of study and different factors influencing career choice.

* Significant difference between the compared groups at p -value < 0.05.

4. Discussion

Exploring students’ preferences toward different future career domains and their motivational variables is essential to designing and implementing future career orientation programs. To our knowledge, this is the first study that attempted to assess preferred career domains and factors influencing career domain choice decisions in Sudan. Results of this study highlighted the high female-to-male ratio (86%:14%). This finding is similar to those in many studies conducted among pharmacy students in Jordan [ 8 , 14 ]. Saudi Arabia [ 15 ], and Malaysia [ 16 , 17 ]. Since admission to the faculty is based on students’ academic achievement via the Sudanese secondary school certificate, and over 50% of admitted students are female, the high female-to-male ratio could be attributed to the fact that top-ranked female students prefer health sciences. Moreover, female students demonstrate higher academic achievement on Sudanese secondary school examinations than male students [ 18 ].

Nearly three-quarters of respondents indicated that studying pharmacy was their first-preferred choice. This result is similar to those concluded in studies conducted in South Africa [ 13 ] and the United Kingdom [ 19 ]. However, the current study finding is much higher than reported in studies conducted in Sierra Leone, where one-quarter of the respondents chose pharmacy as the first study field [ 20 ]. Furthermore, it is higher than the findings of a survey in Saudi Arabia, where about 40% of respondents selected the study of pharmacy as the first choice [ 21 ]. It is expected that students who attain high academic achievement in secondary school studies largely choose to study medicine as their first choice, with pharmacy or another health-related program as a second choice [ 13 , 22 ].

Regarding students’ future career domain of practice preference, our study showed that working as a clinical pharmacist was the most desired career domain (29.9%). The strong desire of respondents for practicing clinical pharmacy could be attributed to the ambition of students to keep pace with recent advancements in the pharmacy profession. In addition, the availability of work opportunities with good salaries, particularly abroad, may positively influence participants to prefer this field. In 2008, the American College of Clinical Pharmacy (ACCP) developed the core competencies of the clinical pharmacist. The proposed core competencies were, in brief: optimization of medication therapy, promotion of health, wellness, and disease prevention [ 23 ]. Fortunately, the B. Pharm curriculum was changed in 2016 from a traditional focus on pharmaceutical science courses to a modern curriculum that integrates more pharmacy practice and clinical pharmacy courses. Moreover, a clinical pharmacy training unit was established at Soba University Hospital [ 24 ]. Reform of the curriculum will help to produce future pharmacists with competency in providing patient care in collaboration with physicians and other health care providers. Currently, the level of clinical pharmacy services provided is low, and collaborative measures and support from health care professionals are needed to overcome the challenges and improve clinical pharmacy practice in Sudan.

The second most preferred career domain was academia and research (11.8%), which differs from the results of Ethiopian [ 25 ] and South African [ 13 ] studies, where academia and research attracted 16% and 9.2% of respondents, respectively. Our findings, on the other hand, partially agree with those of studies conducted in Jordan [ 14 ], Saudi Arabia [ 15 ], and Australia [ 26 ], where academia and research are the most popular career paths. The main motivators toward academia and research include favorable opportunities for professional development, the chance to shape the future of pharmacy, the autonomy of the positions, and the flexible working environment. In addition, student participation in teaching and research via student-centered active learning may further attract students to this field [ 27 ].

The third-preference future career options for respondents were the pharmaceutical industry (10.9%) and community pharmacy (10.5%). This study’s findings are in parallel with the findings of a study conducted among Malaysian pharmacy students [ 16 ], but not in line with the findings of two studies conducted in Saudi Arabia, where they reported the pharmaceutical industry and community pharmacy as the least preferred career domains [ 15 , 28 ], or the findings of a study among Iraqi pharmacy students, where community pharmacy was ranked as the first-choice future career option [ 29 ]. This finding is significant because it contradicts the current distribution of the pharmacist workforce in these domains; according to literature, approximately 67% of pharmacists work in private community pharmacies, while less than 2% are employed in the pharmaceutical industry sector [ 30 , 31 ]. Relatively low preferences for community pharmacies could indirectly impact the reported low levels of job satisfaction among community pharmacists [ 7 , 32 ]. Since private pharmacies are the most available workplace for pharmacy graduates, efforts should be directed to design and apply policies to improve community pharmacy job satisfaction and performance.

The study revealed that medical sales representative was an undesirable career domain, as it was chosen by only 3.2% of respondents. This finding contradicts the studies conducted in Jordan and Iraq [ 14 , 29 ], in which participants ranked medical representatives among the top-three preferred future career domains. Globally, most pharmaceutical companies allocate a relatively high budget for employing and training medical representatives; pharmaceutical product promotion and marketing expenditure is higher than research and development expenditure [ 33 ]. The negative attitude toward medical sales representatives could be an indirect consequence of the prolonged drug shortage in Sudan since the COVID-19 pandemic lockdown measures, further aggravated by local currency inflation [ 34 ], with the lockdown and economic instability making it challenging for many pharmaceutical companies to thrive.

The study also indicates that drug regulatory bodies were undesirable career domains, as they were chosen by only 0.5% of respondents. This finding was consistent with studies conducted in Malaysia [ 18 ], and Jordan [ 8 , 22 ], all of which found the drug regulatory affairs domain to be one of the least-preferred options. A drug regulatory body is a relatively new profession that governments have established to control the safety and efficacy of pharmaceutical products and medical devices [ 35 ]. The low preference of participants for some future career domains, such as drug regulatory bodies, may be due to a lack of sufficient knowledge and awareness about these career domains. The regular revision of the curriculum, providing career ordination, and workplace training programs are crucial to make students aware of various pharmacy profession opportunities, and the importance of their role in different career domains.

As reported in other medical professions in Sudan, approximately 22% of participants wish to migrate, and these findings are not surprising, as reported in other medical professions in Sudan [ 35 , 36 ]. A global report pointed to a shortage of pharmacy professionals in Africa, particularly in low-income developing countries [ 37 ]. The massive brain-drain of health professions has a negative impact on services in the country. Therefore, efforts should be focused on managing migration [ 36 ].

Gender may affect the selection of the response to the most preferred career options. Sudan, as with other Arab communities, is a conservative society in which females prefer to work in a place with flexibility and fewer working hours. In the current study, a relatively large percentage of females preferred to work in academia and research (22.7%) and community pharmacy (11.6%), while the males’ preference for these domains was 6.5% and 3.2%, respectively. On the other hand, a high proportion of males showed a preference to working as medical sales representatives (13%), compared to females (1.6%). This finding agrees with reports from Jordan [ 8 ], and Saudi Arabia [ 38 ], where the influence of gender on future career choice was observed and attributed to cultural and social reasons [ 38 ]. Fieldwork, outstation trips, night shifts, and weekend hours that may be required to complete tasks, make the medical representative position more appealing to men [ 8 ].

When investigating the motivational factors behind the students’ choice of a particular pharmacy career domain, data analysis revealed that the key faculty-related factor was training in a workplace (around 51% strongly agree, 30% agree), followed by a curriculum/course at college (around 70% agree), which is consistent with a study conducted in Saudi Arabia reporting that previous training in a hospital and in community pharmacy had a significant impact on student future career choice [ 28 ]. This finding draws attention to the importance of workplace-based learning/training for students. Workplace training allows the student to apply their knowledge and gain social, cultural, and professional values; this implicit sort of workplace-based learning is known as the hidden curriculum, and has been identified as a significant issue in health professional education [ 39 ].

Personal/family-related influences and interaction with practicing pharmacists were ranked as the top factors by 72% (30% strongly agree, 42% agree), while a family member’s career choice and a friend’s career choice were ranked as the minor motivational factors (only 7.5% and 26% of participants respectively either agree or strongly agree). This finding contrasts with a study conducted in the United Arab Emirates, which reported the minimal influence of pharmacists as role models on students’ career selection [ 40 ]. In agreement with our findings, a study conducted in Saudi Arabia reported the influence of friends and family as minor motivational factors, at 16.5% and 18.5%, respectively [ 15 ]. Importantly, the association between the influence of training in a workplace and the year of study was statistically significant ( p -value 0.01).

The job salary and incentives (78%), followed by the opportunity for promotion and advancement (75%), were the most important job-related factors influencing future career domain choice. This finding is consistent with studies from Saudi Arabia [ 15 , 28 , 41 ]. In contrast, a similar study in the United States concluded that the job environment was the most important factor influencing career decisions [ 42 ]. There was no significant association between socio-demographic characteristics and job-related factors ( p -value > 0.005)

5. Limitations

There were some limitations to this study. It was conducted in one university; thus, it cannot be generalized to pharmacy students in other universities. It was also a cross-sectional study and administered to the students at one point in time. However, students’ choices may change with exposure to experiences; repeating the survey as students progress may enable evaluation of the consistency of students’ career choices and motivational factors. Additionally, the option ‘working outside Sudan’ was written under pharmacy career domains, not in a separate section.

Despite these limitations, our study is novel as it is the first report that assessed the views of pharmacy students towards preferred career domains in Sudan. The findings of the study will inform and guide university authorities, Sudanese pharmaceutical societies, and other stakeholders about the factors that affect students in choosing a pharmacy career domain. It is recommended that the gap between the implemented curriculum and employment skills should be narrowed through auditing and regular updates of the curriculum. In addition, establishing training programs in collaboration with governmental and private bodies can further increase students’ awareness about career domains. Moreover, organizing activities, such as career days, symposiums, and workshops, for various areas of pharmacy professions, particularly for arising career domains, will enable students to identify and achieve their future career goals.

6. Conclusions

The present study highlighted a baseline understanding of the career preference and main factors influencing future career domain choice among undergraduate pharmacy students at the University of Khartoum. The study showed a positive attitude in most students towards pharmacy when applying to the program. Clinical pharmacy, academia and research, the pharmaceutical industry, and community pharmacy were the most preferred choices of students. The main factors that influenced career preference were training in a workplace, curriculum content, interaction with practicing pharmacists, job salary and incentives, and the opportunity for promotion and advancement.

Author Contributions

A.H.A.: conceptualization, data curation, data analysis, writing the original draft; Y.A.M.E.: supervision, conceptualization, resources, software, reviewing, and editing; F.S.E.: conceptualization, data curation, data analysis; B.A.Y.: supervision, conceptualization, investigation, data analysis, reviewing, and editing. All authors have read and agreed to the published version of the manuscript.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Institutional Review Board Statement

The study was conducted in agreement with the recommendations of the Declaration of Helsinki, and approved by the Ethics Committee of the Sudan Medical Specializations Board (SMSB), Khartoum, Sudan (MHPE-B2, 15 March 2021).

Informed Consent Statement

Written, informed consent was obtained from all subjects involved in the study separately and voluntarily after clearly explaining the purpose of the study, and the confidentiality of the data was maintained.

Data Availability Statement

Conflicts of interest.

The authors declare no relevant conflicts of interest or financial relationships.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

• Open access
• Published: 01 December 2020

Exploring the factors that influence the career decision of STEM students at a university in South Africa

• Ethel Ndidiamaka Abe   ORCID: orcid.org/0000-0003-1670-6801 1 &
• Vitallis Chikoko   ORCID: orcid.org/0000-0001-6135-6172 1  

International Journal of STEM Education volume  7 , Article number:  60 ( 2020 ) Cite this article

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Science, Technology, Engineering, and Mathematics (STEM) educators and stakeholders in South Africa are interested in the ways STEM students make their career decisions because of the shortages in these critical skills. Although various factors including family, teachers, peers, and career interest have been reported as determinants of career decision-making, there is a scarcity of studies that have qualitatively explored the levels of influences of any of these factors in the South African context. The main aim of this study was to investigate the factors that influence career decision-making among STEM student majors in a South African university. By better understanding students’ viewpoint on these factors, educators and policymakers can assist students in making career decisions that fit their experiences, personality, and expectations. Students in their 1st, 2nd, 3rd, and 4th year of study respectively, were invited to respond to a semi-structured questionnaire about the factors that were influential in their decision to pursue a career in STEM. A total of 203 texts (response rate: 63%) were qualitatively analyzed utilising a hermeneutic phenomenology approach to traditional content analysis, whereby themes develop inductively from the data.

We used a hermeneutic phenomenological method to traditional content analysis to examine the factors influencing participants’ career decision-making. Peer interrogation, modified member verification, compact description, code-recode tactics, and assessment trails were engaged to confirm quality and rigour. Three key results emerged, namely interpersonal, intrapersonal, and career outcomes expectancy. The perceptions of STEM students of their career decision-making in the South African context are more multifaceted than reported previously. The insights could inform policies to counter skills shortages in the STEM area.

Conclusions

In this exploratory study, we gave attention to describing the various ranges of students’ perceptions and experiences regarding their career decision-making. Several students reported, among other factors, that their families, personality, and expectations played influential roles in their career decision-making. Here, we discuss the meaning of interpersonal, intrapersonal, and outcome expectations with respect to career decision-making from the perspective of STEM students in a South African university.

Introduction

South Africa ranks among the top nations globally to spend a large amount of her national resources on education with respect to percentage gross domestic product (GDP) (Van der Berg & Burger, 2003 ). Practically, government and stakeholders in Science, Technology, Engineering, and Mathematics (STEM) education try to grow sustainable decisions in STEM among students through the provision of funding from the National Student Financial Aid Scheme (NSFAS) and other supportive initiatives (Manuel, 2019 ). The NSFAS funding, through a ring-fenced system, provided for learning materials, tuition, and subsistence for beneficiaries. However, a recent change in its ring-fenced policy to outright cash transfers to beneficiary accounts seems to have resulted in a notable drop in the rate of textbook purchase and decline in academic performance by students. A non-profit organisation called the Alliance for Academic Success cautions that most beneficiaries of the monetary disbursements are using the funds to address family challenges instead of their academic needs (Duma, 2019 ).

Unfortunately, South Africa was among the four lowest performing nations in STEM at the tertiary level in sub-Saharan Africa between 2011 and 2015 (Tikly et al., 2018 ), with “only 1 in 10” high school learners deciding to pursue a career in STEM at tertiary level (Planet Earth Institute, 2016 ). Furthermore, high attrition and low performance among enrolled STEM students is frequently documented (Prince, 2017 ). Therefore, additional high school and university programmes have been developed to further motivate students to choose STEM courses (Kirby & Dempster, 2018 ; Tikly et al., 2018 ). Although some of these endeavours have been helpful, career decision-making still poses challenges among students (Fogarty & McGregor-Bayne, 2008 ).

Literature review

Global literature is rich in empirical evidence about the factors influencing career decision-making, some of which are family influence, passion, capacity, self-efficacy, apparent difficulty, values, sense of belonging, gender and race (Bieri Buschor, Berweger, Keck Frei, & Kappler, 2014 ; Lent et al., 2005 ; Rainey, Dancy, Mickelson, Stearns, & Moller, 2018 ; Rainey, Dancy, Mickelson, Stearns, & Moller, 2019 ). The bulk of attention for the past two decades has been on investigating career decision-making in STEM in western countries. However, there is potential in examining how the phenomenon is experienced in the South African context.

Career decision-making comprises several domains and complex processes. Gelatt’s ( 1962 ) progressive decision-making model offers a supporting foundation for comprehending how career decisions are made. The model shows the process of decision-making as an on-going activity that changes dynamically with the acquisition of additional information. For instance, a young learner who is exposed to technological tools used by their father could learn how to use them and decide over time to choose a career in technology. Furthering the view of Gelatt ( 1962 ), Niles, Amundson, and Neault ( 2010 ) propose that adolescents are pre-emptive catalysts of the socio-cultural domain. Hence, they dynamically integrate knowledge and texts from others to ultimately develop a repository of decision-making.

Outcome expectancy is one of the major constructs that inform career decision-making. It involves the perceived outcomes of performing specific actions (i.e., “if I do this, what will happen?”). The construct assesses young people’s perceptions of several professions based on their apparent economic, shared, and self-satisfaction outcomes. In established frameworks such as the social cognitive career theory (SCCT), career outcome expectancy is positioned as a key mediator of profession and scholarly interest and skill development (Nugent et al., 2015 ). In addition, there are empirical proofs that outcome expectancy, career interest, and self-efficacy are influential in predicting intentions to pursue a career (Blotnicky, Franz-Odendaal, French, & Joy, 2018 ; Fouad & Smith, 1996 ).

Another construct, career interest, is a predictor of both career preference and outcome (Nugent et al., 2015 ). Scholars found that career interest is positively connected to decisions to enrol in a field (Hulleman, Durik, Schweigert, & Harackiewicz, 2008 ). Students who show interests in STEM early in life often decide to study STEM ultimately (OECD, 2005 ).

Furthermore, self-efficacy has been examined as a predictor of career interest using SCCT theories (Fouad & Smith, 1996 ; Lent, Brown, & Hackett, 1994 ). Personal factors and practical STEM-related behaviors influence the formation of self-efficacy, interests, and values, which impact decisions in STEM (Jacobs, Davis-Kean, Bleeker, Eccles, & Malanchuk, 2005 ; Tate et al., 2015 ). Eccles and her associates propose that educators, peers, and families are well positioned to create prospects for students to participate in several STEM-associated activities via learning experiences and special courses (Eccles, Wigfield, & Schiefele, 1997 ; Wang & Eccles, 2012 ).

Additionally, the decision to pursue a career in STEM associates with parental influence. Mzobe ( 2014 ) confirmed that in a study conducted in South Africa, the role played by family in the career decision of students was more significant than monetary influences. Furthermore, Bandura ( 1977 ) asserts that families, educators, and peers are vitally influential in the enhancement of self-efficacy beliefs. Studies have established that self-efficacy could be developed when families and educators accentuate the significance and worth of career proficiencies (Bandura, Barbaranelli, Caprara, & Pastorelli, 2001 ). The influence of family support and attitudes to STEM have been operationalized in several ways, for example, the development of SCCT to incorporate social-contextual factors (Lent, Lopez Jr, Lopez, & Sheu, 2008 ). Workman ( 2015 ) confirms that parental influence was dominant among the themes in learner decision-making processes. This claim is confirmed by several other scholars (Nugent et al., 2015 ). Jacobs, Chhin, and Bleeker ( 2006 ) report that the girl learner’s self-perceptions and proficiencies were influenced by parental gender labelling and encouraged gender-typed career choices. This could be responsible for the under participation of the female gender in STEM as reported globally (Hartung, Porfeli, & Vondracek, 2005 ; Tikly et al., 2018 ; Wang & Degol, 2017 ).

Studies have shown that educators have a strong influence on learner decision-making (Clotfelter, Ladd, & Vigdor, 2007 ; Rivkin, Hanushek, & Kain, 2005 ). Likewise, the attitudes of students’ peers, their accomplishments, and standards can wield a sharp influence on young people’s interest in choosing and deciding to study a specific course (Olitsky, Flohr, Gardner, & Billups, 2010 ). The period of growing up is a time of acquiring a personality and sense of self, and during this period peers can be very instrumental in guiding each other’s choices, behaviors, and career interests (Vedder-Weiss & Fortus, 2013 ).

The role of personality in career decision-making behavior is well researched (Holland, 1997 , 1959 ; Seibert and Kraimer, 2001 ; Sullivan & Hansen, 2004 ). Holland ( 1959 ) proposed a theory suggesting that an individual’s career interest expresses their personality. The theory suggested that personality is a combination of several factors comprising capabilities, interests, behaviors, and principles.

The overarching aim of the present study was to explore the career decision-making of STEM students in a South African university to understand the students’ perspectives about the factors that significantly influenced their decision to study STEM. This qualitative research explored the influential factors in the career decision-making of the participants. The research integrated a hermeneutic phenomenological method to traditional content analysis. Since the study is exploratory in nature, attention was given to describing the different range of students’ viewpoints and experiences. Several students reported, among other factors, that their families, personality, and expectations played influential roles in their career decision-making. Thus, this paper presents the meaning of interpersonal, intrapersonal, and outcome expectations with respect to career decision-making for STEM students in a South African university. With better insight into students’ perspectives on career decision-making, educators can better educate students about their chosen field.

Research question

The investigators explored what students perceived influenced their career decision-making within the intricate context of STEM education settings in a university in South Africa. The aim was to uncover influential factors entrenched in students’ decision-making. The investigators sought to interpret students’ career decision-making journeys and experiences. The term “career decision-making journey” is used here to describe students’ education experiences and the circumstances, individuals, and actions that impacted on their career decision-making. The major question of this study was what defining situation, event, or individual helped STEM students to make the decision to pursue a career in STEM? The question contains many entrenched and intersecting occurrences needing obvious consideration to comprehend and interpret the key phenomenon of this research.

Methodology

Conceptual approach.

Hermeneutic phenomenology proposed by Martin Heidegger (1889–1976) (Laverty, 2003 ), tries to discover the “essence” of people’s lived encounters with phenomena and the factors that influence those encounters (Bynum & Varpio, 2018 ; Creswell & Poth, 2016 ). The technique reflects other people’s encounters and considerations to explain the deeper meaning of phenomena (Bynum & Varpio, 2018 ). Through the examination of people who went through an experience, researchers acquire greater understanding of factors that influence the wider context of STEM education. This method was selected partly because the topic of this research, “exploring the factors that influence the career decision of STEM students at a university in South Africa,” was of personal interest to the researchers who had themselves experienced career decision-making challenges (Bynum & Varpio, 2018 ).

Hermeneutic analysis additionally permits investigators to explore factors that are “taken for granted” (Bynum & Varpio, 2018 ), like those reported in several prior studies (Bennett & Phillips, 2010 ; Clinite et al., 2014 ; Grayson, Newton, & Thompson, 2012 ; Klingensmith et al., 2015 ; Phillips, Peterson, Fang, Kovar-Gough, & Phillips Jr, 2019 a), that learners and residents in the medical profession are motivated by earnings and debts in their career decision-making process. By using a hermeneutic approach, investigators recognise contextual effects of participants’ encounters that ordinarily couch beneath, undetected (Bynum & Varpio, 2018 ). In line with Bennett and Phillips’ model (Bennett & Phillips, 2010 ) which accentuates that learners experience career preparation in diverse manners, this study focuses on the array of students’ lived experiences as they made their career decisions.

This qualitative research was conducted on one campus of the largest university in the province of KwaZulu-Natal. Study participants were enlisted from undergraduate students in Science, Technology, Engineering, and Mathematics (STEM) at the university investigated in 2019, and they were in their 1st, 2nd, 3rd, and 4th year of study, respectively.

Data collection and participants

Within the viewpoint supporting hermeneutic phenomenology, investigators need to create a research approach that runs directly from the research question and aims of the study. Questions in a semi-structured format (see Additional file 1 ) were designed to determine the factors that influenced STEM students’ career decision-making at the university in South Africa (see Additional file 1 ). According to the reports of Phillips, Wilbanks, Rodriguez-Salinas, and Doberneck ( 2019 b), data gathering using written texts (essays) permits many learners to participate in the research, answering in their own words. In line with Phillips et al. ( 2019 a), six semi-structured questions to uncover factors affecting STEM students’ career decision-making were crafted. Participants were expected to respond to all six questions instead of one to generate meaningful data. The questions were piloted with a group of students who were not among the participating fields for clarity. Thereafter, the questionnaire was published on the university’s website for participants to access and complete. Consent forms for each participant were also posted online.

Based on Krejcie and Morgan’s ( 1970 ) table for determining sample size, from a target population of 2000 undergraduate STEM students, a sample of 322 was selected. Out of the sample of 322 STEM students, a total of 203 (63% response rate) responded to the questionnaire. Data was collected over a six-month period. However, the purposeful sampling technique (Patton, 2002 ) was further used to select 150 responses out of the 203 total responses when saturation occurred.

Saturation happens at the point where “additional data does not lead to any new emergent themes” (Given, 2015 , p. 134). In this study, although a hermeneutic phenomenological analysis was adopted, saturation occurred more across than inside individual cases, owing to the large number of participants who participated. Scholars suggest that saturation’s importance and meaning are variously attributed by researchers contingent upon theoretical role and analytical approach used; hence, it could serve dissimilar purposes for various types of studies (Saunders et al., 2018 ). In this context, saturation in this study was interpreted as the point where the researchers found that the responses from participants seemed to be revolving around the captured themes and no more significantly new information could be derived from the remaining collected data.

This research was appraised and approved by the ethics committee of the university as a part of the postdoctoral study funded by the National Research Foundation and the Department of Science and Technology.

Data analysis

The research team included a Ph.D. student (Nneka Akwu) in Sciences, a professional data analyst (Idris Ganiyu) who also holds a Ph.D. in management studies, an education professor (Vitallis Chikoko), and a leadership expert (Isaac I. Abe) also holding a Ph.D. in leadership studies. Since this study was designed as an exploratory one, the responses were analyzed qualitatively through a hermeneutic phenomenological method to typical content analysis, with themes developing inductively from the collected data (instead of by a prearranged, concept-driven coding system) (Crabtree & Miller, 1999 ; Hsieh & Shannon, 2005 ). This method permitted themes and their descriptions to proceed from the data (Hsieh & Shannon, 2005 ), which is vital in exploratory research. Since the data source for this study was a voluminous text pool from many participants instead of in-depth interviews, the researchers could not ask follow-up queries or investigate the vital concepts further. Hence, the analysis fused several student opinions and concepts into developing themes instead of trying to broadly depict each student’s personal experiences and opinions.

Attention was given to describing the different groups of participants’ lived experiences, focusing on minority views. Regardless of the limitations associated with the static data source, a large quantity of data permits for a comprehensive exploration of participants’ viewpoints about career decision-making. The scholars primarily immersed themselves in the collected information by reading the texts repetitively to create meaning out of the entire data (Crabtree & Miller, 1999 ; Hsieh & Shannon, 2005 ). Preliminary codes were generated from repeated readings of individual texts and documented in a comprehensive codebook. Through a continuous comparative procedure, commonalities and divergences were refined and documented in the codebook.

Each participant’s submitted text was subsequently separately coded by a minimum of two members of the team, and their coding choices were assessed, and differences fixed in frequent study team meetings. Final coding was posted into QSR NVivo version 12 and the codes were then categorized into meaningful nascent themes (Miles & Huberman, 1994 ; Ys, 1985 ). All through the analytical process, the scholars reflected on the way each data point (coded reports in texts) furthered the whole (developing themes), i.e., the “hermeneutic cycle” (Bynum & Varpio, 2018 ; Creswell & Poth, 2016 ). Explanations of each coded statement were equally scrutinised carefully by reverting to source texts and appraising them totally to confirm that the individual explanation matches the context of an individual participant’s story.

The use of QSR NVivo software permitted the scholars to confirm that each code and developing theme were backed by the text. Text coding and careful examination of codes and themes were sustained until data saturation was arrived at no novel themes emerged (Miles & Huberman, 1994 ; Ys, 1985 ). The scholars concentrated principally on the subject matter of interest: the factors that influence the career decision-making of STEM students (Bynum & Varpio, 2018 , Creswell & Poth, 2016 ). Nevertheless in the procedure of examining these phenomena, factors linked to students’ career decision-making emerged. Additionally, although the participants had created a lot of texts about several factors, they were silent about peer influence, although it was mentioned in the semi-structured questionnaire. Therefore, the research team agreed not to explore this topic in the study although literature is rich with studies on its influence on students’ career decision-making (Wang & Eccles, 2012 ; Eccles et al., 1997 ; Olitsky et al., 2010 ; Vedder-Weiss & Fortus, 2013 ), acknowledging that since peer influence was directly mentioned in the primary research questionnaire, the exploration of peer influence in this study should be preliminary instead of thorough.

This study ensured that various approaches to confirm quality and rigour were applied (Anfara Jr, Brown, & Mangione, 2002 ; Crabtree & Miller, 1999 ). To confirm credibility, the sciences student brought clarity on students’ ethos as a form of peer examination at every phase of the analytical process. Her viewpoint assisted to explain nuances in student feelings, particularly when the codebooks were being refined. When the analysis was completed, developing themes were presented to a group of postgraduate STEM students and they corroborated that the themes echoed their experiences. Since these students did not participate in the study, this step was a revised type of member checking. The investigators added explicit inclusion and exclusion code standards and findings were conveyed by using deep, rich narrative to strengthen transferability. To confirm dependability, the study team applied the code-recode principle and used QSR NVivo version 12 to create an appraisal path (Anfara Jr et al., 2002 ).

Lastly, hermeneutic phenomenology demands that investigators acknowledge their previous encounters as “embedded in and essential to the analysis process” (Bynum & Varpio, 2018 ). The investigators followed reflexivity by disclosing, pondering on, and listening to their experiences and ideas. Researchers talked about their individual responses to the data all through the investigation process. The study team often scrutinised and inspected their emerging explanations of the texts as a group and urged honest discussion about conflicting or divergent interpretations. These processes were adopted to confirm the researchers’ experiences in education leadership, management, data analysis, sciences, and leadership, and to ensure other uncharted preconceptions did not influence the quality of the analytical process and findings.

Three key themes about STEM students’ career decision-making emerged from the analysis, namely interpersonal factors, intrapersonal factors, and career outcomes expectancy. Interpersonal factors are of varying types and have numerous levels of importance to different students. Intrapersonal factors resonated with many students and they reported a variety of reasons including career interest, personality, and self-efficacy as very influential in their career decision-making. Finally, students also stated that career outcomes expectancy was relevant to their career decision-making. The results are summarised in Table 1 . Below is a presentation of the key themes and sub-themes that emerged from this study.

Key theme 1: interpersonal influences

STEM students who participated in this study generally considered interpersonal influence, but in describing the family, they reported different levels of family influence on their decision-making. Some students wrote that family was of no influence at all in their decision to study STEM.

Family influence

The key finding common to all (100%) participating students in the study was family influence. The phenomenon was embedded in specific situations and in the context of decision-making. They reasoned that they made their best career decisions when around their families or in their learning environment. The students’ perceptions of their families’ influence on their decision to study STEM are summarily described as: “very influential,” “somehow influential,” “no influence,” and “family needs my support.” The responses captured under the “no-influence” subcategory was further grouped into “career prejudice” and “left alone to decide.” The use of these adjectives does not in any way carry measurable significance but explains the meaning of the content derived from participants’ responses.

Sixty-eight (45.33%) students felt that their families were very influential in their decision to pursue a career in STEM, and they stated inter alia :

“My family has a huge positive influence because in my family they’ve advised me that in the field of STEM there are a lot of good opportunities as well as life itself as we use technology in our daily basis.”

“My family encouraged me to enrol for STEM and has supported me 100% in my study choices and I personally enjoy STEM related fields, this has pushed me to achieve great academic success.”

“My family influenced me a lot, everyone in the family believes in STEM, I also think STEM is the future.”

“My family has shown me what to expect in different STEM fields. They also showed me what careers might be good for my personality.”

“My current career was greatly influenced by the fact that my late uncle used to hire me to work with him part time on his Engineering related business.”

“They have a great influence, they even told how it is going to benefit me when I am done studying and how great it is.”

However, 40 other students, representing 27% of the respondents, believed that their families were somehow influential ; however, the final decision to study STEM was made by them. These students felt that their families played supportive roles in their decision to pursue STEM careers. There were innuendos suggestive that some students made their decision without family interference or that the family suggested a course different from the learner’s choice but subsequently agreed to support the student’s decision. These participants reported as follows:

“My family has been somewhat influential in me having a career and being independent. I am very determined to change my way lifestyle, therefore am willing to work hard in my chosen field.”

“I have reached a point where my family is much caring about pursuing my chosen field, they encourage me not to give up but try to tolerate every situation comes across to fulfil my potential desires.”

“I'm the only one who have a qualification at home, I get more encouragement to study from them. I was raised by a farm worker so pursuing studies under STEM is something I grew up wishing although less support from them because they are not educated.”

Yet, a worrisome sub-theme emerged where some students felt that they were under obligation to support their family. This trend could be referred to as an inverse influence on students’ decision to study STEM. The responses of the 19 (13%) participants who submitted the comments in the sub-theme family needs my support are as follows:

“I tend to take career decisions based on how urgent my family needs support. it hasn't paid off so far, but it does have an impact on my decision making.”

“They are very happy because they know that by being under STEM may lead to many job opportunities to help.”

“My family just wants me to have a career that will guarantee a good lifestyle at the end. When you are born under privileged, you are not satisfied by life. Hence, you always believe you must be successful at what you do, even if it is a career within STEM to support the family.”

Conversely, 23 students (15.33%) were convinced that their families made no contribution to their decision to study STEM. Although it seems these participants’ families did not have had any influence on their decision, none of the participants came across as predominantly worried by the lack of family influence; it just did not appear to be a huge factor in their lives, since they reasoned that poor or lack of education for instance, contributed to their non-contributory influence. Further understanding of the intricacies of family influence in the career decision-making behavior of STEM students in this university could yield meaningful results. However, the reports deduced from the texts of participants who reported that their family had no influence over their career decision, therefore, they were left alone to decide are

“My parents are not educated, so they supported and appreciated that I wanted to continue studying after Grade 12; as to what field I chose they had no influence at all.”

“My family has no influence whatsoever on my decision to study STEM.”

“My family doesn’t contribute that much in my life, so I make all the decisions by myself.”

“My family pretty much doesn't care about what I do, as long as I'm studying.” “My family they do not care what studies I take the only thing they want is to see me happy in what I do and study.”

“My family doesn't affect that much about making decisions I only have a say to what I want to learn, and I should be the one knowing about the outcomes of my learning.”

“My family members are mostly uneducated therefore my decision will not be influenced with anything that they may want to say.”

Additionally, career prejudice emerged as one of the reasons explicating why the family had no influence on the decision-making behavior of participating students that said:

“They (family) sometimes have prejudice about my career because of my gender.”

“STEM includes my area of academic learning. I am studying Engineering. My family believes that if you choose a career in STEM, you might never finish your studies because it is difficult.”

These students believed that their families were prejudiced against their decision to follow a career in STEM.

Teacher influence

This second category of theme one (interpersonal influence) showcases the influence that teachers have on the career decision-making behavior of STEM students. The 30 (20%) participants who acknowledged the significant role of their teachers in their career decision-making reported as follows:

“Well during my high school days I taught myself but influence from my teacher made me more interested in STEM As for family they had no idea what I’m doing, all they wanted was me to be successful and that all.”

“To a good extent, choosing a science stream as advised by my teacher in high school propelled me to do science related careers which I enjoy the most.”

Key theme 2: intrapersonal influences

Mzobe ( 2014 ) agrees with Young and Collin ( 2004 ) that there is an intrapersonal level of influence on career decisions. This level depicts the interface of self in the decision-making process of the individual student. The sub-themes here include the following:

“Champion” mentality

The first category under theme two is what is titled “champion” mind set. Individuals with champion mentality often want to “save” or “change” the world. The word was merely chosen to summarily capture the content of the responses of the 45 (30%) participants in this category:

“STEM is most effective way in fast development of our country, since we need more people in STEM related field in South Africa to quickly grow our economy and have a much broad experience in our own to benefit the country and the world at large, I decided to choose a career in STEM.”

“In my family, we’ve never had an Engineer, so If complete my studies, I’ll be the first engineer in my family and surely I will make a difference and my family will be really proud.”

“Engineering seemed like a fun major and that it can lead to great things by helping people.”

“To become one of the scientists in the world and be able to improve the living of people in the world using different skills in science.”

“My family and personal traits influenced me a lot as in the world we are living in families are viewed as inferior or people who won’t do science, so I wanted to prove to the world that I can.”

Commonly participants whose responses are documented in this category desire to make a difference in their family and/or society. They strongly believe that by pursuing a career in STEM they would be changing their family’s status or helping society at large.

Career interest in STEM

This is the second category under theme two. Interestingly, 83 students (55.33%) stated that the decision to pursue a career in STEM was based on their career interest. These participants’ passion, dreams, aspirations, desire, and curiosity to study a career in STEM were highlighted in their responses. Career interest is important in the decision-making process of students and has implication for policy decisions. Participants’ statements include the following:

“My personal interest in this career influenced my decision to study STEM to a great extent.”

“I'm passionate about the field of science.”

“I've always loved science, especially biology. My parents always encouraged me to pursue a career I am passionate about.”

“Passion and curiosity for the environment attracted me to science.”

“I have always been curious and enjoyed STEM.”

“I have always loved nature and what makes it, hence i have always enjoyed biology.”

“My decision to study STEM was influenced more by my own interests and my traits than my family.”

“I've always had a passion for helping other people and a fascination for the human body and this influenced my decision to choose a degree in health sciences.”

“I am interested in evolving things, research and innovations. This encouraged me towards STEM field.”

Personality

This is the third category of factors influencing career decision-making as found in theme two. This term is used purely as a descriptive presentation of interpretations of individual student’s personality, reasoning, or aptitude deduced from their feedback. Fifty-three (35.33%) participants identified their personality as being influential in their decision-making behavior. Their comments are as follows:

“No one other than myself who has the say in my life influences and to what I decide on doing.”

“It’s certainly only personal traits that influenced my career choice and decision.”

“My inquisitive approach to life at large and my family supportive nature on supporting my journey in obtaining such information.”

“Individual traits: my (particular sort of) intelligence and manner of thinking resulted in an affinity for mathematics and physics.”

“I am a very logical thinker and naturally very curious. These traits lead me to study STEM and makes learning easier as I am interested in what I'm learning.” “I think my critical reasoning skills are the pain driver towards STEM.”

Personal development

The fourth category of factors identified in theme two is personal development. Participants’ desire to develop themselves with knowledge and skills attributed to STEM fields underpinned their decision to pursue a career in STEM. The 17 students (11.33%) that responded in this category thought that a career in STEM would challenge and develop their potentials.

“STEM is incorporated in our everyday lives, pouring a litre of milk, baking a cake to sell to make a living, providing electricity for households. It is nice to know what goes on in the smaller parts of life which become the greater ones. I love learning about all that to improve the lives of others and mine.” “To keep myself updated with new and incoming technology.”

“I like to be challenged so that’s why I choose a course in STEM which is a challenging course to bring out my potential.”

Self-efficacy

This is the fifth category of concepts under theme two. Self-efficacy is the confident belief in one’s self about one’s ability to achieve goals and it develops from earlier experiences and verbal persuasions attributable to the environment of upbringing. In this study, 38% (57) of the participants appeared to believe that they could be successful in a career in STEM. They seemed to understand what they could do as stated below:

“I believe in me. Being in harmony with my family and with myself, I've known to accept my strengths and weaknesses and through assessing those, I know I wouldn't want to study anything else. And accepting that I'm studying what I believe I was born to do, makes me appreciate more and work harder.”

“Family satisfaction makes for a motivating environment which allows me to grow and believe in myself during my studying journey.”

“My family believes in me, I believe and know that I can succeed in almost everything that I set my mind into, which is why I went to science even though it wasn't my first or even second option. I'm doing well my results are good.”

Spirituality

This is the sixth concept in the category of factors found in theme two. Participants seemed to believe that they were influenced by their spiritual life to pursue a career in STEM. Others saw morality and values as being supreme to financial benefits deriving from a successful completion of study in STEM. These 21 (14%) participants said:

“I pray about all my decisions and entrust them to Jesus.”

“Being in the STEM requires one to be in tune with their moral and spiritual values more than financial needs.”

Theme 3: career outcomes expectancy

Career outcomes expectancy expresses young people’s perception of some careers based on their apparent financial, societal, and self-satisfaction outcomes. Sub-themes that emerged here are as follows:

Financial matters

Financial matters describe the first category of factors that emerged in theme three. This study did not set out to evaluate the effect of finance on career decision-making behavior of students in STEM, but it emerged as a theme. However, 64 (43%) students appeared to perceive a career in STEM as economically very rewarding. Therefore, the expectation of better pay when studies are completed could have stimulated their decision to pursue a career in STEM. Participants’ statements are as follows:

“It’s a good career path and it’s paying well since it’s a scarce skill.”

“I chose my career according to my ability and interests and future financial stability.”

“Finance greatly affected my learning decision, especially family related issues that demanded financial contribution.”

“I wanna be happy in what I do and be glad of my finances being able to help and support my parents in every way possible for me, so I’d be happy.”

Career opportunities and prospects

These factors emerged as the second category of theme three. Forty-three students (29%) who participated in this study felt that families understood the benefits and prospects of pursuing a career in STEM. Their comments are stated below:

“My family believes Science has more opportunities, benefits and career prospects more than other fields of study.”

“STEM there are lots of job opportunities and you can get a job. Some of the jobs are similar and you can use skills from one job in the other job.”

“My family had always told me about the opportunities that sciences provided, the money and also the respect for STEM learners.”

This qualitative research provides insight and perspective into the factors that influenced the career decisions of participating STEM students in a South African university.

• Interpersonal factors

The finding in this study that the interpersonal relationships that students had formed with family, teachers, and peers are vital in relation to career decision-making is supported by Bennett and Phillips’ ( 2010 ) model, which confirmed that in making their career decisions, students consider various values and experiences that impact individual decisions differently. For instance family and teacher influences were found to have had varying degrees of influence on participants’ career decision-making in this study. This result is also supported by previous evidence that showcases family influence as a leading theme among the themes in career decision-making (Jacobs et al., 2006 ; Nugent et al., 2015 ; Workman, 2015 ).

Unlike prior studies on career development of students (Mzobe, 2014 ; Zahra & Malik, 2017 ), using a qualitative approach, this study uniquely identified a dimensional angle to family influence on the phenomenon investigated. For several participants, family was found to be very influential in their career decision-making, as commonly reported by scholars (Mzobe, 2014 ; Nugent et al., 2015 ; Workman, 2015 ). However, it was interesting to find in this study that some participants distanced themselves from the family as an influential factor on their career decision-making. Those students firmly reported that other factors such as the need to support their family took greater priority in their career decision-making. Summarily, interpersonal factors were found to be the most prominent reason cited by participants for career decision-making in this study. This implies that educators and stakeholders who have an interest in closing the STEM skills gap by understanding how students make their decision to major in STEM can take note of the levels of influence that the family has on student career decision-making, create constructive initiatives, and offer structures that foster robust interpersonal connections in a productively strategic manner.

Although participants indicated that support received from their families influenced their decision to study STEM, the present study did not classify the form of support received. Further studies could unravel this relationship.

• Intrapersonal factors

STEM students also cited champion mind set, career interest, personality, personal development, self-efficacy, spirituality, and morality, which were categorized as intrapersonal factors, to explain why they decided to pursue a study in the STEM field. This is an essential discovery to note because it agrees with the idea that interest, self-efficacy, and personality are influential in career decision-making (Tzu-Ling, 2019 ; Wu, Zhang, Zhou, & Chen, 2020 ; Yu & Jen, 2019 ), and implies that focus on individual cognitive factors in investigations on career decision-making is founded. However, champion mind set, spirituality, and morality also mentioned by participants as reasons for their career decision-making—even though cognitive factors have meaningful influence on career decision-making—is notable. This finding importantly implies that operational and cultural factors in addition to individual cognitive and interpersonal factors should be considered in future investigations of representation in STEM.

Outcome expectancy

An outcome expectancy as a construct measuring students’ perception of some careers based on their perceived financial, societal, and self-satisfaction effects (Nugent et al., 2015 ) was confirmed to be influential in STEM student career decision-making in this study. Participating students expect to gain financial stability and independence by exploiting the career opportunities and prospects they foresee in the STEM fields. For the participants who place value on financial and economic expectations, the earnings could offer them the ability to meet the financial needs of their family members. The findings also clarify the understanding of the lens through which participants view the STEM field for opportunities and prospects. This characterisation of outcome expectancy is specifically useful because it could assist career counselors in supporting the students in defining their career pursuit in STEM.

Furthermore, the findings of the present study showed that in addition to outcomes expectancy; family, teachers, self-efficacy, interest, spirituality, morality, and personality, among other factors, are influential in students’ decision to pursue a career in STEM. Several studies on career interest, career growth, self-efficacy, and career outcomes expectancy have been conducted among students in high schools and tertiary institutions. A study was conducted among university students in Spain to investigate the effect of perceived supports and hindrances to self-efficacy convictions and other social-cognitive variables associated with STEM students’ career development (Peña-Calvo, Inda-Caro, Rodríguez-Menéndez, & Fernández-García, 2016 ). While another study among Taiwanese college students investigated their career interests and career goals for majoring in STEM (Mau, Chen, & Lin, 2020 ), Baglama and Uzunboylu ( 2017 ) examined the association between career decision-making self-efficacy and career outcomes expectancy among Turkish preservice teachers. They found that career decision-making self-efficacy significantly predicts career outcome expectancy.

However, STEM students need assistance in finding information concerning the world of work, transforming from students to professionals, planning for work, and coping with pressure (Güneri, Aydın, & Skovholt, 2003 ). The transitioning process may not be easy on the students. A study conducted by Gizir ( 2005 ) among graduating university students found that they feel apprehensive about getting employed after graduation and are also uncertain about what the future holds for them. For this purpose, this study may be of value-adding benefit in describing the career counseling needs of STEM students. It could be implied then that knowing what to do post-graduation and the way to approach the world of work could make STEM undergraduates commit to their career.

A study carried out by Vertsberger and Gati ( 2016 ) discovered that adolescents facing career decision challenges and pessimistic outcomes expectancy concerning their potential careers are inclined to seek help in the process. This has a significantly important implication with regards to career counseling initiatives designed to assist students and heightens the cognisance of the value of offering support for students in their career decision-making process. Ascertaining the variables that influence career-associated opinions and behaviors of STEM students in tertiary institutions could result in the control of these variables and the learners being assisted. Because of the importance of providing career guidance and support, it could be inferred that the present study will add to the improvement of counseling interventions. In addition, numerous scholars have focused on student career decision processes elsewhere globally, it is therefore expected that the present study would offer a dissimilar cultural viewpoint to findings from Sub-Saharan Africa. Scholars from elsewhere globally, including the USA, China, Turkey, Taiwan, Spain, and other regions in Africa, would derive benefit from the results of this study.

STEM students approach their career decision-making from diverse perspectives and experiences. Likewise, they appraise the influence of interpersonal and intrapersonal factors to different levels and for a variety of reasons, and interestingly, the family emerged as a dominantly influential element among a host of others found in this study. By comprehending students’ perspectives on career decision-making, STEM educators can assist students in making decisions that reflect their values and experiences.

Limitations

A few limitations should be acknowledged. This research was undertaken at a single tertiary institution. Learners at other institutions could have dissimilar opinions on interpersonal and intrapersonal factors and career outcomes expectation. Texts generated from undergraduate STEM students offered insights into their perceptions at that period; these ideas could change as career plans develop, for instance in postgraduate years. Participants wrote their responses in the context of semi-structured questions. Their answers could have been influenced by the desire to provide generally satisfactory information. As stated above, the data gathering method—the assessment of student texts—differs from the typical hermeneutic phenomenology approach, whereby data is gathered from people using in-depth interviews (Phillips et al., 2019 a). The investigators had no chance to ask follow-up questions to make more enquiry into matters of interest as would have been done in a procedure involving interviews. Lastly, since the questionnaire did not ask participants to respond to financial issues and gender, the findings may not mirror the full range of participants’ ideas of the effects of finances and gender on career decision-making. Further investigation is required to explore these constructs further to confirm the study’s results as generalizable.

Implications

These findings involving interpersonal, intrapersonal, and career outcomes expectancy in the decision to pursue a career in STEM have important theoretical and practical implications. Firstly, this study, like several other studies, has yet again been supported using a phenomenological hermeneutic approach. However, the researchers are quick to agree that this finding is limited to the university investigated and the peculiarity of the environment, bearing in mind Holland’s ( 1959 ) position. He was of the conviction that the experience that an individual acquires in the environment of his/her upbringing creates the inclination towards specific interests or behaviors that combine with the individual’s values to shape their personality trait.

Secondly, this study invites awareness to the finding that although peer influence was prominent in extant literature as an influence on students’ career decision-making (Eccles et al., 1997 ; Olitsky et al., 2010 ; Vedder-Weiss & Fortus, 2013 ; Wang & Eccles, 2012 ), the present study found a different result—peer influence was not notable. Further studies are recommended to explicate the reason behind this finding.

Interestingly, the need to support family was an unexpected sub-theme that emerged from family influence on career decision-making in this study. The students who reported that they needed to support their families were not very pointed about the way in which they needed to support their families and why. Further study would be needed to explore this phenomenon and could be meaningful in assisting educators and policymakers in making more informed decisions on how best to serve this category of STEM students. However, individuals interested in motivating students to pursue STEM careers could consider the fact that majority of the students affirmed that their family was influential in their career decision-making, while some other students considered it financially rewarding. These, in addition to the other factors identified in this study, could be taken into consideration and integrated into future STEM outreach and initiatives. The factors influencing students’ career decision-making have implications for how institutional practices, educational caretakers, and stakeholders shape students’ support.

Availability of data and materials

University ethics approval does not include release of the raw information. Data was collected from the STEM students under the stringent condition of anonymity and cannot be shared. Please contact the corresponding author for more information.

Abbreviations

National Student Financial Aid Scheme

Social Cognitive Career Theory

Doctor of Philosophy

Technology & Software Solutions, owners of NVivo software

Science, Technology, Engineering, and Mathematics

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Acknowledgements

Funding was provided to author by a grant from the National Research Foundation of South Africa. We are thankful to the individuals who helped our team with vetting the coding structure and proof-reading the manuscript. Dr. Isaac I. Abe and Dr. Idris Ganiyu made extensive contributions to data analysis and interpretation and reviewed the paper critically. Nneka Akwu made substantial contribution to the code-recode process bringing the viewpoint of student nuance into consideration in the process of data collection and analysis.

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• Career decision-making
• Social cognitive career theory
• Career outcomes expectancy
• Career interest

Research Trends in STEM Clubs: A Content Analysis

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To identify the research trends in studies related to STEM Clubs, 56 publications that met the inclusion and extraction criteria were identified from the online databases ERIC and WoS in this study. These studies were analysed by using the descriptive content analysis research method based on the Paper Classification Form (PCF), which includes publishing years, keywords, research methods, sample levels and sizes, data collection tools, data analysis methods, durations, purposes, and findings. The findings showed that, the keywords in the studies were used under six different categories: disciplines, technological concepts, academic community, learning experiences, core elements of education, and psychosocial factors (variables). Case studies were frequently employed, with middle school students serving as the main participants in sample groups ranging from 11–15, 16–20, and 201–250. Surveys, questionnaires, and observations were the primary methods of data collection, and descriptive analysis was commonly used for data analysis. STEM Clubs had sessions ranging from 2 to 16 weeks, with each session commonly lasting 60 to 120 min. The study purposes mainly focused on four themes: the impact of participation on various aspects such as attitudes towards STEM disciplines, career paths, STEM major selection, and academic achievement; the development and implementation of a sample STEM Club program, including challenges and limitations; the examination of students' experiences, perceptions, and factors influencing their involvement and choice of STEM majors; the identification of some aspects such as attitudinal effects and non-academic skills; and the comparison of STEM experiences between in-school and out-of-school settings. The study results mainly focused on three themes: the increase in various aspects such as academic achievement, STEM major choice, engagement in STEM clubs, identity, interest in STEM, collaboration-communication skills; the design of STEM Clubs, including sample implementations, design principles, challenges, and factors affecting their success and sustainability; and the identification of factors influencing participation, motivation, and barriers. Overall, this study provides a comprehensive understanding of STEM Clubs, leading the way for more targeted and informed future research endeavours.

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Introduction

Worldwide, STEM education, which integrates the disciplines of science, technology, engineering, and math, is gaining popularity in K-12 settings due to its capacity to enhance 21st-century skills such as adaptability, problem-solving, and creative thinking (National Research Council [NRC], 2015 ). In STEM lessons, students are frequently guided by the engineering design process, which involves identifying problems or technical challenges and creating and developing solutions. Furthermore, higher achievement in STEM education has been linked to increased enrolment in post-secondary STEM fields, offering students greater opportunities to pursue careers in these domains (Merrill & Daugherty, 2010 ). However, STEM activities require dedicated time and the restructuring of integrated curricula, necessitating careful organization of lessons. Recognizing the complexity of developing 21st-century STEM proficiency, schools are not expected to tackle this challenge alone. In addition to regular STEM classes, there exists a diverse range of extended education programs, activities, and out-of-school learning environments (Baran et al., 2016 ; Kalkan & Eroglu, 2017 ; Schweingruber et al., 2014 ). In this paper, out-of-school learning environments, informal learning environments, extended education, and afterschool programs were used synonymously. It is worth noting that the literature lacks a universally accepted definition for out-of-school learning environments, leading to the use of various interchangeable terms (Donnelly et al., 2019 ). Some of these terms include informal learning environments, extended education, afterschool programs, all-day school, extracurricular activities, out-of-school time learning, extended schools, expanded learning, and leisure-time activities. These terms refer to optional programs and clubs offered by schools that exist outside of the standard academic curriculum (Baran et al., 2016 ; Cooper, 2011 ; Kalkan & Eroglu, 2017 ; Schweingruber et al., 2014 ).

Out-of-school learning, in contrast to traditional in-school learning, offers greater flexibility in terms of time and space, as it is not bound by the constraints of the school schedule, national or state standards, and standardized tests (Cooper, 2011 ). Out-of-school learning experiences typically involve collaborative engagement, the use of tools, and immersion in authentic environments, while school environments often emphasize individual performance, independent thinking, symbolic representations, and the acquisition of generalized skills and knowledge (Resnick, 1987 ). They encompass everyday activities such as family discussions, pursuing hobbies, and engaging in daily conversations, as well as designed environments like museums, science centres, and afterschool programs (Civil, 2007 ; Hein, 2009 ). On the other hand, extended education refers to intentionally structured learning and development programs and activities that are not part of regular classes. These programs are typically offered before and after school, as well as at locations outside the school (Bae, 2018 ). As a result, out-of-school learning environments encompass a wide range of experiences, including social, cultural, and technical excursions around the school, field studies at museums, zoos, nature centres, aquariums, and planetariums, project-based learning, sports activities, nature training, and club activities (Civil, 2007 ; Donnelly et al., 2019 ; Hein, 2009 ). At this point, STEM clubs are a specialized type of extracurricular activity that engage students in hands-on projects, experiments, and learning experiences related to scientific, technological, engineering, and mathematical disciplines. STEM Clubs, described as flexible learning environments unconstrained by time or location, offer an effective approach to conducting STEM studies outside of school (Blanchard et al., 2017 ; Cooper, 2011 ; Dabney et al., 2012 ).

Out-of-school learning environments, extended education or afterschool programs, hold tremendous potential for enhancing student learning and providing them with a diverse and enriching educational experience (Robelen, 2011 ). Extensive research supports the notion that these alternative educational programs not only contribute to students' academic growth but also foster their social, emotional, and intellectual development (NRC, 2015 ). Studies have consistently shown that after-school programs play a vital role in boosting students' achievement levels (Casing & Casing, 2024 ; Pastchal-Temple, 2012 ; Shernoff & Vandell, 2007 ), and contributing to positive emotional development, including improved self-esteem, positive attitudes, and enhanced social behaviour (Afterschool Alliance, 2015 ; Durlak & Weissberg, 2007 ; Lauer et al., 2006 ; Little et al., 2008 ). Moreover, engaging in various activities within these programs allows students to develop meaningful connections, expand their social networks, enhance leadership skills (Lipscomb et al., 2017 ), and cultivate cooperation, effective communication, and innovative problem-solving abilities (Mahoney et al., 2007 ).

Implementing STEM activities in out-of-school learning environments not only supports students in making career choices and fostering meaningful learning and interest in science, but also facilitates deep learning experiences (Bybee, 2001 ; Dabney et al., 2012 ; Sahin et al., 2018 ). Furthermore, STEM Clubs enhance students' emotional skills, such as a sense of belonging and peer-to-peer communication, while also fostering 21st-century skills, facilitating the acquisition of current content, and promoting career awareness and interest in STEM professions (Blanchard et al., 2017 ). In summary, engaging in STEM activities through social club activities not only addresses time constraints but also complements formal education and contributes to students' overall development. Hence, STEM Clubs, which are part of extended education, can be defined as dynamic and flexible learning environments that provide an effective approach to conducting STEM studies beyond traditional classroom settings. These clubs offer flexibility in terms of time and location, with intentionally structured programs and activities that take place outside of regular classes. They provide students with unique opportunities to explore and deepen their understanding of STEM subjects through collaborative engagement, hands-on use of tools, and immersive experiences in authentic environments (Bae, 2018 ; Blanchard, et al., 2017 ; Bybee, 2001 ; Cooper, 2011 ; Dabney et al., 2012 ). STEM Clubs have gained immense popularity worldwide, providing students with invaluable opportunities to explore and cultivate their interests and knowledge in these crucial fields (Adams et al., 2014 ; Bell et al., 2009 ). According to America After 3PM, nearly 75% of afterschool program participants, around 5,740,836 children, have access to STEM learning opportunities (Afterschool Alliance, 2015 ).

STEM Clubs as after-school programs come in various forms and provide diverse tutoring and instructional opportunities. For instance, the Boys and Girls Club of America (BGCA) operates in numerous cities across the United States, annually serving 4.73 million students (Boys and Girls Club of America, 2019 ). This program offers students the chance to engage in activities like sports, art, dance, field trips, and addresses the underrepresentation of African Americans in STEM. Another example is the Science Club for Girls (SCFG), established by concerned parents in Cambridge to address gender inequity in math, science, and technology courses and careers. SCFG brings together girls from grades K–7 through free after-school or weekend clubs, science explorations during vacations, and community science fairs, with approximately 800 to 1,000 students participating each year. The primary goal of these clubs is to increase STEM literacy and self-confidence among K–12 girls from underrepresented groups in these fields. More examples can be found in the literature, such as the St. Jude STEM Club (SJSC), where students conducted a 10-week paediatric cancer research project using accurate data (Ayers et al., 2020 ), and After School Matters, based in Chicago, offers project-based learning that enhances students' soft skills and culminates in producing a final project based on their activities (Hirsch, 2011 ).

The Purpose of The Study

The literature on STEM Clubs indicates a diverse range of such clubs located worldwide, catering to different student groups, operating on varying schedules, implementing diverse activities, and employing various strategies, methodologies, experiments, and assessments (Ayers et al., 2020 ; Blanchard et al., 2017 ; Boys and Girls Club of America, 2019 ; Hirsch, 2011 ; Sahin et al., 2018 ). However, it was previously unknown which specific sample groups were most commonly studied, which analytical methods were used frequently, and which results were primarily reported, even though the overall topic of STEM Clubs has gained significant attention. Therefore, organizing and categorizing this expansive body of literature is necessary to gain deeper insights into the current state of knowledge and practices in STEM Clubs. By systematically reviewing and synthesizing the diverse range of studies on this topic, we can develop a clearer understanding of the focus areas, methodologies, and key findings that have emerged from the existing research (Fraenkel et al., 2012 ). At this point, using a content analysis method is appropriate for this purpose because this method is particularly useful for examining trends and patterns in documents (Stemler, 2000 ). Similarly, some previous research on STEM education has conducted content analyses to examine existing studies and construct holistic patterns to understand trends (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Lin et al., 2019 ; Martín-Páez et al., 2019 ; Noris et al., 2023 ). However, there is a lack of content analysis specifically focused on studies of STEM Clubs in the literature and showing the trends in this topic. Analysing research trends in STEM Clubs can help build upon existing knowledge, identify gaps, explore emerging topics, and highlight successful methodologies and strategies (Fraenkel et al., 2012 ; Noris et al., 2023 ; Stemler, 2000 ). This information can be valuable for researchers, educators, and policymakers to stay up-to-date and make informed decisions regarding curriculum design (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Lin et al., 2019 ; Martín-Páez et al., 2019 ; Noris et al., 2023 ), the development of effective STEM Club programs, resource allocation, and policy formulation (Blanchard et al., 2017 ; Cooper, 2011 ; Dabney et al., 2012 ). Therefore, the identification of research trends in STEM Clubs was the aim of this study.

To identify research trends, studies commonly analysed documents by considering the dimensions of articles such as keywords, publishing years, research designs, purposes, sample levels, sample sizes, data collection tools, data analysis methods, and findings (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Sozbilir et al., 2012 ). Using these dimensions as a framework is a useful and common approach in content analysis because this framework allows researchers to systematically examine the key aspects of existing studies and uncover patterns, relationships, and trends within the research data (Sozbilir et al., 2012 ). Hence, since the aim of this study is to identify and analyse research trends in STEM Clubs, it focused on publishing years, keywords, research designs, purposes, sample levels, sample sizes, data collection tools, data analysis methods, and findings of the studies on STEM Clubs.

As a conclusion, the main problem of this study is “What are the characteristics of the studies on STEM Clubs?”. The following sub-questions are addressed in this study:

What is the distribution of studies on STEM Clubs by year?

What are the frequently used keywords in studies on STEM Clubs?

What are the commonly employed research designs in studies on STEM Clubs?

What are the typical purposes explored in studies on STEM Clubs?

What are the commonly observed sample levels in studies on STEM Clubs?

What are the commonly observed sample sizes in studies on STEM Clubs?

What are the commonly utilized data collection tools in studies on STEM Clubs?

What are the commonly utilized data analysis methods in studies on STEM Clubs?

What are the typical durations reported in studies on STEM Clubs?

What are the commonly reported findings in studies on STEM Clubs?

In this study, the descriptive content analysis research method was employed, which allows for a systematic and objective examination of the content within articles, and description of the general trends and research results in a particular subject matter (Lin et al., 2014 ; Suri & Clarke, 2009 ; Sozbilir et al., 2012 ; Stemler, 2000 ). Given the aim of examining research trends in STEM Clubs, the utilization of this method was appropriate, as it provides a structured approach to identify patterns and trends (Gay et al., 2012 ). To implement the content analysis method, this study followed the three main phases proposed by Elo and Kyngäs ( 2008 ): preparation, organizing, and reporting. In the preparation phase, the unit of analysis, such as a word or theme, is selected as the starting point. So, in this study, the topic of STEM Clubs was carefully selected. During the organizing process, the researcher strives to make sense of the data and to learn "what is going on" and obtain a sense of the whole. So, in this study, during the analysis process, the content analysis framework (sample levels, sample sizes, data collection tools, research designs, etc.) was used to question the collected studies. Finally, in the reporting phase, the analyses are presented in a meaningful and coherent manner. So, the analyses were presented meaningfully with visual representations such as tables, graphs, etc. By adopting the content analysis research method and following the suggested phases, this study aimed to gain insights into research trends in STEM Clubs, identify recurring themes, and provide a comprehensive analysis of the collected data.

Search and Selection Process

The online databases ERIC and Web of Science were searched using keywords derived from a database thesaurus. These databases were chosen because of their widespread recognition and respect in the fields of education and academic research, and they offer a substantial amount of high-quality, peer-reviewed literature. The search process involved several steps. Firstly, titles, abstracts, and keywords were searched using Boolean operators for the keywords "STEM Clubs," "STEAM Clubs," "science-technology-engineering-mathematics clubs," "after school STEM program" and "extracurricular STEM activities" in the databases (criterion-1). Secondly, studies were collected beginning from November to the end of December 2023. So, the studies published until the end of December 2023 were included in the search, without a specific starting date restriction (criterion-2). Thirdly, the search was limited to scientific journal articles, book chapters, proceedings, and theses, excluding publications such as practices, letters to editors, corrections, and (guest) editorials (criterion-3). Fourthly, studies published in languages other than English were excluded, focusing exclusively on English language publications (criterion-4). Fifthly, duplicate articles found in both databases were identified and removed. Next, the author read the contents of all the studies, including those without full articles, with a particular focus on the abstract sections. After that, studies related to after school program and extracurricular activities that did not specifically involve the terms STEM or clubs were excluded, even though “extracurricular STEM activities” and “after school STEM program” were used in the search process, and there were studies related to after school program or extracurricular activities but not STEM (criterion-5). Additionally, studies conducted in formal and informal settings within STEM clubs were included, while studies conducted in settings such as museums or trips were excluded (criterion-6). Because STEM Clubs are a subset of informal STEM education settings, which also include museums and field trips, the main focus of this study is to show the trends specifically related to STEM Clubs. Moreover, studies focusing solely on technology without incorporating other STEM components were also excluded (criterion-7). Finally, 56 publications that met the inclusion and extraction criteria were identified. These publications comprised two dissertations, seven proceedings, and 47 articles from 36 different journals. By applying these criteria, the search process aimed to ensure the inclusion of relevant studies while excluding those that did not meet the specified criteria as shown in Fig.  1 .

Flowchart of article process selection

Data Analysing Process

Two different approaches were followed in the content analysis process of this study. In the first part, deductive content analysis was used, and a priori coding was conducted as the categories were established prior to the analysis. The categorization matrix was created based on the Paper Classification Form (PCF) developed by Sozbilir et al. ( 2012 ). The coding scheme devised consisted of eight classification groups for the sections of publication years, keywords, research designs, sample levels, sample sizes, data collection tools, data analysis methods, and durations, with sub-categories for each section. For example, under the research designs section, the sub-categories included qualitative and quantitative methods, case study, design-case study, comparative-case study, ethnographic study, phenomenological study, survey study, experimental study, mixed and longitudinal study, and literature review study. These sub-categories were identified prior to the analysis. Coding was then applied to the data using spreadsheets in the Excel program, based on the categorization matrix. Frequencies for the codes and categories created were calculated and presented in the findings section with tables. Line charts were used for the publication years section, while word clouds, which visually represent word frequency, were used for the keywords section. Word clouds display the most frequently used words in different sizes and colours based on their frequencies (DePaolo & Wilkinson, 2014 ). So, in this part, the analysis was certain since the studies mostly provided related information in their contents.

In the second part, open coding and the creation of categories and abstraction phases were followed for the purposes and findings sections. Firstly, the stated purposes and findings of the studies were written as text. The written text was then carefully reviewed, and any necessary terms were written down in the margins to describe all aspects of the content. Following this open coding, the lists of categories were grouped under higher order headings, taking into consideration their similarities or dissimilarities. Each category was named using content-characteristic words. The abstraction process was repeated to the extent that was reasonable and possible. In this coding process, two individuals independently reviewed ten studies, considering the coding scheme for the first part and conducting open coding for the second part. They then compared their notes and resolved any differences that emerged during their initial checklists. Inter-rater reliability was calculated as 0.84 using Cohen's kappa analysis. Once coding reliability was ensured, the remaining articles were independently coded by the author. After completing the coding process, consensus was reached through discussions regarding any disagreements among the researchers regarding the codes, as well as the codes and categories constructed for the purpose and findings sections. At this point, there were mostly agreements in the coding process since the studies had already clearly stated their key characteristics, such as research design, sample size, sample level, and data collection tools. Additionally, when coding the studies' stated purposes and results, the researchers closely referred to the original sentences in the studies, which led to a high level of consistency in the coded content between the two raters.

Studies related to the STEM Clubs were initially conducted in 2009 (Fig.  2 ). The noticeable increase in the number of studies conducted each year is remarkable. It can be seen that the majority of the 47 articles that were examined (56 articles) were published after 2015, despite a decrease in the year 2018. Additionally, it was observed that the articles were most frequently published (8) in the years 2019 and 2022, least frequently (1) in the years 2009, 2010, and 2014, and there were no publications in 2012.

Number of articles by years

Word clouds were utilized to present the most frequently used keywords in the articles, as shown in Fig.  3 . However, due to the lack of reported keywords in the ERIC database, only 30 articles were included for these analyses. The keywords that exist in these studies were represented in a word cloud in Fig.  3 . The most frequently appearing keywords, such as "STEM," "education" and "learning" were identified. Additionally, by using a content analysis method, these keywords were categorized into six different groups: disciplines, technological concepts, academic community, learning experiences, core elements of education, and psychosocial factors (variables) in Table  1 .

Word cloud of the keywords used in articles

The purposes of the identified studies identified were classified into six main themes: “effects of participation in STEM Clubs on” (25), “evolution of a sample program for STEM Clubs and its implementation” (25), “examination of” (11), “identification of” (3), “comparison of in-school and out-school STEM experiences” (2) and “others” (6). Table 2 presents the distribution of the articles’ purposes based on the classification regarding these themes. Therefore, it can be seen that purposes of “effects of participation in STEM Clubs on,” and “evolution of a sample program for STEM Clubs and its implementation” were given the highest and equal consideration, while the purposes related to "identification of" (3) and "comparison of in-school and out-of-school STEM experiences" (2) were given the least consideration among them.

Within the theme of "effects of participation in STEM Clubs on" there are 11 categories. The aims of the studies in this section are to examine the effect of participation in STEM Clubs on various aspects such as attitudes towards STEM disciplines or career paths, STEM major choice/career aspiration, achievement in math, science, STEM disciplines, or content knowledge, perception of scientists, strategies used, value of clubs, STEM career paths, enjoyment of physics, use of complex and scientific language, interest in STEM, creativity, critical thinking about STEM texts, images of mathematics, or climate-change beliefs/literacy. It is evident that the majority of research in this section focuses on the effects of participation in STEM Clubs on STEM major choice/career aspiration (5), achievement (4), perception of something (4), and interest in STEM (3).

Within the theme of "evolution of a sample program for STEM Clubs and its implementation" there are three categories: development of program/curriculum/activity (14), identification of program's challenges and limitations (3), and implementation of program/activity (8). The studies in this section aim to develop a sample program for STEM Clubs and describe its implementation. It can be seen that the most preferred purpose among them is the development of program/curriculum/activity (14), while the least preferred purpose is the identification of program's challenges and limitations (3). In addition, studies that focus on the development of the program, curriculum, or activity were classified under the "general" category (10). Sub-categories were created for studies specifically expressing the development of the program with a focus on a particular area, such as the maker movement or Arduino-assisted robotics and coding. Similarly, studies that explicitly mentioned the development of the program based on presented ideas and experiences formed another sub-category. Furthermore, the category related to the implementation of program/activity was divided into eight sub-categories, each indicating the specific centre of implementation, such as problem-based learning-centred and representation of blacks-centred.

The theme of "examination of" refers to studies that aim to examine certain aspects, such as the experiences and perceptions of students (7) and the factors influencing specific subjects (4). Studies focusing on examining the experiences and perceptions of students were labelled as "general" (4), while studies exploring their experiences and perceptions regarding specific content, such as influences and challenges to participation in STEM clubs (2) and assessment (1), were labelled accordingly. Additionally, studies that focused on examining factors affecting the choice of STEM majors (2), participation in STEM clubs (1), and motivation to develop interest in STEM (1) were categorized in line with their respective focuses. As shown in Table  2 , it is evident that studies focusing on examining the experiences and perceptions of students (7) were more frequently conducted compared to studies focusing on examining the factors affecting specific subjects (4).

The theme of "identification of" refers to studies that aim to identify certain aspects, such as the types of attitudinal effects (1), types of changes in affect toward engineering (1), and non-academic skills (1). Additionally, the theme of "comparison of in-school and out-of-school STEM experiences" (2) refers to studies that aim to compare STEM experiences within school and outside of school. Lastly, studies that did not fit into the aforementioned categories were included in the "others" theme (6) as no clear connection could be identified among them.

Research Designs

The research designs employed in the examined articles were identified as follows: qualitative methods (36), including case study (20), design-case study (6), comparative-case study (4), ethnographic study (2), phenomenological study (2), and survey study (2); quantitative methods (7), including survey study (4) and experimental study (3); mixed methods and longitudinal studies (10); and literature review (3), as illustrated in Table  3 . It can be observed that among these methods, case study was the most commonly utilized. Furthermore, it is evident that quantitative methods (7) and literature reviews (3) were employed less frequently compared to qualitative (36) and mixed methods (10). Additionally, survey studies were utilized in both quantitative and qualitative studies.

Sample Levels

The frequencies and percentages of sample levels in the examined articles are presented in Table  4 . The studies involved participants at different educational levels, including elementary school (8), middle school (23), high school (14), pre-service teachers or undergraduate students (6), teachers (4), parents (3), and others (1). It is apparent that middle school students (23) were the most commonly utilized sample among them, while high school students (14) were more frequently chosen compared to elementary school students (8). It should be noted that while grade levels were specified for both elementary and middle school students, separate grade levels were not identified for high school students in these studies. Additionally, studies that involved mixed groups were labelled as 3-5th and 6-8th grades. However, when the mixed groups included participants from different educational levels such as elementary, middle, or high school, teachers, parents, etc., they were counted as separate levels. Furthermore, the studies conducted with participants such as pre-service teachers, undergraduates, teachers, and parents were less frequently employed compared to K-12 students.

Sample Sizes

The frequencies of sample sizes in the examined articles are presented in Table  5 . It was observed that in 15 studies, the number of sample sizes was not provided. The intervals for the sample size were not equally separated; instead, they were arranged with intervals of 5, 10, 50, and 100. This choice was made to allow for a more detailed analysis of smaller samples, as smaller intervals can provide a more granular examination of data instead of cumulative amounts. The analysis reveals that the studies primarily prioritized sample groups with 11–15 (f:8) participants, followed by groups of 16–20 (f:4) and 201–250 (f:4). Additionally, it is evident that sample sizes of 6–10, 21–25, 41–50, 50–100, and more than 2000 (f:1) were the least commonly studied.

Data Collection Tools

The frequencies and percentages of data collection tools in the examined articles are presented in Table  6 . The analysis reveals that the studies primarily employed survey or questionnaires (31.6%) and observations (30.5%) as data collection methods, followed by interviews (15.8%), documents (13.7%), tests (4.2%), and field notes (4.2%). Regarding survey/questionnaires, Likert-type scales (f:23) were more commonly employed compared to open-ended questions (f:7). Tests were predominantly used as achievement tests (f:2) and assessments (f:2), representing the least preferred data collection tools. Furthermore, the table illustrates that multiple data collection tools were frequently employed, as the total number of tools (95) is nearly twice the number of studies (56).

Data Analysing Methods

The frequencies and percentages of data analysing methods in the examined articles are presented in Table  7 . The table reveals that the studies predominantly employed descriptive analysis (f:33, 41.25%), followed by inferential statistics (f:16, 20%), descriptive statistics (f:15, 18.75%), content analysis (f:14, 17.5%), and the constant-comparative method (f:2, 2.5%). It is notable that qualitative methods (f:49, 61.25%) were preferred more frequently than quantitative methods (f:31, 38.75%) in the examined studies related to STEM Clubs. Within the qualitative methods, descriptive analysis (f:33) was utilized nearly twice as often as content analysis (f:14), while within the quantitative methods, descriptive statistics (f:15) and inferential statistics (f:16), including t-tests, ANOVA, regression, and other methods, were used with comparable frequency.

The durations of STEM Clubs in the examined studies are presented in Table  8 . Based on the analysis, there are more studies (f:37) that do not state the duration of STEM Clubs than studies (f:19) that do provide information on the durations. Additionally, among the studies that do state the durations, there is no common period of time for STEM Clubs, as they were implemented for varying numbers of weeks and sessions, with session durations ranging from several minutes. Therefore, it can be observed that STEM Clubs were conducted over the course of 3 semesters (academic year and summer), 5 months, 2 to 16 weeks, with session durations ranging from 60 to 120 min. Furthermore, the durations of "3 semesters," "10 weeks with 90-min sessions per week," and "unknown weeks with 60-min sessions per week" were used more than once in the studies.

The content analysis of the findings of the identified examined articles are presented by their frequencies in Table  9 . Although the studies cover a diverse range of topics, the analysis indicates that the results can be broadly classified into three themes, namely, the "development of or increase in certain aspects" (f:68), "design of STEM Clubs" (f:17), and "identification of various aspects" (f:16). Based on the analysis, the findings in the studies are associated with the development of certain aspects such as skills or the increase in specific outcomes like academic achievement. Furthermore, the studies explore the design of STEM Clubs through the description of specific cases, such as sample implementations and challenges. Additionally, the studies focus on the identification of various aspects, such as factors and perceptions.

It is evident from the findings that the studies predominantly yield results related to the development of or increase in certain aspects (f:68). Within this theme, the most commonly observed result is the development of STEM or academic achievement or STEM competency (f:11). This is followed by an increase in STEM major choice or career aspiration (f:9), an increase in engagement or participation in STEM clubs (f:5), the development of identity including STEM, science, engineering, under-representative groups (f:5), the development of interest in STEM (f:4), an increase in enjoyment (f:4), and the development of collaboration, leadership, or communication skills (f:4). Furthermore, it can be observed that there are some results, such as the development of critical thinking, perseverance and the teachers’ profession, that were yielded less frequently (f:1). The results of 16 studies were found with a frequency of 1.

Within the design of STEM Clubs, the sample implementation or design model for different purposes such as the usage of robotic program or students with disabilities (f:7), design principles or ideas for STEM clubs, activities or curriculum (f:4), challenges or factors effecting STEM Clubs success and sustainability (f:3) were presented as a result. Additionally, the comparison was made between in-school and out-of-school learning environments (f:3), highlighting the contradictions of STEM clubs and science classes, as well as the differences in STEM activities and continues-discontinues learning experiences in mathematics. Within the identification of various aspects, the most commonly gathered result was the identification of factors affecting participation or motivation to STEM clubs (f:5). This was followed by the identification of barriers to participation (f:2). The identification of other aspects, such as parents' roles and perspectives on STEM, was comparatively less frequent.

Considering the wide variety of STEM Clubs found in different regions around the world, this study aimed to investigate the current state of research on STEM Clubs. It is not surprising to observe an increase in the number of studies conducted on STEM Clubs over the years. This can be attributed to the overall growth in research on STEM education (Zhan et al., 2022 ), as STEM education often includes activities and after-school programs as integral components (Blanchard et al., 2017 ). Identifying relevant keywords and incorporating them into a search strategy is crucial for conducting a comprehensive and rigorous systematic review (Corrin et al., 2022 ). To gain a broader understanding of keyword usage in the context of STEM Clubs, a word cloud analysis was performed (McNaught & Lam, 2010 ). Additionally, based on the content analysis method, six different categories for keywords were immerged: disciplines, technological concepts, academic community, learning experiences, core elements of education, and psychosocial factors (variables). The analysis revealed that the keyword "STEM" was used most frequently in the studies examined. This may be because authors want their studies to be easily found and widely searchable by others, so they use "STEM" as a general term for their studies (Corrin et al., 2022 ). Similarly, the frequent use of keywords like "education" and "learning" from the "core elements of education" category could be attributed to authors' desire to use broad, searchable terms to make their studies more discoverable (Corrin et al., 2022 ). Additionally, it was observed that from the STEM components, only "science" and "engineering" were used as keywords, while "mathematics" and "technology" were not present. This finding aligns with claims in the literature that mathematics is often underemphasized in STEM integration (Fitzallen, 2015 ; Maass et al., 2019 ; Stohlmann, 2018 ). Although the specific term "technology" did not appear in the word cloud, technology-related keywords such as "arduino," "robots," "coding," and "innovative" were present. Furthermore, the analysis revealed that authors preferred to use keywords related to their sample populations, such as "middle (school students)," "elementary (students)," "high school students," or "teachers." Additionally, keywords describing learning experiences, such as "extracurricular," "informal," "afterschool," "out-of-school," "social," "clubs," and "practice" were commonly used. This preference may stem from the fact that STEM clubs are often part of informal learning environments, out-of-school programs, or afterschool activities, and these concepts are closely related to each other (Baran et al., 2016 ; Cooper, 2011 ; Kalkan & Eroglu, 2017 ; Schweingruber et al., 2014 ). Moreover, the analysis showed that keywords related to psychosocial factors (variables), such as "disabilities," "skills," "interest," "attainment," "enactment," "expectancy-value," "self-efficacy," "engagement," "motivation," "career," "gender," "cognitive," and "identity" were also prevalent. This suggests that the articles investigated the effects of STEM club practices on these psychosocial variables. To sum up, by using these keywords, researchers can gain valuable insights and effectively search for relevant articles related to STEM clubs, enabling them to locate appropriate resources for their research (Corrin et al., 2022 ).

The popularity of case studies as a research design, based on the analysis, can be attributed to the fact that studies on STEM Clubs were conducted in diverse learning environments, highlighting sample implementation designs (Adams et al., 2014 ; Bell et al., 2009 ; Robelen, 2011 ). At this point, case studies offer the opportunity to present practical applications and real-world examples (Hamilton & Corbett-Whittier, 2012 ), which is highly valuable in the context of STEM Clubs. Additionally, the observation that quantitative methods were not as commonly utilized as qualitative methods in studies related to STEM Clubs contrasts with the predominant reliance on quantitative methods in STEM education research (Aslam et al., 2022 ; Irwanto et al., 2022 ; Lin et al., 2019 ). This suggests a lack of quantitative studies specifically focused on STEM Clubs, indicating a need for more research in this area employing quantitative approaches. Therefore, it is important to prioritize and conduct additional quantitative studies to further enhance our understanding of STEM Clubs and their impact. In studies on STEM Club, there is a higher frequency of research involving K-12 students, particularly middle school students, parallel to some studies on literature (Aslam et al., 2022 ), compared to other groups such as pre-service teachers, undergraduate students, teachers, and parents. This can be attributed to the fact that STEM Clubs are designed for K-12 students, and middle school is a crucial period for introducing them to STEM concepts and careers. Middle school students are developmentally ready for hands-on and inquiry-based learning, commonly used in STEM education. Additionally, time constraints, especially for high school students preparing for university, may limit their involvement in extensive STEM activities. Furthermore, STEM Clubs were primarily employed with sample groups ranging from 11–15, 16–20, and 201–250 participants. The preference for 11–20 participants, rather than less than 10, may be attributed to the collaborative nature of STEM activities, which often require a larger team for effective teamwork and group dynamics (Magaji et al., 2022 ). Utilizing small groups as samples can result in the case study research design being the most frequently employed approach due to its compatibility with smaller sample sizes. On the other hand, the inclusion of larger groups (201–250) is suitable for survey studies, as this number can represent the total student population attending STEM Clubs throughout a semester with multiple sessions (Boys & Girls Club of America, 2019 ).

According to studies on STEM Clubs, surveys or questionnaires and observations were predominantly used as data collection methods. This preference can be attributed to the fact that surveys or questionnaires allow researchers to gather data on diverse aspects, including students' attitudes, perceptions, and experiences related to STEM Clubs, facilitating generalization and comparison (McLafferty, 2016 ). Furthermore, observations were frequently employed because they can offer a deeper understanding of the lived experiences and actual practices within STEM Clubs (Baker, 2006 ). Along with data collection tools, descriptive analysis was predominantly utilized in studies on STEM Clubs, with quantitative methods including descriptive statistics and inferential statistics being used to a similar extent. The preference for descriptive analysis may arise from its effectiveness in describing activities, experiences, and practices within STEM Clubs. Given the predominance of case study research in the analysed studies, it is not surprising to observe a high frequency of descriptive statistics in the findings. On the other hand, the extensive use of quantitative analysing methods can be attributed to the need for statistical analysis of surveys and questionnaires (Young, 2015 ). Consequently, future studies on STEM Clubs could benefit from considering the use of tests and field notes as additional data collection tools, along with surveys, observations and interviews. Additionally, the development of tests specifically designed to assess aspects related to STEM could provide valuable insights (Capraro & Corlu, 2013 ; Grangeat et al., 2021 ). Moreover, increasing the utilization of content analysis and constant comparative analysis methods could further enhance the depth and richness of data analysis in STEM Club research (White & Marsh, 2006 ). In the studies on STEM Clubs, the duration and scheduling of the clubs varied considerably. While there was no common period of time for STEM Clubs, they were implemented for different numbers of weeks and sessions, with session durations ranging from several minutes to 60 to 120 min. However, it was observed that STEM Clubs were predominantly conducted over the course of three semesters, including the academic year and summer, or for durations of 2 to 16 weeks. This scheduling pattern can be attributed to the fact that STEM Clubs were often implemented as after-school programs, and they were designed to align with the academic semesters and summer school periods to effectively reach students. Additionally, the number of weeks in these studies may have been arranged according to the duration of academic semesters, although some studies were conducted for less than a semester (Gutierrez, 2016 ). The most common use of multiple sessions with a time range of 60 to 120 min can be attributed to the nature of the activities involved in STEM Clubs. These activities often require more time than regular class hours, and splitting them into separate sessions allows students to effectively concentrate on their work and engage in more in-depth learning experiences (Vennix et al., 2017 ).

The purposes of the studies on STEM Clubs were mostly related to effects of participation in STEM Clubs on various aspects such as attitudes towards STEM disciplines or career paths, STEM major choice/career aspiration, achievement etc., evolution of a sample program for STEM Clubs and its implementation including the development of program/activity, identification of program's challenges and limitations, and implementation of it, followed by the examination of certain aspects such as the experiences and perceptions of students and the factors influencing specific subjects, identification of such as the types of attitudinal effects and non-academic skills, and comparison of in-school and out-school STEM experiences. Therefore, the results of the studies parallel to the purposes were mostly related to development of or increase in certain aspects such as STEM or academic achievement or STEM competency STEM major choice or career aspiration engagement or participation in STEM Clubs, identity, interest in STEM, enjoyment, collaboration, communication skills, critical thinking, the design of STEM Clubs including the sample implementation or design model for different purposes such as the usage of robotic program or students with disabilities, design principles or ideas for STEM clubs or activities, challenges or factors effecting STEM Clubs success and sustainability, and the comparison between in-school and out-of-school learning environments. Also, they are related to the identification of various aspects such as factors affecting participation or motivation to STEM clubs, barriers to participation. At this point, it is evident that these identified categories align with the findings of studies in the literature. These studies claim that after-school programs, such as STEM Clubs, have positive impacts on students' achievement levels (NRC, 2015 ; Kazu & Kurtoglu Yalcin, 2021 ; Shernoff & Vandell, 2007 ), communication, and innovative problem-solving abilities (Mahoney et al., 2007 ), leadership skills (Lipscomb et al., 2017 ), career decision-making (Bybee, 2001 ; Dabney et al., 2012 ; Sahin et al., 2018 ; Tai et al., 2006 ), creativity (Wan et al., 2023 ), 21st-century skills (Hirsch, 2011 ; Zeng et al., 2018 ), interest in STEM professions (Blanchard et al., 2017 ; Chittum et al., 2017 ; Wang et al., 2011 ), and knowledge in STEM fields (Adams et al., 2014 ; Bell et al., 2009 ). Furthermore, it can be inferred that the studies on STEM Clubs paid significant attention to the design descriptions of programs or activities (Nation et al., 2019 ). This may be because there is a need for studies that focus on designing program models for different cases (Calabrese Barton & Tan, 2018 ; Estrada et al., 2016 ). These studies can serve as examples and provide guidance for the development of STEM clubs in various settings. By creating sample models, researchers can contribute to the improvement and expansion of STEM clubs across different environments (Cakir & Guven, 2019 ; Estrada et al., 2016 ).

In conclusion, as the studies on the trends in STEM education (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Lin et al., 2019 ; Martín-Páez et al., 2019 ; Noris et al., 2023 ), the analysis of prevailing research trends specifically in STEM Clubs, which are implemented in diverse environments with varying methods and purposes, can provide a comprehensive understanding of these clubs as a whole.

It can also serve as a valuable resource for guiding future investigations in this field. By identifying common approaches and identifying gaps in methods and results, a holistic perspective on STEM Clubs can be achieved, leading to a more informed and targeted direction for future research endeavours.

Recommendations

Future research on STEM Clubs should consider the trends identified in the study and address methodological gaps. For instance, there is a lack of research in this area that employs quantitative approaches. Therefore, it is important for future studies to incorporate quantitative methods to enhance the understanding of STEM Clubs and their impact. This includes exploring underrepresented populations, investigating the long-term impacts of STEM Clubs, and examining the effectiveness of specific pedagogical approaches or interventions within these clubs. Researchers should conduct an analysis to identify common approaches used in STEM Clubs across different settings. This analysis can help uncover effective strategies, best practices, and successful models that can be replicated or adapted in various contexts. By undertaking these efforts, researchers can contribute to a more comprehensive understanding of STEM Clubs, leading to advancements in the field of STEM education.

Limitations

It is important to consider the limitations of the study when interpreting its findings. The study's findings are based on the literature selected from two databases, which may introduce biases and limitations. Additionally, the study's findings are constrained by the timeframe of the literature review, and new studies may have emerged since the cut-off date, potentially impacting the representation and generalizability of the research trends identified. Another limitation lies in the construction of categories during the coding process. The coding scheme used may not have fully captured or represented all relevant terms or concepts. Some relevant terms may have been inadequately represented or identified using different words or phrases, potentially introducing limitations to the analysis. While efforts were made to ensure validity and reliability, there is still a possibility of unintended biases or inconsistencies in the categorization process.

Data Availability

The datasets (documents, excel analysis) utilized in this article are available upon request from the corresponding author.

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Fall 2024 Semester

Undergraduate courses.

Composition courses that offer many sections (ENGL 101, 201, 277 and 379) are not listed on this schedule unless they are tailored to specific thematic content or particularly appropriate for specific programs and majors.

• 100-200 level

ENGL 151.S01: Introduction to English Studies

Tuesday and Thursday, 11 a.m.-12:15 p.m.

Sharon Smith

ENGL 151 serves as an introduction to both the English major and the discipline of English studies. In this class, you will develop the thinking, reading, writing and research practices that define both the major and the discipline. Much of the semester will be devoted to honing your literary analysis skills, and we will study and discuss texts from several different genres—poetry, short fiction, the novel, drama and film—as well as some literary criticism. As we do so, we will explore the language of the discipline, and you will learn a variety of key literary terms and concepts. In addition, you will develop your skills as both a writer and researcher within the discipline of English.

ENGL 201.ST1 Composition II: The Mind/Body Connection

In this section of English 201, students will use research and writing to learn more about problems that are important to them and articulate ways to address those problems. The course will focus specifically on issues related to the mind, the body and the relationship between them. The topics we will discuss during the course will include the correlation between social media and body image; the efficacy of sex education programs; the degree to which beliefs about race and gender influence school dress codes; and the unique mental and physical challenges faced by college students today. In this course, you will be learning about different approaches to argumentation, analyzing the arguments of others and constructing your own arguments. At the same time, you will be honing your skills as a researcher and developing your abilities as a persuasive and effective writer.

ENGL 201.S10 Composition II: Environmental Writing   

Monday/Wednesday/Friday 1-1:50 p.m.

Gwen Horsley

English 201 will help students develop the ability to think critically and analytically and to write effectively for other university courses and careers. This course will provide opportunities to develop analytical skills that will help students become critical readers and effective writers. Specifically, in this class, students will:

• Focus on the relationships between world environments, land, animals and humankind.
• Read various essays by environmental, conservational and regional authors.
• Produce student writings. 

Students will improve their writing skills by reading essays and applying techniques they witness in others’ work and those learned in class. This class is also a course in logical and creative thought. Students will write about humankind’s place in the world and our influence on the land and animals, places that hold special meaning to them or have influenced their lives and stories of their own families and their places and passions in the world. Students will practice writing in an informed and persuasive manner, in language that engages and enlivens readers by using vivid verbs and avoiding unnecessary passives, nominalizations and expletive constructions.

Students will prepare writing assignments based on readings and discussions of essays included in "Literature and the Environment " and other sources. They may use "The St. Martin’s Handbook," as well as other sources, to review grammar, punctuation, mechanics and usage as needed.

ENGL 201.13 Composition II: Writing the Environment

Tuesday and Thursday 9:30-10:45 a.m.

Paul Baggett

For generations, environmentalists have relied on the power of prose to change the minds and habits of their contemporaries. In the wake of fires, floods, storms and droughts, environmental writing has gained a new sense of urgency, with authors joining activists in their efforts to educate the public about the grim realities of climate change. But do they make a difference? Have reports of present and future disasters so saturated our airwaves that we no longer hear them? How do writers make us care about the planet amidst all the noise? In this course, students will examine the various rhetorical strategies employed by some of today’s leading environmental writers and filmmakers. And while analyzing their different arguments, students also will strengthen their own strategies of argumentation as they research and develop essays that explore a range of environmental concerns.

ENGL 201 Composition II: Food Writing

S17 Tuesday and Thursday 12:30-1:45 p.m.

S18 Tuesday and Thursday 2-3:15 p.m.

Jodi Andrews

In this composition class, students will critically analyze essays about food, food systems and environments, food cultures, the intersections of personal choice, market forces and policy and the values underneath these forces. Students will learn to better read like writers, noting authors’ purpose, audience organizational moves, sentence-level punctuation and diction. We will read a variety of essays including research-intensive arguments and personal narratives which intersect with one of our most primal needs as humans: food consumption. Students will rhetorically analyze texts, conduct advanced research, reflect on the writing process and write essays utilizing intentional rhetorical strategies. Through doing this work, students will practice the writing moves valued in every discipline: argument, evidence, concision, engaging prose and the essential research skills for the 21st century.

ENGL 221.S01 British Literature I

Michael S. Nagy

English 221 is a survey of early British literature from its inception in the Old English period with works such as "Beowulf" and the “Battle of Maldon,” through the Middle Ages and the incomparable writings of Geoffrey Chaucer and the Gawain - poet, to the Renaissance and beyond. Students will explore the historical and cultural contexts in which all assigned reading materials were written, and they will bring that information to bear on class discussion. Likely themes that this class will cover include heroism, humor, honor, religion, heresy and moral relativity. Students will write one research paper in this class and sit for two formal exams: a midterm covering everything up to that point in the semester, and a comprehensive final. Probable texts include the following:

• The Norton Anthology of English Literature: The Middle Ages. Ed. Alfred David, M. H. Abrams, and Stephen Greenblatt. 9th ed. New York: W. W. Norton & Company, 2012.
• The Norton Anthology of English Literature: The Sixteenth Century and Early Seventeenth Century. Ed. George M. Logan, Stephen Greenblatt, Barbara K Lewalski, and M. H. Abrams. 9th ed. New York: W. W. Norton & Company, 2012.
• The Norton Anthology of English Literature: The Restoration and the Eighteenth Century. Ed. George M. Logan, Stephen Greenblatt, Barbara K Lewalski, and M. H. Abrams. 9th ed. New York: W. W. Norton & Company, 2012.
• Gibaldi, Joseph. The MLA Handbook for Writers of Research Papers. 6th ed. New York: The Modern Language Association of America, 2003.
• Any Standard College Dictionary.

ENGL 240.S01 Juvenile Literature Elementary-5th Grade

Monday, Wednesday and Friday noon-12:50 p.m.

April Myrick

A survey of the history of literature written for children and adolescents, and a consideration of the various types of juvenile literature. Text selection will focus on the themes of imagination and breaking boundaries.

ENGL 240.ST1 Juvenile Literature Elementary-5th Grade

Randi Anderson

In English 240 students will develop the skills to interpret and evaluate various genres of literature for juvenile readers. This particular section will focus on various works of literature at approximately the K-5 grade level. We will read a large range of works that fall into this category, as well as information on the history, development and genre of juvenile literature.

Readings for this course include classical works such as "Hatchet," "Little Women", "The Lion, the Witch and the Wardrobe" and "Brown Girl Dreaming," as well as newer works like "Storm in the Barn," "Anne Frank’s Diary: A Graphic Adaptation," "Lumberjanes," and a variety of picture books. These readings will be paired with chapters from "Reading Children’s Literature: A Critical Introduction " to help develop understanding of various genres, themes and concepts that are both related to juvenile literature and also present in our readings.

In addition to exposing students to various genres of writing (poetry, historical fiction, non-fiction, fantasy, picture books, graphic novels, etc.) this course will also allow students to engage in a discussion of larger themes present in these works such as censorship, race and gender. Students’ understanding of these works and concepts will be developed through readings, research, discussion posts, exams and writing assignments designed to get students to practice analyzing poetry, picture books, informational books and transitional/easy readers.

ENGL 241.S01: American Literature I

Tuesday and Thursday 12:30-1:45 p.m.

This course provides a broad, historical survey of American literature from the early colonial period to the Civil War. Ranging across historical periods and literary genres—including early accounts of contact and discovery, narratives of captivity and slavery, poetry of revolution, essays on gender equality and stories of industrial exploitation—this class examines how subjects such as colonialism, nationhood, religion, slavery, westward expansion, race, gender and democracy continue to influence how Americans see themselves and their society.

Required Texts

• The Norton Anthology of American Literature: Package 1, Volumes A and B Beginnings to 1865, Ninth Edition. (ISBN 978-0-393-26454-8)

ENGL 283.S01 Introduction to Creative Writing

Steven Wingate

Students will explore the various forms of creative writing (fiction, nonfiction and poetry) not one at a time in a survey format—as if there were decisive walls of separation between then—but as intensely related genres that share much of their creative DNA. Through close reading and work on personal texts, students will address the decisions that writers in any genre must face on voice, rhetorical position, relationship to audience, etc. Students will produce and revise portfolios of original creative work developed from prompts and research. This course fulfills the same SGR #2 requirements ENGL 201; note that the course will involve a research project. Successful completion of ENGL 101 (including by test or dual credit) is a prerequisite.

ENGL 283.S02 Introduction to Creative Writing

Jodilyn Andrews

This course introduces students to the craft of writing, with readings and practice in at least two genres (including fiction, poetry and drama).

ENGL 283.ST1 Introduction to Creative Writing

Amber Jensen, M.A., M.F.A.

This course explores creative writing as a way of encountering the world, research as a component of the creative writing process, elements of craft and their rhetorical effect and drafting, workshop and revision as integral parts of writing polished literary creative work. Student writers will engage in the research practices that inform the writing of literature and in the composing strategies and writing process writers use to create literary texts. Through their reading and writing of fiction, poetry and creative nonfiction, students will learn about craft elements, find examples of those craft elements in published works and apply these elements in their own creative work, developed through weekly writing activities, small group and large group workshop and conferences with the instructor. Work will be submitted, along with a learning reflection and revision plan in each genre and will then be revised and submitted as a final portfolio at the end of the semester to demonstrate continued growth in the creation of polished literary writing.

• 300-400 level

ENGL 424.S01 Language Arts Methods grades 7-12  

Tuesday 6-8:50 p.m.

Danielle Harms

Techniques, materials and resources for teaching English language and literature to middle and secondary school students. Required of students in the English education option.

AIS/ENGL 447.S01: American Indian Literature of the Present 

Thursdays 3-6 p.m.

This course introduces students to contemporary works by authors from various Indigenous nations. Students examine these works to enhance their historical understanding of Indigenous peoples, discover the variety of literary forms used by those who identify as Indigenous writers, and consider the cultural and political significance of these varieties of expression. Topics and questions to be explored include:

• Genre: What makes Indigenous literature indigenous?
• Political and Cultural Sovereignty: Why have an emphasis on tribal specificity and calls for “literary separatism” emerged in recent decades, and what are some of the critical conversations surrounding such particularized perspectives?
• Gender and Sexuality: What are the intersecting concerns of Indigenous Studies and Women, Gender and Sexuality Studies, and how might these research fields inform one another?
• Trans-Indigeneity: What might we learn by comparing works across different Indigenous traditions, and what challenges do such comparisons present?
• Aesthetics: How do Indigenous writers understand the dynamics between tradition and creativity?
• Visual Forms: What questions or concerns do visual representations (television and film) by or about Indigenous peoples present?

Possible Texts

• Akiwenzie-Damm, Kateri and Josie Douglas (eds), Skins: Contemporary Indigenous Writing. IAD Press, 2000. (978-1864650327)
• Erdrich, Louise, The Sentence. Harper, 2021 (978-0062671127)
• Harjo, Joy, Poet Warrior: A Memoir. Norton, 2021 (978-0393248524)
• Harjo, Sterlin and Taika Waititi, Reservation Dogs (selected episodes)
• Talty, Morgan. Night of the Living Rez, 2022, Tin House (978-1953534187)
• Wall Kimmerer, Robin. Braiding Sweet Grass, Milkweed Editions (978-1571313560)
• Wilson, Diane. The Seed Keeper: A Novel. Milkweed Editions (978-1571311375)
• Critical essays by Alexie, Allen, Cohen, Cox, King, Kroeber, Ortiz, Piatote, Ross and Sexton, Smith, Taylor, Teuton, Treuer, Vizenor, and Womack.

ENGL 472.S01: Film Criticism

Tuesdays 2-4:50 p.m.

Jason McEntee

Do you have an appreciation for, and enjoy watching, movies? Do you want to study movies in a genre-oriented format (such as those we typically call the Western, the screwball comedy, the science fiction or the crime/gangster, to name a few)? Do you want to explore the different critical approaches for talking and writing about movies (such as auteur, feminist, genre or reception)?

In this class, you will examine movies through viewing and defining different genres while, at the same time, studying and utilizing different styles of film criticism. You will share your discoveries in both class discussions and short writings. The final project will be a formal written piece of film criticism based on our work throughout the semester. The course satisfies requirements and electives for all English majors and minors, including both the Film Studies and Professional Writing minors. (Note: Viewing of movies outside of class required and may require rental and/or streaming service fees.)

ENGL 476.ST1: Fiction

In this workshop-based creative writing course, students will develop original fiction based on strong attention to the fundamentals of literary storytelling: full-bodied characters, robust story lines, palpable environments and unique voices. We will pay particular attention to process awareness, to the integrity of the sentence, and to authors' commitments to their characters and the places in which their stories unfold. Some workshop experience is helpful, as student peer critique will be an important element of the class.

ENGL 479.01 Capstone: The Gothic

Wednesday 3-5:50 p.m.

With the publication of Horace Walpole’s "The Castle of Otranto " in 1764, the Gothic officially came into being. Dark tales of physical violence and psychological terror, the Gothic incorporates elements such as distressed heroes and heroines pursued by tyrannical villains; gloomy estates with dark corridors, secret passageways and mysterious chambers; haunting dreams, troubling prophecies and disturbing premonitions; abduction, imprisonment and murder; and a varied assortment of corpses, apparitions and “monsters.” In this course, we will trace the development of Gothic literature—and some film—from the eighteenth-century to the present time. As we do so, we will consider how the Gothic engages philosophical beliefs about the beautiful and sublime; shapes psychological understandings of human beings’ encounters with horror, terror, the fantastic and the uncanny; and intervenes in the social and historical contexts in which it was written. We’ll consider, for example, how the Gothic undermines ideals related to domesticity and marriage through representations of domestic abuse, toxicity and gaslighting. In addition, we’ll discuss Gothic texts that center the injustices of slavery and racism. As many Gothic texts suggest, the true horrors of human existence often have less to do with inexplicable supernatural phenomena than with the realities of the world in which we live. 

ENGL 485.S01: Undergraduate Writing Center Learning Assistants 

Flexible Scheduling

Nathan Serfling

Since their beginnings in the 1920s and 30s, writing centers have come to serve numerous functions: as hubs for writing across the curriculum initiatives, sites to develop and deliver workshops and resource centers for faculty as well as students, among other functions. But the primary function of writing centers has necessarily and rightfully remained the tutoring of student writers. This course will immerse you in that function in two parts. During the first four weeks, you will explore writing center praxis—that is, the dialogic interplay of theory and practice related to writing center work. This part of the course will orient you to writing center history, key theoretical tenets and practical aspects of writing center tutoring. Once we have developed and practiced this foundation, you will begin work in the writing center as a tutor, responsible for assisting a wide variety of student clients with numerous writing tasks. Through this work, you will learn to actively engage with student clients in the revision of a text, respond to different student needs and abilities, work with a variety of writing tasks and rhetorical situations, and develop a richer sense of writing as a complex and negotiated social process.

Graduate Courses

Engl 572.s01: film criticism, engl 576.st1 fiction.

In this workshop-based creative writing course, students will develop original fiction based on strong attention to the fundamentals of literary storytelling: full-bodied characters, robust story lines, palpable environments and unique voices. We will pay particular attention to process awareness, to the integrity of the sentence and to authors' commitments to their characters and the places in which their stories unfold. Some workshop experience is helpful, as student peer critique will be an important element of the class.

ENGL 605.S01 Seminar in Teaching Composition

Thursdays 1-3:50 p.m.

This course will provide you with a foundation in the pedagogies and theories (and their attendant histories) of writing instruction, a foundation that will prepare you to teach your own writing courses at SDSU and elsewhere. As you will discover through our course, though, writing instruction does not come with any prescribed set of “best” practices. Rather, writing pedagogies stem from and continue to evolve because of various and largely unsettled conversations about what constitutes effective writing and effective writing instruction. Part of becoming a practicing writing instructor, then, is studying these conversations to develop a sense of what “good writing” and “effective writing instruction” might mean for you in our particular program and how you might adapt that understanding to different programs and contexts.

As we read about, discuss and research writing instruction, we will address a variety of practical and theoretical topics. The practical focus will allow us to attend to topics relevant to your immediate classroom practices: designing a curriculum and various types of assignments, delivering the course content and assessing student work, among others. Our theoretical topics will begin to reveal the underpinnings of these various practical matters, including their historical, rhetorical, social and political contexts. In other words, we will investigate the praxis—the dialogic interaction of practice and theory—of writing pedagogy. As a result, this course aims to prepare you not only as a writing teacher but also as a nascent writing studies/writing pedagogy scholar.

At the end of this course, you should be able to engage effectively in the classroom practices described above and participate in academic conversations about writing pedagogy, both orally and in writing. Assessment of these outcomes will be based primarily on the various writing assignments you submit and to a smaller degree on your participation in class discussions and activities.

ENGL 726.S01: The New Woman, 1880–1900s 

Thursdays 3–5:50 p.m.

Katherine Malone

This course explores the rise of the New Woman at the end of the nineteenth century. The label New Woman referred to independent women who rebelled against social conventions. Often depicted riding bicycles, smoking cigarettes and wearing masculine clothing, these early feminists challenged gender roles and sought broader opportunities for women’s employment and self-determination. We will read provocative fiction and nonfiction by New Women writers and their critics, including authors such as Sarah Grand, Mona Caird, George Egerton, Amy Levy, Ella Hepworth Dixon, Grant Allen and George Gissing. We will analyze these exciting texts through a range of critical lenses and within the historical context of imperialism, scientific and technological innovation, the growth of the periodical press and discourse about race, class and gender. In addition to writing an argumentative seminar paper, students will complete short research assignments and lead discussion.

ENGL 792.ST1 Women in War: Female Authors and Characters in Contemporary War Lit

In this course, we will explore the voices of female authors and characters in contemporary literature of war. Drawing from various literary theories, our readings and discussion will explore the contributions of these voices to the evolving literature of war through archetypal and feminist criticism. We will read a variety of short works (both theoretical and creative) and complete works such as (selections subject to change): "Eyes Right" by Tracy Crow, "Plenty of Time When We Get Home" by Kayla Williams, "You Know When the Men are Gone" by Siobhan Fallon, "Still, Come Home" by Katie Schultz and "The Fine Art of Camouflage" by Lauren Johnson.