student attitudes and behaviors research paper

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

The PMC website is updating on October 15, 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• v.8(10); 2022 Oct

An analysis of the attitudes and behaviours of university students and perceived contextual factors in alternative assessment during the pandemic using the attitude–behaviour–context model

Siu-cheung kong.

a Department of Mathematics and Information Technology, Education University of Hong Kong, Hong Kong

Cheuk-Nam Yuen

b Centre of Learning, Teaching and Technology, Education University of Hong Kong, Hong Kong

Associated Data

Data will be made available on request.

Alternative assessment aims to increase the practicality and authenticity of assessment in university education and has been increasingly used during the pandemic. The implementation can be ineffective without considering students' needs and concerns in adapting to new assessment practices. This mixed-methods study applied an attitude–behaviour–context model to examine students' perceptions about the implementation of alternative assessment. One hundred and thirteen questionnaires were collected from students who experienced alternative assessment before the survey. Six students were interviewed about their learning experience. The quantitative results revealed that the students' perceived context of alternative assessment directly influenced their learning behaviour. The students' attitudes towards alternative assessment partially mediated the relationship between their perceived context of alternative assessment and their learning behaviour. The qualitative data were analysed using a deductive thematic approach, providing an in-depth interpretation of students' understanding and awareness of perceived teacher support and expectations about alternative assessment at the university. The semi-structured interview found that although students positively viewed the alternative assessment as an authentic task that help developing their higher-level thinking skills, the effectiveness of the assessment was weakened by the insufficient support and monotonous types of the assessment. This study's findings provide practical suggestions for teachers and universities to improve alternative assessment.

Authenticity in assessment; Formative assessment; Higher education; Mixed-methods; Teacher support.

1. Introduction

Views of assessment have changed over time in line with the desire to provide students with a better learning experience ( Berry, 2008 ). The suspension of face-to-face learning because of the coronavirus pandemic has motivated universities to rethink their assessment approach with the aim of designing creative, innovative and practical assessments for university students ( Kong et al., 2021 ). To cope with the unexpected challenges posed by the pandemic, universities worldwide have shifted away from traditional test-based assessment to alternative assessment, also known as authentic assessment ( Brown and Sambell, 2020 ). For instance, some chemistry teachers at a university in Singapore designed concept map tasks to replace examinations and tests ( Lau et al., 2020 ). Moreover, Gachon International Language Centre redesigned the assessment to adapt the sudden transition to online learning by asking students to do video presentations and self and peer assessment ( Chung and Choi, 2021 ). Teachers at a Hong Kong university also used different technology tools to facilitate the adoption of alternative assessment, like designing posters and creating e-portfolio ( Kong et al., 2021 ). These examples show that universities have been working hard to maintain the quality of assessment in the online learning environment.

Meanwhile, students' perceptions of alternative assessment are important because the effectiveness of the assessment is determined by their learning experience and outcomes ( Ajjawi et al., 2020 ). Siow (2015) showed that student's positive attitude of the self and peer assessment is constituted by the remarkable learning outcome experienced by students, such as the improved critical thinking and organization skills. Students having a favorable attitude of alternative assessment would love to see such kind of assessment in the future, encouraging university to achieve the goal of assessment for learning. However, Atifnigar et al. (2020) reported that students would have negative attitudes towards the portfolio assessment due to the extra workload. They also failed to see the relevance of the assessment to their future career. In view of this, the university reduced the content requirements in the assessment and redesigned it so that it was more relevant to the students' future career development. Students also developed a more positive attitude towards the alternative assessment after the adjustment made by the university. Therefore, students' attitudes and perceived context of alternative assessment can affect their engagement in the assessment. While previous studies mainly focus on investigating students' perception towards the alternative assessment ( Atifnigar et al., 2020 ; Siow, 2015 ; Cornelius and Kinghorn, 2014 ), little is known about how students' learning behaviours in alternative assessment is influenced by students' attitudes and perceived context of alternative assessment.

It is important to learn from the students' perspectives concerning how the alternative assessment is implemented and whether they feel comfortable towards such new and novel approach. As such, universities and academic staffs can adjust the alternative assessment according to the students' needs and expectations and thus guarantee the effectiveness of alternative assessment. The purpose of this study was to explore the perceptions and learning behaviours of students who experienced alternative assessment at a university. The attitude–behaviour–context (ABC) model was adopted to explore students' attitudes, perceived context and learning behaviours in relation to alternative assessment. A mixed-methods approach was adopted, with a quantitative study examining the statistical relationships between students' attitudes, perceived context and learning behaviours and a qualitative study offering an in-depth picture of students’ perceptions of their experiences with alternative assessment. This study aimed to answer the following research questions.

(RQ 1): What are the relationships between students' attitudes towards, perceived context of and learning behaviours in alternative assessment? (Quantitative study)

(RQ 2): How do students perceive the situation of alternative assessment regarding their understanding and awareness of alternative assessment and perceived teacher support? (Qualitative study)

(RQ 3): What do students expect from the university to improve their learning experience in alternative assessment? (Qualitative study)

This study's findings and implications provide suggestions and insights for universities to improve their alternative assessment approaches.

2. Background

2.1. alternative assessment in university education.

Educators in university settings view assessment not only as the measurement of students' learning outcomes but also as a way of engaging students in the learning process ( Brown, 2015 ). Alternative assessment emphasises practicality and authenticity. It enables students to apply their knowledge and skills in real-life scenarios ( Berry, 2008 ). According to Wiggins (1998) , alternative assessment consists of the following six elements: (1) enabling students to reflect on the knowledge and skills that are essential in a real-world setting; (2) encouraging students to think critically and innovatively to solve unstructured problems; (3) asking students to complete a task using the skills and procedures typically used in their academic discipline; (4) allowing students to apply what they have learned in a realistic context; (5) assessing students’ performance in using a wide range of higher-order competencies in complex tasks and (6) allowing students to exchange feedback with their peers and to practise so they can improve their work. Alternative assessment can be implemented in various ways, such as creating portfolios and reflective journals, designing posters, doing self and peer assessment, making video or oral role-play presentation and completing projects ( Berry, 2008 ; Cornelius and Kinghorn, 2014 ; Craft and Ainscough, 2015 ).

Alternative assessment has been found to promote university students' learning outcomes ( Sokhanvar et al., 2021 ). Applying acquired knowledge and skills in realistic circumstances promotes students' learning determination and satisfaction, and students thus participate more actively in their learning ( Ashford-Rowe et al., 2014 ; Svinicki, 2004 ). For instance, James and Casidy (2018) found that undergraduates had favourable attitudes towards alternative assessment, which was found to drive their learning satisfaction and intention to pursue business studies. Nikolova and Andersen (2017) concluded that business students' engagement in service-learning assessment was promoted when they faced real clients with needs. Alternative assessment can also enhance students' cognitive skills such as self-reflection, creativity and problem-solving ( Darling-Hammond and Snyder, 2000 ; Palmer, 2004 ). Traditional assessment tends to test memory and lower-level thinking skills, whereas alternative assessment is considered a better tool for comprehensively assessing students' performance, including their higher-level thinking skills ( Ahmad et al., 2020 ). According to Berry (2008) , students are required to monitor and reflect on their own learning progress, which is a fundamental feedback practice featured in alternative assessment. The self-reflection and feedback process allows students to examine their true self and cultivate their creativity and problem-solving skills ( Palmer, 2004 ; Wiewiora and Kowalkiewicz, 2018 ). For example, Palmer (2004) found that traditional assessments, such as examinations, tend to engender only surface learning in engineering students. Comparatively, an alternative assessment engineering assignment was more effective in developing engineering students' deep learning and creativity ( Palmer, 2004 ). However, because it is time- and resource-intensive to prepare and adopt, alternative assessment can be a challenging assessment approach ( Sokhanvar et al., 2021 ). For example, in Muthohharoh et al. (2020) , an English teacher needed to give more attention to students' progress during class as he lacked the time to implement self-assessment formally. Putri et al. (2019) asserted that teachers do not have enough time to measure all aspects of students' oral language skills via alternative assessment, and thus discouraging students' participation at speaking class. In addition, teachers often lack an awareness of alternative assessment or techniques for adopting it ( Ojung'a & Allida, 2017 ). Ojung'a and Allida (2017) observed that teachers in Kenya tended to use traditional assessment tools and seldom design and use alternative assessment tools. As a result, students' engagement in alternative assessment was low. Meanwhile, students may feel insecure about new types of assessment because they are unfamiliar with the format and measurement standards ( Fox et al., 2017 ). In Lau et al. (2020) , some chemistry students felt uneasy about replacing traditional written assignments with a concept map task because they doubted that the alternative approach would reflect their abilities. To explore the challenges related to alternative assessment, this study investigated the implementation of alternative assessment in a university. We believe that the findings will give university educators new ideas for improving their alternative assessment approach.

2.2. Theoretical framework—attitude–behaviour–context theory

Attitude–behaviour–context (ABC) theory ( Guagnano et al., 1995 ) has been frequently used in studies concerning environmental education and pro-environmental behaviour. Specifically, it has been used to explain how pro-environmental activities are promoted through the constructs of attitude and context. In ABC theory, ‘attitude’ refers to a person's beliefs, values and general assumptions about behaving in specific ways ( Stern, 2000 ). A positive attitude would mean acceptance and ongoing adoption of the promoted item by users ( Reddy et al., 2020 ). Whereas ‘context’ refers to external legal, physical, social or financial parameters ( Stern, 2000 ). As universities continue to improve the use of assessment, the context for higher education in assessment is ever-changing, ranging from summative to formative way (Pereira et al., 2016). Researchers think that one's attitude alone is insufficient to motivate behaviour change and that contextual factors can motivate or discourage actions ( Guagnano et al., 1995 ; Zepeda and Deal, 2009 ). In addition, studies have found that attitude plays a mediating role in the interaction between contextual factors and behaviour. For instance, Guagnano et al. (1995) found that Americans' recycling behaviour was significantly affected by both their ideas of responsibility (i.e., attitude) and their possession of a recycling bin (contextual factor). Importantly, the possession of a bin indirectly influenced their recycling behaviour via their ideas about responsibility. Zepeda and Deal (2009) found that organic-food shoppers perceived that a few large chain stores controlled the availability of organic food. Motivated by this negative perception of control, they preferred to shop at smaller, local markets.

ABC theory has been increasingly used to study the relationships between context, attitudes and behaviours. However, most of these studies have been conducted in the environmental protection field (e.g., Xu et al., 2017 ; Zepeda and Deal, 2009 ). Specifically, researchers have mainly applied ABC theory to understand the connection between the context of an environmental policy and the public's environmental behaviour. Similarly, we argue that ABC theory is applicable to the education field because it can help educators to understand the context of an education policy and students' learning behaviour. However, there is limited evidence of ABC theory being adopted in educational research. This study adapted ABC theory to better understand the implementation of alternative assessment. We explored how students' attitudes towards and perceived context of alternative assessment at university affected their behaviour in relation to alternative assessment. The proposed path model is shown in Figure 1 .

The proposed attitude–behaviour–context (ABC) theory model for describing university education alternative assessment.

2.3. Hypotheses

The qualitative findings of Adie et al. (2010) suggested that university students have a fixed mindset in which assessment must have a research study format. However, after building a more supportive learning environment by providing sufficient guidelines and information about the alternative assessment, the students were willing to engage in the alternative assessment approach, which took the form of a community project. Fook and Sidhu (2010) found that if students perceived that the context of alternative assessment would allow them to acquire practical real-world skills, they engaged more actively in the task and did not need close supervision from the academic/teaching staff. Thus, we expect that a positive perceived context of alternative assessment can positively influence students’ learning behaviour.

(H1): Enhancing students' perceived context of alternative assessment directly promotes their learning behaviour.

According to Gulikers (2006) , students' perceptions of alternative assessment are a function of their experiences with it and its applicability to their future profession. Student's engagement in the assessment is determined by the motivational value of the task and its manageability ( Lizzio and Wilson, 2013 ). Students' positive impressions of alternative assessment can be reinforced when it allows them to apply their knowledge in a real-world scenario ( Craft and Ainscough, 2015 ). However, as authenticity is subjective, what an educator considers authentic might not match what students consider authentic ( Ajjawi et al., 2020 ). Ojung'a and Allida (2017) found that students had a limited understanding of alternative assessment because their perceived learning environment was not informative. Therefore, the students' uncertainty negatively affected their engagement ( Lau et al., 2020 ). We expect that a positive attitude towards alternative assessment positively mediates the relationship between the students' perceived context of alternative assessment and their learning behaviour.

(H2): Enhancing students' perceived context of alternative assessment indirectly promotes their learning behaviour through the mediating role of attitude.

3. Methodology

This study used a convergent mixed methods design ( Cohen et al., 2011 ) to answer the research questions through collecting and analyzing the quantitative ( RQ1 ) and qualitative ( RQ2 and RQ3 ) data concurrently. The data collection was completed through distributing online questionnaires to and interviewing students at a local university. Students' ratings in the quantitative section were analyzed to present the relationships between students' attitudes towards, perceived context of and learning behaviours in alternative assessment with SPSS and AMOS. The qualitative method was used to understand students' perception regarding the situation of alternative assessment regarding their understanding and awareness of alternative assessment and perceived teacher support, as well as their expectation on the implementation of alternative assessment. The mixed method design offered an in-depth understanding of students’ perspectives in assessment practices.

3.1. Instrument

3.1.1. quantitative study.

We designed a survey based on the three fundamental constructs of the ABC model, namely, attitude, perceived context and behaviour. Attitude consisted of eight items. The items reflected the major characteristics of alternative assessment: practicality, versatility, flexibility, learning motivation and metacognition engagement ( Berry, 2008 ; Wiggins, 1998 ). Higher marks represented students' greater acknowledgement of the effectiveness of alternative assessment. Perceived context consisted of six items that measured students' perceived implementation of alternative assessment in terms of the variety and content of the assessments, the use of assessment tools, and support from the academic/teaching staff. Higher marks indicated that students perceived a greater intensity of implementation. Learning behaviour consisted of seven items that measured students' behaviour in terms of their activeness, contributions, learning process and outcomes. Higher marks indicated greater engagement. The complete survey is shown in Table 1 below. All of the constructs were measured using a five-point Likert scale ranging from 1 (‘strongly disagree)’ to 5 (‘strongly agree)’. George and Mallery (2003) specified that an alpha of .90 should be considered as having an excellent internal consistency. Cronbach's alpha of the survey was .91, suggesting excellent reliability.

Table 1

The survey's confirmatory factor analysis, Cronbach's alpha and mean.

3.1.2. Qualitative study

Nine interview questions ( Table 2 ) based on our research questions were developed to address the following issues: (a) students' understanding and awareness of alternative assessment; (b) students' perceived teacher support in relation to alternative assessment and (c) students’ expectations about the future implementation of alternative assessment.

Table 2

Interview questions for student interviewees.

3.2. Procedure and participants

3.2.1. quantitative study.

Online questionnaires were distributed to all students in a university via Qualtrics. This study focused on the implementation of alternative assessments in courses undertaken in 2020 and 2021 while face-to-face classes were suspended because of the coronavirus pandemic. The university's Human Research Ethics Committee approved the study, and informed consent was obtained online from those who agreed to participate in this research. Online surveys were sent to 6,050 students, and 113 responses (2%) were obtained. The low response rate was due to the short implementation period of alternative assessment, which only began in 2020. Moreover, the adoption of alternative assessment was not implemented throughout the university; thus, only a small group of students had any understanding or experience of alternative assessment. Among the respondents, 21% were men (N = 26) and 79% were women (N = 87). The demographic characteristics of the respondents are presented in Table 3 .

Table 3

Respondents’ demographic characteristics.

3.2.2. Qualitative study

Individual semi-structured interviews were conducted to collect qualitative data. Four undergraduate and two postgraduate students (two men and four women) were interviewed. The six students were anonymised with letters (students A to F). Each interview was conducted through Zoom, a videoconferencing platform that can securely record and store recordings. Each interview lasted approximately 30 min and was conducted in Cantonese and transcribed into English.

4.1. Quantitative results

4.1.1. descriptive statistics.

Table 4 shows the means, standard deviations (SD) and correlations between the ABC model constructs. The score of each item presented in this research ranged from 1 to 5, meaning from strongly disagree to strongly agree. The mean values of the three constructs fall between 3.5 and 4.0. This implies that students generally had a moderately high attitude towards the alternative assessment. The result also indicated that students experienced and engaged in alternative assessment in their courses at a moderately high level. The SD values for students' attitudes of and learning behaviour in alternative assessment are lower than 0.6, meaning that students' response in these areas differ insignificantly from the overall mean. However, the SD values for students' perceived context of alternative assessment is around 0.70, implying a relatively high variation in the participants' response. This suggests that the students' learning environment regarding the alternative assessment differed significantly. Moderately significant positive intercorrelations were observed between the constructs. The reliability coefficients of each construct are shown in brackets. George and Mallery (2003) specified that an alpha of .80 should be considered as having a good internal consistency. Cronbach's alpha for the three constructs ranged from .85 to .87, indicating good reliability.

Table 4

Descriptive statistics, correlations and reliabilities (in brackets) of the ABC model constructs

Note: N = 113; ∗p < .05; ∗∗p < .01.

4.1.2. Path analysis

AMOS version 27 tested the hypotheses regarding the relationship between students' attitude, perceived context of and behaviours in alternative assessment. According to Cohen et al. (2002) , the root mean square error of approximation (RMSEA) should be below .08. Comparative fix index (CFI) and Tucker–Lewis index (TLI) values greater than .95 indicate an excellent fit ( Hu and Bentler, 1999 ). The model showed an excellent fit to the data (χ2 = 143.34, df = 114, p < .05, χ2/df = 1.26, TLI = .96, CFI = .97; RMSEA = .05). The results revealed the following significant paths: (a) from perceived context to attitude (β = .40, p < .000), (b) from attitude to learning behaviour (β = .59, p < .000) and (c) from perceived context to learning behaviour (β = .47, p < .000). In addition, 5,000 bootstrap resamples were used to investigate the mediation effects of the model ( MacKinnon et al., 2004 ). Direct and indirect effects were found ( Table 5 ). Hypotheses 1 and 2 were thus both supported. Enhancing students' perceived context of alternative assessment directly promotes their learning behaviour in alternative assessment. Also, enhancing students’ perceived context of alternative assessment indirectly promotes their learning behaviour through the mediating role of attitude. Figure 2 shows the final model developed in this study and its significant paths.

Table 5

Summary of direct, indirect and total effects among the three model constructs.

The attitude–behaviour–context alternative assessment model.

4.2. Qualitative results

We applied our proposed ABC alternative assessment model to the qualitative data to further investigate our research questions. A deductive and theory-driven thematic analysis was conducted. This approach allowed us to align the data to the significant paths revealed by the ABC model ( Braun and Clarke, 2006 ). Moreover, it helped us pinpoint answers to our research questions. We developed the following themes: (a) the direct and indirect paths of the ABC alternative assessment model, (b) students’ understanding and awareness of alternative assessment, (c) perceived teacher support and (d) expectations of future alternative assessment implementation. After thoroughly scrutinising the transcripts, the authors completed and refined the initial coding. The coding results were discussed and reviewed by the authors until a consensus was reached for all of the codes. The findings are described in the next section according to theme. Table 6 presents the demographics of the interviewees with details of their gender, year of study, courses in which they experienced an alternative assessment and the assessment methods. Table 7 shows the themes, sub-themes and supporting comments of the qualitative analysis.

Table 6

Demographics of the interviewees.

Note: N = 6.

1. Paper art: Students designed art pieces with paper using the creativity theories they learned in class.

2. Microteaching: Students filmed themselves teaching a topic.

3. Presentation: Case studies or portfolio presentations were made in various forms, including individual, group and video formats.

4. Teaching practicum: Students were sent to local schools to teach in the classroom.

5. Case study essay: Students were asked to analyse and give suggestions about the implementation of a positive psychology intervention at a local school.

Table 7

Themes, sub-themes and supporting comments from students.

4.2.1. Views on direct and indirect paths of the ABC alternative assessment model

The interviews provided in-depth information about the significant paths identified in the ABC alternative assessment model. For example, the qualitative analysis showed that some students perceived the content of the implemented assessment to be meaningful and useful in real life, resulting in their having a positive attitude towards the assessment and increasing their active engagement. As student D stated, ‘ The teaching practicum provided me with a chance to apply what I learned, and I gained real-life experience that traditional assessment cannot offer. Since there are no standard answers, I spent a lot of time preparing and improving my performance according to my teacher's opinions.’ If students cannot relate what they learn to their life, they might perceive the context of the assessment to be meaningless, which could further weaken their motivation and involvement. As student B stated, ‘ Writing a reflective journal about my teaching styles and strengths was quite useless for me as a freshman. The knowledge I acquired in the reflection would ultimately disappear since I'm not applying it in life any time soon . I wrote the journal just like writing an academic essay. ’ Meanwhile, some students perceived a rich variety of alternative assessments, which aroused their learning interest and hence promoted their learning behaviour. For example, student A mentioned, ‘ In the creativity course, there were many different types of alternative assessment activities, like filling in surveys and making paper art. I have never had lessons like that. It was fun and interesting … I was always looking forward to that class. ’ However, some students voiced that their perceptions of the assessment became negative when the assessment was monotonous. As student A mentioned, ‘ Although peer assessment was useful, I started losing interest in it because it was part of almost every course. I hope that there will be other ways to evaluate my performance .’ In addition, some students perceived the alternative assessment implementation to be instructive and supportive, which further increased their efforts to learn. As student E stated, ‘ Teachers would regularly track our feedback personally or by electronic tools. I appreciated the teachers’ effort and was motivated to do more in the assessment. ’

4.2.2. Students’ understanding and awareness of alternative assessment

Relevance to the real world substantially contributed to the students' understanding of the alternative assessment. Four students thought that the alternative assessment provided them an opportunity to experience their future profession. For example, student D stated, ‘ The teaching practicum allowed me to examine different teaching techniques I learned from class … I could also try my own methods to see whether the students liked them or not .’ Student F similarly stated, ‘ As I work at a school, I could use the techniques I learned in class, like time management, content delivery and teaching plan design .’ In addition, the students believed that alternative assessment could assist them in developing higher-level skills such as problem-solving and communication skills. These skills may help them to become a life-long learner and might exert a positive long-lasting impact on their lives. For instance, student A mentioned, ‘ Writing reflective journals has taught me how to discover and appreciate the creativity hidden in our daily lives. I will maintain this habit even after finishing the course .’

In terms of the implementation, every student was aware that they had experienced at least two types of alternative assessment. Most of the alternative assessments involved various realistic scenarios, such as writing or making video presentations. Some assessments were peer assessments, portfolios, hands-on activities or professional practicums. Overall, the students preferred other types of assessments over writing assessments. They believed that the experience gained through completing an alternative assessment should build upon exposure to real-life situations. Therefore, they considered obtaining first-hand experience a vivid and effective way to learn. As student A mentioned, ‘ I learn the most when I have the chance to gain hands-on experience. When I worked on paper art assignments, I could apply the creativity theories that I learned in class. ’ Student B also stated, ‘ I wish we could visit the local schools more. Since there are no real students in microteaching, it is less useful. Why don't I just go teach at the tutoring centre where there are real students .’

4.2.3. Perceived teacher support of alternative assessment

All of the students valued the support they received from the university and academic/teaching staff in relation to alternative assessments. This support took various forms, such as providing instructions and coursework to equip the students with the knowledge and ability to complete the assessment, offering samples as a reference and giving feedback. For instance, student F mentioned, ‘ The coursework offered me sufficient knowledge to reflect on my area of study and thus I knew how to do the e-portfolio .’ However, three students reported that they received insufficient support. For instance, student D mentioned, ‘ The practicum guidelines concerning the format and hours were unclear. The department staff failed to answer our questions. This increased my workload unnecessarily and caused me to teach with uncertainty. ’ Such negative feelings could negatively influence their learning experience.

4.2.4. Expectations about future implementation of alternative assessment

As alternative assessment was new to the students, two students wanted to see more samples to gain insight into how others performed. Student E said, ‘ Providing more samples would give me a clearer idea of the teacher's expectations .’ The students would also like to see more informal activities so they can gain more experience without worrying about receiving a low grade. Student D stated, ‘ I wish my teacher would monitor my teaching without grading my performance in the beginning stage of practice so I can have a chance to improve my teaching before the formal evaluation. ’ Moreover, three students expressed their desire to experience more varieties of alternative assessment. As student C asserted, ‘ I would like to see more varieties other than writing, like drawing a mind map or making videos or recordings ... Then I would be more motivated to do the assignment. Some students are not good at writing. Including other varieties would give us an opportunity to use our strength. ’

5. Discussion and practical implications

This study's findings show that students' perceived context of alternative assessment significantly influences their learning behaviour. In addition, attitude partially mediates the relationship between perceived context and learning behaviour. The mixed-methods study design allowed the qualitative investigation to enrich the quantitative findings. For example, the qualitative findings showed that some students perceived the context of alternative assessment as supportive, which further enhanced their positive attitude towards the assessment and increased their engagement in learning. These findings answered RQ1 concerning the relationships between students' attitudes towards, perceived context of and learning behaviours in alternative assessment. They echoed those of other studies such as Lizzio et al. (2002) and Kurtz et al. (2019) . These studies found that if students perceive an assessment to be appropriate and teaching to be empathic, motivating, understandable and helpful, they are more likely to adopt a deep approach to learning. A deep approach to learning is described as seeking for complex understanding and meaning about the course content; conversely, a surface approach—led by a negative perception of the assessment and teaching—merely involves reproducing knowledge without making an effort to integrate the information. Importantly, a deep approach contributes to students' qualitative learning outcomes such as general academic and workplace skills. To improve students' perceived context of alternative assessment, we believe that clear instructions and feedback are critical to forming a supportive assessment context (e.g., Fox et al., 2017 ). For example, clarifying the grading system might mitigate students' uncertainty and anxiety and thus help them to perform better in the assessment ( Litchfield and Dempsey, 2015 ). Additionally, Van Wyk (2017) found that by offering constructive feedback, teachers supported education students in their alternative assessment, which required the students to engage in practice teaching and write a reflective journal. In this way, the education students could self-monitor their teaching performance and successfully develop their own teaching philosophy. Furthermore, the students' higher-order thinking skills, such as critical thinking, was developed through the process of articulating and rethinking their practice in conjunction with the teachers' feedback ( Van Wyk, 2017 ).

This study's qualitative findings contradicted those of other studies in terms of students' understanding and awareness of alternative assessment. Some studies have suggested that university students have a fixed mindset about assessment approaches and that they prefer traditional assessments such as paper-based exams and essays because they are more familiar with these methods (e.g., Adie et al., 2010 ; Lau et al., 2020 ). However, in this study, the students could identify the advantages of the alternative assessment based on their learning experience, such as its practicality and real-world relevance. Unlike traditional assessment, alternative assessment highlighting real-world learning allows students to develop practical hands-on skills ( Sheila et al., 2021 ). Although our quantitative study found that the students generally perceived teacher support to be somewhat low, the qualitative study provided in-depth information about the various levels of teacher support perceived by the students in relation to the assessment. Specifically, whereas some students appreciated the careful guidance they received from their teachers, others felt frustrated because of the unclear instructions and lack of feedback. These findings answered RQ2 regarding students' understanding and awareness of alternative assessment and perceived teacher support in their learning environment. Student perceptions of alternative assessment are critical in how they decide to engage with the assessment. For example, Lau et al. (2020) found that students who had a negative attitude towards making a concept map preferred traditional assessments. Their interest and engagement in the alternative assessment were thus weakened ( Lau et al., 2020 ). Khoury (2022) observed that the translation students found the peer assessment difficult as they were not familiar with the interactive computer-assistance translation tools and lacked the confidence and skills to conduct the task. Cornelius and Kinghorn, 2014 also found that first-year students were generally unfamiliar with the self and peer assessment. To raise the acceptance and participation of students towards the assessment, teachers designed materials and in class activities to allow students becoming familiar with the assessment gradually. Teachers not only provided check boxes to guide the students during the assessment process, but also arranged pair activity for students to comment on each other's’ work in a comparatively stress-free environment. Students in the end generally recognized the peer assessment as a valuable language-learning tool and expressed their willingness to participate in these forms of assessment. Therefore, to improve student perceptions of alternative assessment and to ultimately promote student engagement, universities should pinpoint and address students' concerns by increasing their understanding of alternative assessment and offering follow-up support.

Finally, RQ3 concerning students' expectations in improving alterative assessment was addressed by obtaining information through the student interviews; most of the students expected to receive more information from their teachers and a greater variety of alternative assessment methods. As alternative assessment was newly introduced to the university, it is reasonable that the students' expectations were not completely met. A gap between student expectations and teachers' implementation has often been observed (e.g., Henderson et al., 2019 ). For example, Gulikers (2006) found that students highly value the feedback process because it offers them information to improve. However, teachers’ busy schedules often prevent them from giving students thorough feedback, which can lead to student dissatisfaction with learning ( Henderson et al., 2019 ) because they cannot use feedback to improve their performance. In addition, Kong et al. (2021) mentioned that teachers utilized many online technology tools to facilitate the implementation of alternative assessment in universities. Written assessments take various forms, such as posters, e-portfolios and peer reviews ( Kong et al., 2021 ). However, students in the study of Ajjawi et al. (2020) were not convinced that writing-based alternative assessments could fully reflect their developed skills and abilities; hence, they were frustrated by the lack of recognition for their attainment of general skills. To narrow the gap between student expectations and university implementation, universities should promote and require the adoption of alternative assessment by teachers. As teachers have various understandings about changes in educational practices, university administrators could promote more the philosophy and goals behind alternative assessment methods to them ( Brezicha et al., 2015 ). In addition, universities can provide a platform and network for teachers to discuss their alternative assessment approaches, exchange ideas and receive support from colleagues ( Brezicha et al., 2015 ).

6. Conclusion and limitations

In this mixed-methods study, we used an ABC model to examine university students' perceptions of alternative assessment. The quantitative and qualitative studies both showed that the students' perceived context influenced their learning behaviour directly and indirectly through the mediating role of attitude. Although the students believed that alternative assessment was a practical and rewarding learning tool, they also found difficulties with it, such as a lack of teacher support. Local students' perceived context of alternative assessment has room for improvement, thus the attitude of alternative assessment and their engagement in alternative assessment were too not high. The practical implications of this study are that universities need to spend more effort in successfully shifting from traditional test-based assessment to alternative assessment to provide a better learning experience for students. Universities should investigate what students worry about the assessment and address their concerns accordingly. In our case, the insufficient teacher support and monotonous types of the assessment reported by students had prevented the university from implementing an effective alternative assessment. Possible solutions for these barriers require the effort from both teachers and the universities. Teachers should provide detailed instructions such as clarifying the grading system and offer constructive feedback to overcome students' uncertainty and anxiety. Universities should offer professional development to increase teachers' knowledge of how to give constructive feedback and deliver the assessment in a richer form. Also, university can build up a communication platform for teachers, such that teachers' implementation experiences can be shared and learned among each other. It is hoped that by increasing students' exposure to and increasing teachers' knowledge of the alternative assessment, students' awareness and attitudes toward the alternative assessment could be facilitated and thus the benefits of the alternative assessment can be maximized in students’ learning.

This study has three limitations that could be addressed in future work. First, as alternative assessment was only recently implemented among a small population at the university, the sample size was relatively small, and the response rate was low. Therefore, the findings are generalisable only to a certain extent in this university. Second, the application of the ABC model is also limited by the small sample size. The original ABC model predicts that the attitude–behaviour link is the strongest when contextual factors are at a moderate level. However, we did not have enough data to confirm this theory in our research context. The third limitation concerns the design of the survey. As the questionnaire consists of only positively worded items, the missing of negatively worded items might lead to response bias effects. Also, the third item in the behaviour section includes two questions. This forced students to answer the question inaccurately and thus lowered the validity of the questionnaire. Future studies should recruit more university students to better clarify the relationships between students’ attitudes, behaviours and perceived contextual factors after a university implements alternative assessment. Researchers are also suggested to design the survey including a mixture of positive and negative items to reduce response bias from participants, as well as stating only one question for each item.

Declarations

Author contribution statement.

Siu-Cheung KONG: Conceived and designed the experiments; and contributed reagents, materials, analysis tools and data.

Cheuk-Nam Yuen: Performed the experiments; analyzed and interpreted the data; and wrote the paper.

Funding statement

This work was supported by the Teaching Development Grant (TDG), provided by The Education University of Hong Kong.

Data availability statement

Declaration of interest’s statement.

The authors declare no conflict of interest.

Additional information

No additional information is available for this paper.

• Adie L.E., Hee L., Wharton L. In: Emerging Trends in Higher Education Learning and Teaching: Proceedings of the TARC International Conference on Learning and Teaching. Chin S.N., editor. Tunku Abdul Rahman College; Malaysia: 2010. Incorporating authentic assessment into different university learning scenarios; pp. 82–90. [ Google Scholar ]
• Ahmad S., Sultana N., Jamil S. Behaviourism vs constructivism: a paradigm shift from traditional to alternative assessment techniques. J. Appl. Ling. Lang. Res. 2020; 7 :19–33. [ Google Scholar ]
• Ajjawi R., Tai J., Huu Nghia T.L., Boud D., Johnson L., Patrick C.J. Aligning assessment with the needs of work-integrated learning: the challenges of authentic assessment in a complex context. Assess Eval. High Educ. 2020; 45 (2):304–316. [ Google Scholar ]
• Ashford-Rowe K., Herrington J., Brown C. Establishing the critical elements that determine authentic assessment. Assess Eval. High Educ. 2014; 39 (2):205–222. [ Google Scholar ]
• Atifnigar H., Alokozay W., Takal G.M. Students’ perception of alternative assessment: a systematic literature review. Int. J. Ling. Liter. Trans. 2020; 3 (4):228–240. [ Google Scholar ]
• Berry R. Hong Kong University Press; 2008. Assessment for Learning. [ Google Scholar ]
• Braun V., Clarke V. Using thematic analysis in psychology. Qual. Res. Psychol. 2006; 3 (2):77–101. [ Google Scholar ]
• Brezicha K., Bergmark U., Mitra D.L. One size does not fit all: differentiating leadership to support teachers in school reform. Educ. Adm. Q. 2015; 51 (1):96–132. [ Google Scholar ]
• Brown S. A review of contemporary trends in higher education assessment. @tic. Rev. Innovació Educ. 2015; 14 :43–49. [ Google Scholar ]
• Brown S., Sambell K. 2020. Contingency planning: exploring rapid alternatives to face-to-face assessment. Sally-brown.net. https://sally-brown.net/download/3122/ [ Google Scholar ]
• Chung S.J., Choi L.J. The development of sustainable assessment during the Covid-19 pandemic: the case of the English language program in South Korea. Sustainability. 2021; 13 (8):4499. [ Google Scholar ]
• Cohen J., Cohen P., Stephen G.W., Aiken L.S. third ed. Routledge; 2002. Applied Multiple Regression/Correlation Analysis for the Behavioural Sciences. [ Google Scholar ]
• Cohen L., Manion L., Morrison K. sixth ed. Routledge; London: 2012. Research Methods in Education. [ Google Scholar ]
• Cornelius S., Kinghorn O. Student attitudes towards self and peer assessment in Japanese university first year EFL classes. Foreign Lang. Educ. Forum. 2014; 13 :1–10. [ Google Scholar ]
• Craft J., Ainscough L. Development of an electronic role-play assessment initiative in bioscience for nursing students. Innovat. Educ. Teach. Int. 2015; 52 (2):172–184. [ Google Scholar ]
• Darling-Hammond L., Snyder J. Authentic assessment of teaching in context. Teach. Teach. Educ. 2000; 16 :523–545. [ Google Scholar ]
• Fook C.Y., Sidhu G.K. Authentic assessment and pedagogical strategies in higher education. J. Soc. Sci. 2010; 6 (2):153–161. [ Google Scholar ]
• Fox J., Murphy V., Freeman S., Hughes N. ‘Keeping it real’: a review of the benefits, challenges and steps towards implementing authentic assessment. All Ireland J. Higher Educ. 2017; 9 (3):3232–3239. [ Google Scholar ]
• George D., Mallery P. Allyn & Bacon; 2003. SPSS for Windows Step by Step: A Simple Guide and Reference. 11.0 Update (4th Edition) [ Google Scholar ]
• Guagnano G.A., Stern P.C., Dietz T. Influences on attitude-behaviour relationships: a natural experiment with curbside recycling. Environ. Behav. 1995; 27 (5):699–718. [ Google Scholar ]
• Gulikers J. Datawyse/Universitaire Pers Maastricht; 2006. Authenticity Is in the Eye of the Beholder. Beliefs and Perceptions of Authentic Assessment and the Influence on Student Learning. [ Google Scholar ]
• Henderson M., Ryan T., Phillips M. The challenges of feedback in higher education. Assess Eval. High Educ. 2019; 44 (8):1237–1252. [ Google Scholar ]
• Hu L., Bentler P.M. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Model. 1999; 6 (1):1–55. [ Google Scholar ]
• James L.T., Casidy R. Authentic assessment in business education: its effects on student satisfaction and promoting behaviour. Stud. High Educ. 2018; 43 (3):401–415. [ Google Scholar ]
• Khoury O. Perceptions of student-centered learning in online translator training: findings from Jordan. Heliyon. 2022; 8 (6) [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kong S.C., Lam S.S.M., Lam W.W.M., Lau K.K.M., Yee L.T.S., Yung S.N. Four case studies on applying alternative assessments in higher education with technology tools to facilitate teaching and learning. ICERI2021 Proc. 2021:8843–8850. [ Google Scholar ]
• Kurtz J.B., Lourie M.A., Holman E.E., Grob K.L., Monrad S.U. Creating assessments as an active learning strategy: what are students' perceptions? A mixed methods study. Med. Educ. Online. 2019; 24 (1):1630239. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lau P.N., Chua Y.T., Teow Y., Xue X. Implementing alternative assessment strategies in chemistry amidst COVID-19: tensions and reflections. Educ. Sci. 2020; 10 (11):1–15. [ Google Scholar ]
• Litchfield B.C., Dempsey J.V. Authentic assessment of knowledge, skills, and attitudes. N. Dir. Teach. Learn. 2015; 2015 (142):65–80. [ Google Scholar ]
• Lizzio A., Wilson K., Simons R. University students' perceptions of the learning environment and academic outcomes: implications for theory and practice. Stud. High Educ. 2002; 27 (1):27–52. [ Google Scholar ]
• Lizzio A., Wilson K. First-year students' appraisal of assessment tasks: implications for efficacy, engagement and performance. Assess Eval. High Educ. 2013; 38 (4):389–406. [ Google Scholar ]
• MacKinnon D.P., Lockwood C.M., Williams J. Confidence limits for the indirect effect: distribution of the product and resampling methods. Multivariate Behav. Res. 2004; 39 (1):99–128. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Muthohharoh S., Linggar-Bharati D.A., Rozi F. The implementation of authentic assessment to assess students’ higher order thinking skills in writing at MAN 2 Tulungagung. Engl. Educ. J. 2020; 10 (3):374–386. [ Google Scholar ]
• Nikolova N., Andersen L. Creating shared value through service-learning in management education. J. Manag. Educ. 2017; 41 (5):750–780. [ Google Scholar ]
• Ojung’a J., Allida D. A survey of authentic assessments used to evaluate English language learning in Nandi central sub-county secondary schools. Kenya: Baraton Interdiscipl. Res. J. 2017; 7 :1–11. [ Google Scholar ]
• Palmer S. Authenticity in assessment: reflecting undergraduate study and professional practice. Eur. J. Eng. Educ. 2004; 29 (2):193–202. [ Google Scholar ]
• Putri N.S.E., Pratolo B.W., Setiani F. The alternative assessment of EFL students’ oral competence: practices and constraints. Ethical Lingua: J. Lang. Teach. Learn. 2019; 6 (2):72–85. [ Google Scholar ]
• Reddy P., Chaudhary K., Sharma B., Chand R. The two perfect scorers for technology acceptance. Educ. Inf. Technol. 2020; 26 (2):1505–1526. [ Google Scholar ]
• Sheila N.A., Zhu C., Kintu M.J., Kataike J. Assessing higher education institutional stakeholders' perceptions and needs for community engagement: an empirical evidence from Uganda. Heliyon. 2021; 7 (4) [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Siow L.F. Students' perceptions on self- and peer-assessment in enhancing learning experience. Malays. Online J. Educ. Sci. 2015; 3 (2):21–35. [ Google Scholar ]
• Sokhanvar Z., Salehi K., Sokhanvar F. Advantages of authentic assessment for improving the learning experience and employability skills of higher education students: a systematic literature review. Stud. Educ. Eval. 2021; 70 [ Google Scholar ]
• Stern P. Toward a coherent theory of environmentally significant behaviour. J. Soc. Issues. 2000; 56 (3):407–424. [ Google Scholar ]
• Svinicki M.D. Authentic assessment: testing in reality. N. Dir. Teach. Learn. 2004; 2004 (100):23–29. [ Google Scholar ]
• Van Wyk M.M. Student teachers’ views regarding the usefulness of reflective journal writing as an eportfolio alternative strategy: an interpretive phenomenological analysis. Gender Behav. 2017; 15 (4):10208–10219. [ Google Scholar ]
• Wiewiora A., Kowalkiewicz A. The role of authentic assessment in developing authentic leadership identity and competencies. Assess Eval. High Educ. 2018; 44 (3):415–430. [ Google Scholar ]
• Wiggins G. first ed. Jossey-Bass; 1998. Educative Assessment: Designing Assessments to Inform and Improve Student Performance. [ Google Scholar ]
• Xu X., Maki A., Chen C.F., Dong B., Day J.K. Investigating willingness to save energy and communication about energy use in the American workplace with the attitude-behaviour-context model. Energy Res. Social Sci. 2017; 32 :13–22. [ Google Scholar ]
• Zepeda L., Deal D. Organic and local food consumer behaviour: alphabet theory. Int. J. Consum. Stud. 2009; 33 (5):697–705. [ Google Scholar ]

Home > Journals > IJ-SoTL > Vol. 8 (2014) > No. 2

Disentangling The Effects Of Student Attitudes and Behaviors On Academic Performance

Susan Janssen , University of Minnesota Duluth Follow Maureen O'Brien , University of Minnesota - Duluth Follow

The interplay among motivation, ability, attitudes, behaviors, homework, and learning is unclear from previous research. We analyze data collected from 687 students enrolled in seven economics courses. A model explaining homework and exam scores is estimated, and separate analyses of ability and motivation groups are conducted. We find that motivation and ability explain variation in both homework and exam scores. Attitudes and behaviors, such as procrastination and working with others directly, affect homework score, but not exam score. These effects are not the same within all motivation and ability groups. Given that homework is the strongest predictor of exam score, we conclude that graded homework is beneficial to learning, and attitudes and behaviors related to homework may have an indirect benefit for exam performance. Suggestions are made as to how homework and course design might be managed to help students at different ability and motivational levels maximize learning.

Creative Commons License

Recommended citation.

Janssen, Susan and O'Brien, Maureen (2014) "Disentangling The Effects Of Student Attitudes and Behaviors On Academic Performance," International Journal for the Scholarship of Teaching and Learning : Vol. 8: No. 2, Article 7. Available at: https://doi.org/10.20429/ijsotl.2014.080207

Additional files available below

Since July 30, 2014

https://doi.org/10.20429/ijsotl.2014.080207

• Journal Home
• About this Journal
• Scholarship of Teaching & Learning
• Editorial Board
• Ethics Statement
• Review Process
• Call for Editorial Review Board Members
• SoTL Commons Conference
• Submit Article
• Most Popular Papers
• Receive Email Notices or RSS

Special Issues:

Search gs commons.

Advanced Search

ISSN: 1931‐4744

Home | About | FAQ | My Account | Accessibility Statement

Privacy Copyright

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• My Bibliography
• Collections
• Citation manager

Save citation to file

Email citation, add to collections.

• Create a new collection
• Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

• Search in PubMed
• Search in NLM Catalog
• Add to Search

Teacher and Teaching Effects on Students' Attitudes and Behaviors

Affiliations.

• 1 Harvard Graduate School of Education.
• 2 Brown University.
• PMID: 28931959
• PMCID: PMC5602565
• DOI: 10.3102/0162373716670260

Research has focused predominantly on how teachers affect students' achievement on tests despite evidence that a broad range of attitudes and behaviors are equally important to their long-term success. We find that upper-elementary teachers have large effects on self-reported measures of students' self-efficacy in math, and happiness and behavior in class. Students' attitudes and behaviors are predicted by teaching practices most proximal to these measures, including teachers' emotional support and classroom organization. However, teachers who are effective at improving test scores often are not equally effective at improving students' attitudes and behaviors. These findings lend empirical evidence to well-established theory on the multidimensional nature of teaching and the need to identify strategies for improving the full range of teachers' skills.

Keywords: behavior; happiness; instruction; non-cognitive outcomes; self-efficacy; teacher effectiveness.

PubMed Disclaimer

Scatter plots of teacher effects…

Scatter plots of teacher effects across outcomes. Solid lines represent the best-fit regression…

Similar articles

• Teachers' physiological and self-reported stress, teaching practices and students' learning outcomes in Grade 1. Jõgi AL, Pakarinen E, Lerkkanen MK. Jõgi AL, et al. Br J Educ Psychol. 2023 Apr;93 Suppl 1:211-226. doi: 10.1111/bjep.12529. Epub 2022 Jun 30. Br J Educ Psychol. 2023. PMID: 35774026
• The impact of gender differences in teachers' teaching practices and attitudes on students' math and science achievement in Saudi Arabia: Evidence from TIMSS 2019 data. Alnahdi GH, Schwab S. Alnahdi GH, et al. Front Psychol. 2023 Feb 23;14:1066843. doi: 10.3389/fpsyg.2023.1066843. eCollection 2023. Front Psychol. 2023. PMID: 36910826 Free PMC article.
• Associations among teachers' depressive symptoms and students' classroom instructional experiences in third grade. McLean L, Abry T, Taylor M, Connor CM. McLean L, et al. J Sch Psychol. 2018 Aug;69:154-168. doi: 10.1016/j.jsp.2018.05.002. Epub 2018 Jun 6. J Sch Psychol. 2018. PMID: 30558750
• The effect of perceived teachers' interpersonal behavior on students' learning in physical education: a systematic review. Tian L, Shen J. Tian L, et al. Front Psychol. 2023 Aug 29;14:1233556. doi: 10.3389/fpsyg.2023.1233556. eCollection 2023. Front Psychol. 2023. PMID: 37720632 Free PMC article. Review.
• Conflict management strategies in coping with students' disruptive behaviors in the classroom: Systematized review. Mahvar T, Ashghali Farahani M, Aryankhesal A. Mahvar T, et al. J Adv Med Educ Prof. 2018 Jul;6(3):102-114. J Adv Med Educ Prof. 2018. PMID: 30013994 Free PMC article. Review.
• Empirical Research on Technological Pedagogical Content Knowledge (TPACK) Framework in Health Professions Education: A Literature Review. Ait Ali D, El Meniari A, El Filali S, Morabite O, Senhaji F, Khabbache H. Ait Ali D, et al. Med Sci Educ. 2023 Apr 26;33(3):791-803. doi: 10.1007/s40670-023-01786-z. eCollection 2023 Jun. Med Sci Educ. 2023. PMID: 37501808 Free PMC article. Review.
• A theoretical review of the role of teacher professional development in EFL students' learning achievement. Zeng J. Zeng J. Heliyon. 2023 Apr 27;9(5):e15806. doi: 10.1016/j.heliyon.2023.e15806. eCollection 2023 May. Heliyon. 2023. PMID: 37180889 Free PMC article. Review.
• Multi-dimensional potential factors influencing COVID-19 vaccine booster acceptance and hesitancy among university academic community in Bangladesh: A cross-sectional comparative study. Roy DN, Azam MS, Islam E. Roy DN, et al. PLoS One. 2023 Apr 13;18(4):e0281395. doi: 10.1371/journal.pone.0281395. eCollection 2023. PLoS One. 2023. PMID: 37053270 Free PMC article.
• Investigating students' attitudes towards translation technology: The status quo and structural relations with translation mindsets and future work self. Tian S, Jia L, Zhang Z. Tian S, et al. Front Psychol. 2023 Feb 16;14:1122612. doi: 10.3389/fpsyg.2023.1122612. eCollection 2023. Front Psychol. 2023. PMID: 36874868 Free PMC article.
• Evaluation of Attitudes toward Corporal Expression in Primary School Students: Validation and Psychometric Properties of a Questionnaire. Rojo-Ramos J, Polo-Campos I, Hernández-Mosqueira C, Gomez-Paniagua S. Rojo-Ramos J, et al. Int J Environ Res Public Health. 2023 Feb 16;20(4):3463. doi: 10.3390/ijerph20043463. Int J Environ Res Public Health. 2023. PMID: 36834158 Free PMC article.
• Achenbach TM, McConaughy SH, Howell CT. Child/adolescent behavioral and emotional problems: implications of cross-informant correlations for situational specificity. Psychological Bulletin. 1987;101(2):213. - PubMed
• Backes B, Hansen M. Working Paper 146. Washington, D C: National Center for Analysis of Longitudinal in Education Research; 2015. Teach for America impact estimates on nontested student outcomes. Retrieved from http://www.caldercenter.org/sites/default/files/WP&%20146.pdf .
• Bandura A, Barbaranelli C, Caprara GV, Pastorelli C. Multifaceted impact of self-efficacy beliefs on academic functioning. Child Development. 1996:1206–1222. - PubMed
• Baron J. Personality and intelligence. In: Sternberg RJ, editor. Handbook of human intelligence. New York: Cambridge University Press; 1982. pp. 308–351.
• Blazar D. Effective teaching in elementary mathematics: Identifying classroom practices that support student achievement. Economics of Education Review. 2015;48:16–29.

Related information

Grants and funding.

• P2C HD041020/HD/NICHD NIH HHS/United States

LinkOut - more resources

Full text sources.

• Europe PubMed Central
• PubMed Central

Other Literature Sources

• scite Smart Citations
• Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

ORIGINAL RESEARCH article

The impact of social behavior and peers’ attitudes toward students with special educational needs on self-reported peer interactions.

• 1 Centre of Teacher Education, University of Vienna, Vienna, Austria
• 2 Research Focus Area Optentia, North-West University, Vanderbijlpark, South Africa
• 3 Institute of Psychology, University of Graz, Graz, Austria

According to the literature, social participation (e.g., peer interactions) of students diagnosed with special educational needs (SEN) has to be focused upon as they are at a higher risk of being socially excluded compared to students without SEN. Research has pointed out that social participation of students with SEN is influenced by their own social behavior as well as the attitudes of peers with no SEN toward them. The present study assessed the impact of the social behavior of students diagnosed with SEN ( n = 88; 48 boys and 40 girls) as well as that of the attitudes of their peers without SEN ( n = 227; 139 boys and 153 girls) toward them on the social participation. Results indicated that students without SEN were less likely to interact with their classmates with SEN. Peer interactions of students with SEN were not significantly influenced by their own social behavior.

Introduction

According to the European policy (see Schwab, 2020 for an overview), inclusive education refers to the enhancement of the developmental opportunities of all students and the removal of different types of barriers. Students diagnosed with special education needs (SEN 1 ) are particularly focused on as a target group in research as there is a long history of educating them in special classes. The present paper refers to inclusive education in terms of physically and socially including students with SEN in mainstream classes. In Austria more than half of the students with SEN are nowadays educated in mainstream classes; their parents can decide whether they attend mainstream classes or special classes (for an overview of the Austrian inclusive educational system, see Schwab, 2014 , 2018a ). One reason why parents do not choose mainstream schools is the concern that their child could be socially excluded.

Social Participation of Students With and Without SEN

The term “social participation” comprises relevant social aspects of inclusion and includes the following as core themes: students’ social interactions (e.g., spending time together while working on a project or during breaks), peer acceptance, friendships, and self-perception of social inclusion (e.g., feeling lonely) (see the reviews of Koster et al., 2009 ; Bossaert et al., 2013 ). To summarize the results of recent literature reviews ( Koster et al., 2009 ; Bossaert et al., 2013 ; Schwab, 2018b ), the social participation of students with SEN is lower compared to their peers without SEN. The reviews showed that students with SEN have lower peer acceptance, fewer friendships, and less peer interactions compared to students without SEN. Mamas et al. (2020) demonstrated that students with SEN were less likely to receive friendship nominations from their peers. Nepi et al. (2015) showed in their study that students with SEN are rarely chosen as favored classmates by their peers without SEN. With specific focus on peer interactions, usually operationalized as time spent together, the literature clearly shows that students with SEN have fewer interactions with classmates than their peers without SEN (e.g., Schwab, 2015 ; Henke et al., 2017 ; Petry, 2018 ). A study by Schwab (2017) revealed that students with SEN are less frequently chosen by their peers for joint activities, such as working together on a school project. However, differences within a group (e.g., students with SEN) are often higher than differences between groups (e.g., students with and without SEN). In light of these results, it is particularly important to identify opportunities to promote social participation of students with SEN (see Hassani et al., 2020 ). Many factors may play a role in determining social participation of students: e.g., factors within the student, within the educational environment (educational processes), and classroom-related or contextual factors. A crucial way to foster students’ social participation is to improve individual student variables, such a students’ attitudes and/or their social behavior (see the review of Hassani et al., 2020 ). Within the framework of this study, the focus will be on the social behavior of students with SEN and without SEN as well as on students’ attitudes toward peers with special needs. Therefore, factors at the individual level (of students) as well as within the educational environment (e.g., attitudes and social behavior of class members) will be addressed in the present paper.

Students’ Social Behavior and Its Impact on Social Participation

Based on the literature (see Schwab et al., 2015a ), the presence of pro-social behavior and the absence of behavioral problems in students with SEN seem to be particularly important for social participation. Studies have shown that students with SEN (particularly those with learning disabilities) show more aggressive behavior and less pro-social behavior compared to their peers without SEN (for an overview, see Schwab, 2014 ). Mand (2007) observed that students with behavioral problems were rather unpopular in both inclusive and special education systems and thereby concluded that social behavior plays a prominent role in social participation. According to the results by Schwab (2014) , social participation of students is mainly determined by their social behavior and social skills. Sociometric studies have provided evidence that popular students show more positive associated social behavior, whereas socially rejected students show significantly more negative associated behavior (e.g., aggressive behavior) than averagely rated students (e.g., Newcomb et al., 1993 ; Jones and Frederickson, 2010 ). These results can be underpinned by research in other contexts: For instance, the results of the study by Lu et al. (2018) show the strong relation between aggressive behavior and students’ popularity in middle and high schools.

Students’ Attitudes Toward Peers With SEN and Its Impact on Social Participation

According to Allport, 1935 , 810) attitude is described as “A mental and neural state of readiness, organized through experience, exerting a directive or dynamic influence upon the individual’s response to all objects and situations with which it is related.” Within the definition of attitude, reference is mostly made to three components: the affective component (which indicates feelings), the behavioral component (which is related to intentions) and the cognitive component (beliefs) (see Eagly and Chaiken, 1998 ). Grütter et al. (2018) analyzed cross-group friendships between students with average academic achievement and students with low academic achievement. The authors showed that these intergroup friendships increase the social participation of low-achieving students due to the resulting increase in sympathy and intergroup trust.

Changes in students’ intergroup attitudes can be explained with the intergroup contact theory, according to which a stigma-reducing effect of contact on attitudes can be assumed ( Allport, 1954 ; Pettigrew and Tropp, 2000 ). Empirical evidence for this theory has been shown through several studies in the context of SEN ( MacMillan et al., 2013 ; Armstrong et al., 2016a ; de Boer and Pijl, 2016 ; Schwab, 2017 ; Petry, 2018 ) or student achievement ( Grütter et al., 2018 ; see also the review of MacMillan et al., 2013 ). However, not all studies found evidence that students’ attitudes toward peers with SEN influence the social participation of students with SEN ( Petry, 2018 ). One explanation for the inconsistent findings could be that it is not the quantity but rather the quality of contact that is associated with more positive attitudes ( Keith et al., 2015 ; Schwab, 2017 ). Within the theory of planned behavior ( Ajzen, 1991 ), it is assumed that attitudes explain people’s behavior. Moreover, according to the framework of the cognitive dissonance theory of Festinger (1957) , people want to avoid disharmony in attitudes and beliefs. This might explain why students with more negative attitudes toward peers with SEN avoid having contact with them.

There is little literature investigating whether there are class composition effects in peers’ attitudes toward students with SEN. Petry (2018) examined the link between class members’ mean attitudes in relation to peer interactions and showed an effect on students with sensory and/or motor limitations. However, no effect was found on students with autism spectrum disorder.

Objectives of the Study

Despite the knowledge currently available from cross-sectional studies about lower peer interactions of students with SEN in general education, there is still a lack of information about variables that promote the social participation of students with SEN ( de Boer et al., 2013 ). For instance, hardly any studies examine if mean attitudes in class (as an indicator of social norm) influence individual peer attitudes ( Schwab, 2018a ). The current study sought to examine the following hypotheses:

1. Social behavior of students with SEN predicts the interactions between students with and without SEN.

2.a. Individual attitudes of students without SEN toward peers with SEN predict the interactions between students with and without SEN.

2.b. The mean class attitude of students without SEN toward peers with SEN predict the interactions between students with and without SEN.

Materials and Methods

Research design.

The current study is part of the longitudinal research project “Attitudes Toward Inclusion of Students with Disabilities related to Social Inclusion” (ATIS-SI). Data were collected from primary and secondary school students (fourth and seventh graders, respectively). The fourth grade was chosen as it is the last year of primary education in Austria and students know each other for three years by this point. The seventh grade was chosen from secondary school as the students know each other for at least two years by this time. Since students with SEN sometimes repeat classes, the number of students with SEN in seventh grade was expected to be higher than in the eighth grade. Besides, students with SEN may already have completed the required nine years of compulsory school in Austria. However, the exact duration of placement of students with disability in these classes was not assessed in this project.

Data for the ATIS-SI study were collected at three measurement points. At the first measurement point (T1; beginning of the school year), fourth and seventh graders from three Austrian Federal States, Styria, Lower Austria and Burgenland, participated in the paper-and-pencil survey. The second measurement point (T2) was at the end of the school year. In addition, a questionnaire was also completed by secondary school students (the former seventh graders) at the end of grade eight (T3). However, since student in the primary schools moved to different secondary schools after T2, data for T3 are not available for this subsample. The series of questionnaires encompassed topics such as social participation, social behavior, and attitudes toward peers with SEN. At each measurement point, students spent approximately 50 min to complete the questionnaires. The data were collected by trained research assistants. A team of two or three trained research assistants supported students in filling out the paper-pencil questionnaires. They also assisted those students who had difficulties (e.g., they read the questions for students with reading difficulties).

Study Procedure

For the current study, data from T1 to T2 were used. At T1, 63 classes participated in the paper-and-pencil survey. At T2, 60 of those classes participated again. Only those students who completed the questionnaires at both measurement points (T1 and T2) were included in the analysis. However, only a subset of the ATIS-SI data was used in this study because around half of the sample contained data from regular classes (in which no students with SEN diagnosis are taught). Further, for the current study, only ratings from students without SEN regarding their interactions and attitudes toward peers with SEN were included. As such, the ratings of students with SEN about their interactions with peers (and their attitudes toward peers with SEN) were not included in the analysis. This was done because of the interest in inter-group effects rather than in intra-group effects. However, students’ social behavior ratings for the subsample of students with SEN were included in the analyses. Further, the female sample included only the ratings for female peers, while the male sample included only the ratings for male peers. The rational for this decision was that previous literature already indicated differences in friendship patterns related to gender (see e.g., Mjaavatn et al., 2016 ). Example, it was already shown that social interactions of students mostly occur within same gender groups (e.g., Underwood, 2004 ). In addition, in classes with only one student with SEN, either the girls or the boys without SEN (depending on the sex of the student with SEN) were excluded from further calculations.

Ethical Approval

The research was approved by the Regional School Authorities of Styria, Lower Austria and Burgenland and informed consent was obtained from all participants completing the questionnaires and their parents.

Participants

The sample for the present study consisted of 292 students without SEN (153 girls and 139 boys; 66.4% fourth graders, 33.6% secondary graders) from 20 primary (fourth graders, approximately 9–11 years old) and secondary (seventh graders, approximately 12–14 years old) school classes from Austria. These students rated 88 students with SEN (40 girls and 48 boys). About 10.5% of the students in the sample were born outside Austria. Additionally, more than 30% of the students in the sample speak a language other than German with their parents. Generally, in Austria, as in many countries, students from a migrant background and with lower socioeconomic status are overrepresented in the subsample of students with SEN (see Gebhardt et al., 2013 ). Moreover, in Austria, up to five students with SEN are in one class, and in most of the Austrian inclusive classes two teachers (a regular and a special needs teacher) teach together. In addition, as George and Schwab (2019) demonstrated using a nation-wide sample in inclusive classes in Austria, students with low socioeconomic status, students of parents with low educational levels as well as students with non-German-speaking parents are overrepresented in Austrian inclusive classes.

Special Educational Needs (SEN) With Respect to Learning (T1)

In Austria, students with SEN need an official statement from the local educational authority to qualify for additional resources (see Schwab, 2018a ). Since in the present study most students with diagnosed SEN had SEN related to learning disabilities 2 (more than 80%) and only a very small number of students with SEN had other types of SEN (e.g., behavioral disorders), it was not possible to perform calculations for different subgroups of students with SEN.

Social Behavior of Students (T1 Only)

One of the instruments most frequently used to assess the behavioral problems of students is the Strengths and Difficulties Questionnaire (SDQ; Goodman and Goodman, 2011 ), which assesses students’ behavioral problems from different perspectives (e.g., self-perspective, parents’ or teachers’ view). In the current study, the self-perspective version for children was used. 3 The SDQ consists of 25 items, five items per subscale (emotional symptoms, conduct problems, hyperactivity/inattention, peer relationship problems, and pro-social behavior), to be answered on a 3-point Likert scale (not true = 0, somewhat true = 1, certainly true = 2). Satisfactory reliability and a replicable factor structure of this have been shown in previous research ( Klasen et al., 2000 ). Further, Schwab et al. (2015c) showed that the SDQ is also acceptable for a slightly younger sample (students aged 9). Moreover, researchers have already shown that the student version of the SDQ is suitable for students with and without SEN (see DeVries et al., 2018 ). The Cronbach’s Alpha for the SDQ problem score within the ATIS-SI study was.75. For the purpose of this study, the peer relationship problems scale was not included. The scores for the other four SDQ subscales were standardized.

Attitudes Toward Students With SEN With Respect to Learning Disabilities (T1 and T2)

Attitudes toward students with SEN (i.e., with learning disabilities) were assessed using a short German version ( Schwab, 2015 ) of the Chedoke-McMaster Attitudes toward Children with Handicaps Scale (CATCH; see also Rosenbaum et al., 1986 ). First, students had to read a brief case description. Girls were given a female version (with a female character) and boys were given a male version. The female case was introduced as follows ( Schwab, 2015 , 180): “Susanne has just moved to your city and goes to the same school as you. Susanne has great difficulties with reading, writing, and mathematics. She needs more time to solve exercises than other children.” These vignettes are used to avoid stigmatizing effects through the use of negatively connoted words such as “disability.” Moreover, the concept of learning disabilities may not be clear to school children; therefore, describing an unknown case seems more appropriate. Students had to answer the six items of the short version of the CATCH on a 5-point rating scale (never = 1, rarely = 2, sometimes = 3, often = 4, always = 5) measuring the affective and behavioral components of attitudes (e.g., “I would feel good doing a school project with Susanne”). This version was built up from a previous seven-item version of Bossaert and Petry (2013) in which five items belong to the affective component and two items to the behavioral component. The cognitive subscale was not used as other research has shown that this subscale does not create a unidimensional and internally consistent scale ( Armstrong et al., 2016b ). The psychometric qualities (i.e., unidimensional factor structure and measurement invariance between students with SEN versus students without SEN, as well as high reliability) of this short German version have been demonstrated by Schwab (2015) . One item was deleted as the confirmatory factor analysis showed that the item fit is higher when removing this item. The results of the confirmatory factor analysis indicated a good fit for the six-item version and the reliability (Cronbach’s Alpha) was above 9 (for more details, see Schwab, 2015 ). Further, Schwab (2015) showed that there is no measurement bias between students with and without SEN for this scale. The Cronbach’s Alpha for T1 was 80 and T2 was 85. For the purpose of this study, a standardized mean score ( M = 0, SD = 1) of the six items was used.

Peer Interaction (T1 and T2)

A peer rating method was used as a criterion (dependent variable) since this method is a powerful tool for measuring students’ social participation. Students (without SEN 4 ) were asked to indicate their response to the following question on a 5-point scale (never = 1, rarely = 2, sometimes = 3, often = 4, always = 5): “How often do you interact with each of your classmates during breaks?” A list with the names of all peers was provided so that students could rate them. For the analysis of peer interaction with students with SEN, the same-sex ratings of each student without SEN toward their peer with SEN was used.

Statistical Analysis

Based on the results of de Boer et al. (2013) as well as on literature about same-sex preference in friendships (see Aboud and Mendelson, 1996 ), it seems that gender plays an important role in the social participation of students with SEN. Female/male vignettes were used to assess the attitudes toward peers with SEN (see Schwab, 2015 ) to avoid gender effects (e.g., girls might generally have more negative attitudes toward boys compared to girls). Moreover, it might be the case that constructs (e.g., intergroup effects; peer influences) function differently for girls and boys. Therefore, this study focused on same-sex results and data for girls and boys were analyzed separately. For girls, the dependent variable was the peer interaction of girls without SEN with girls with SEN. Similarly, for boys, the dependent variable was the peer interaction of boys without SEN with boys with SEN.

The hierarchically nested structure of our data was taken into account by multilevel regression analyses of peer interaction (Level 2: classes, Level 1: students; see also de Boer et al., 2013 ). For both hypotheses, we used a multilevel model without entering any predictors (null model) to estimate the variance in Level 2 versus Level 1 and to calculate the size of the intra-class correlations (ICCs, reported in Table 1 ). The ratings of students without SEN have been used as dependent variables within these analyses.

Table 1a. Means, standard deviations, and intra-class correlations (ICC) for peer interaction of boys with SEN versus boys without SEN as reported by boys without SEN (T1).

Table 1b. Means, standard deviations, and intra-class correlations (ICC) for peer interaction of girls with SEN versus girls without SEN by as reported girls without SEN (T1).

For Hypothesis 1, a multilevel model (Level 2: classes) was employed with the social behaviors of students with SEN (along with grade) as predictors and their peer interactions, as reported by students without SEN, as outcome variables (see Tables 2 – 4 ).

Table 2. Influence of social behavior of students with SEN at T1 on their peer interactions during breaks at T1 as reported by boys or girls without SEN.

Table 3. Influence of social behavior of students without SEN at T1 on their peer interactions during breaks at T1 as reported by boys or girls without SEN.

Table 4. Influence of social behavior of students with SEN at T1 on their peer interactions during breaks at T2 as reported by girls or boys without SEN.

For Hypothesis 2, a multilevel model (Level 2: classes) was used with the individual and class mean social attitudes of the students without SEN (together with grade) as predictors (see Tables 5 – 7 ) and their reports on their peer interactions with students with SEN as the outcome variable.

Table 5. Influence of attitudes toward students with SEN at T1 on peer interactions during breaks at T1 as reported by boys or girls without SEN.

Table 6. Influence of attitudes toward students with SEN at T2 on peer interactions during breaks at T2 as reported by boys or girls without SEN.

Table 7. Influence of attitudes toward students with SEN at T1 on peer interactions during breaks at T2 as reported by boys or girls without SEN.

Moreover, for both hypotheses, a cross-sectional analyses (see Tables 2 , 3 , 5 , 6 ) as well as longitudinal analyses (see Tables 4 , 7 ) were conducted. In the cross-sectional analysis both, the predictors and the dependent variable (peer interaction), came from either T1 or T2, whereas in the longitudinal analysis the predictors came from T1 and the dependent variable from T2.

In the multilevel analysis, the metric variables were grand-mean centered.

Tables 1a , b show the means, standard deviations and intra-class correlations (ICCs indicating the variance in class level) for peer interactions during breaks. For both genders, the means show that during breaks, students without SEN interact less frequently with their classmates with SEN than they do with their classmates without SEN. The size of the ICCs further indicates variation between classes in the frequency of peer interactions during breaks. Compared to the other ICCs (0.41–0.45), the lower ICC for peer interactions of girls with SEN (ICC = 0.24) during breaks is noteworthy. Nevertheless, the size of all ICCs underlines the need for multilevel analyses instead of regular multiple regression analyses.

Hypothesis 1: The peer interactions of students with SEN during breaks can be predicted by their social behavior

To investigate this hypothesis, three multilevel analyses were conducted, the first two for cross-sectional data and the third for longitudinal data. Table 2 shows the results of the cross-sectional analysis for students with SEN. In order to provide a reference point for interpreting these results, the same multilevel analyses were conducted for students without SEN (see Table 3 ). Finally, a longitudinal analysis for students with SEN using the behavior scores from T1 as predictors and the peer interactions during breaks of students with SEN at T2 as criterion (see Table 4 ) were performed.

As can be seen in Table 2 , the peer interaction of students with SEN is not significantly influenced by their own social behavior. Table 3 shows the results of the same multilevel analyses, but now conducted for students without SEN. While there are some significant effects of social behavior, the effects are nevertheless relatively small (all βs ≤ | 0.12|). For boys, conduct problems negatively influenced peer interactions during breaks; for girls, conduct problems as well as hyperactivity and emotional symptoms predicted peer interactions during breaks. A positive link was found for hyperactivity, indicating that higher hyperactivity is associated with more interaction.

Finally, Table 4 shows the results of the longitudinal analysis. For girls with SEN, the results resemble those of the cross-sectional analysis. For boys with SEN, however, an unexpected effect arises: The higher the hyperactivity of students with SEN (β = 0.35, p < 0.05) the more their peer interaction with their male peers.

Hypothesis 2: The peer interactions of students with SEN during breaks can be predicted by (a) the individual attitudes of students without SEN toward peers with SEN and/or (b) the respective class means

To investigate this hypothesis, three multilevel analyses were conducted: the first two for the cross-sectional data (see Tables 5 , 6 , respectively) and the third one for the longitudinal data ( Table 7 ). For boys, positive attitudes toward male peers with SEN significantly predict their peer interaction, either through individual attitudes at T1 (β = 0.15, p < 0.05) or average class attitudes at T2 (β = 1.38, p < 0.05). For girls, however, negative attitudes toward female peers with SEN significantly predict their peer interaction with them at T1 (β = –0.67, p < 0.01) but not at T2 (β = –0.20, p > 0.10). Finally, as can be seen in Table 7 , the longitudinal analysis showed no significant results. Although not significant, the average class attitudes also predict peer interaction in the cross-sectional analysis of T1 (β = 0.59) as well as the longitudinal analysis (β = 0.86).

In line with previous studies, this study shows that students with SEN in inclusive educational settings are not automatically socially included. The results show that peers with no SEN interact less frequently with peers with SEN than they do with peers without SEN. Given the highly negative impact of low social participation on students’ academic, social, emotional, and mental health development ( Låftman and Östberg, 2006 ; Kidger et al., 2012 ), this problem should be addressed and given a much higher priority in schools. In this study, the variance in peer interactions in terms of class levels indicates that there are classes which handle the social participation of students with SEN better, while other classes have greater difficulties. One explanation for the low levels of interaction of students without SEN with their peers with SEN during breaks could be that, in some cases, teachers spend time with students with SEN during the breaks. They try to finish exercises with them or explain to them what they did not understand during the lesson (see Bajzek et al., 2014 ), etc. Although it is important to make sure that all students keep track of what was thought during class, a practical recommendation would be for teachers to give students with SEN the chance to interact with their peers during breaks. To prove this assumption, future research should observe students and their teachers during breaks to identify possible factors hindering the interactions between peers with and without SEN. Additionally, results of this study clearly underpinned that social interactions in inclusive classrooms need to be promoted actively (see e.g., Mamas and Avramidis, 2013 ). Another explanation could be that it is not the environment but the social behavior of students with SEN that predicts their low peer interactions. This was analyzed within hypothesis 1. For cross-sectional data, no link between the peer interaction of students with SEN (boys and girls) and their social behavior (emotional symptoms, conduct problems, hyperactivity/inattention, pro-social behavior) was found. In comparison, for students without SEN, some significant effects of social behavior on their peer interactions were found. Maybe Hypothesis 1 (the peer interactions of students with SEN during breaks can be predicted by their social behavior) remained unsupported due to a methodological weakness of the study. To examine this hypothesis a self-perspective version of SDQ for children was used to assess students’ social behavior. However, results from Schwab et al. (2016) lead to the conclusion that students with SEN show a tendency to underestimate their own peer problems when using the SDQ. Finally, the results of the longitudinal analysis show that for boys with SEN, hyperactivity predicts more peer interaction from their male peers. It can only speculated that hyperactivity, an externalizing disorder, may manifest itself in boys with SEN playing the class clown and therefore being perceived as funny by their male peers. In line with this, Jonkmann et al. (2009) showed that high popularity in seventh graders could be predicted by positive and deviant behavior alike.

Another explanation for low interaction with peers with SEN could be the attitude of peers with no SEN toward students with SEN. Therefore, hypothesis 2 was related to the predictive validity of the individual attitudes of students without SEN as well as the respective mean class attitude. It was anticipated that the individual and mean class attitudes of students without SEN toward their peers with SEN could predict the interactions of students with SEN during breaks. For boys, the cross-sectional data on T1 show that the individual attitudes of students without SEN toward their peers with SEN predicted their interactions with peers with SEN at T1, while the mean class attitude was no significant predictor. At T2, this effect was the other way around: while the individual attitude was not significantly linked to the peer interactions of students with SEN, the mean class attitudes were related to the interactions. Therefore, improving boys’ attitudes toward students with SEN could be a relevant factor for increasing the social participation of their male peers with SEN. Like other studies, this study also indicates that, for the male sample, direct contact is positively linked to students’ attitudes ( MacMillan et al., 2013 ). For teachers, this means promoting high quality contacts between students with and without SEN in classes.

The results of the female sample were even more complex. The cross-sectional data for the first measurement showed a negative effect of the mean class attitudes. This means that the more negative the mean class attitudes of girls toward their peers with SEN are, the more often individual students had contact with their female peers with SEN. One possible interpretation of this result could be that individual girls are aware that their peers have rather negative attitudes toward students with SEN and they therefore try to compensate for this through socially desirable behavior or care. However, the longitudinal analysis showed no significant results for both samples, neither for the individual attitude nor for the mean class attitude. In line with this result, one must bear in mind that the question of attitudes toward peers with SEN is rather theoretical (referring to an imaginary student who was new in the class). Therefore, the predictor was more theoretical, while the criterion was real peer interactions with real students with SEN. Future research should focus on the real attitudes toward the actual students with SEN in the class and link this to the social participation of the students with SEN in order to increase the external validity and practical relevance. For teachers, the findings imply that they have to ensure social inclusion of all students, and that is not something that can be easily aimed for. However, there are still some possibilities for teachers to foster students’ social participation (see the review of Hassani et al., 2020 ). Creating a positive climate (e.g., in the sense of positive attitudes toward students with SEN) might be an important topic and teachers need to be aware of its power. Further, teachers should also foster students’ social competences in order to avoid behavior problems – not solely of students without SEN but also of those with SEN.

Limitations

This study provides more insight into the possible reasons for students without SEN having fewer interactions with their peers with SEN than with peers without SEN during their breaks. Some limitations of this study need to be pointed out: First, as mentioned before, a self-assessments was used to rate students’ social behavior. However, self-report questionnaires may not actually reflect real behavior, and could be biased due to social desirability or other effects, such as wanting to be part of the group or “cool” ( Müller et al., 2013 ). To avoid such effects, longitudinal observations by independent observers in classrooms would be necessary. In addition, scores of the SDQ were used as indicators of social behavior. The SDQ is rather a proxy measure of social behavior and it is used as a screening measure for diagnosing psychiatric disorders. Moreover, a further critical issue is the operationalization of students with SEN. Previous research in Austria ( Schwab et al., 2015b ) clearly pointed out a lack of transparency and clarity in the diagnosing process. It might be the case that some students who have SEN are not diagnosed as such. Even if the focus is only on students with SEN with respect to learning disabilities, the group will be fairly heterogeneous. Another limitation is the use of vignettes to assess students’ attitudes toward peers with learning disabilities. Especially because associations were made within this study between the attitudes toward hypothetical students and the relationship with actual peers in classes. As Schwab (2018b) showed, students may not be able to make a connection between the hypothetical case vignettes and their actual peers in class. Last but not least, for reliable causal interpretation, it would also be necessary to have more measurement points and use a cross-lagged-panel design.

In spite of these limitations, this study pointed out that the need for more insight into possible predictors of low social participation among students with SEN and the necessity of more longitudinal research, as results often show different patterns.

Data Availability Statement

The data analyzed in this study is subject to the following licenses/restrictions: Due to the granting of anonymity and data protection agreements, the dataset analyzed for this study is only available upon reasonable request from the corresponding author. Requests to access these datasets should be directed to SS, [email protected] .

Ethics Statement

The research was approved by the Regional School Authorities of Styria, Lower Austria, and Burgenland. Written informed consent to participate in this study was provided by the participants legal guardian.

Author Contributions

SS, NT, and ML have jointly designed the manuscript and gave feedback and revised everything. ML was responsible for the data collection and supported mainly in the writing of the method and the results. NT did the analyses and authored the results. SS wrote the introduction and discussion. All authors agreed to be accountable for the content of the work.

The University of Vienna funded the open access fee.

Conflict of Interest

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.

The reviewer CM declared a past co-authorship with one of the authors SS to the handling Editor.

• ^ Within this study the term SEN refers to students with a diagnosis of SEN rather than to those having SEN. There is a lack of reliability and transparency in the criteria of diagnosed SEN within research. In other words, since students with undiagnosed SEN are often not considered in empirical studies, this term rather tends to include those students who are officially diagnosed with SEN (see Schwab, 2020 ). Moreover, having a disability (in Austria) does not necessarily mean that a student has SEN.
• ^ In Austria, students with learning difficulties do not include those with specific learning difficulties such as dyslexia or dyscalculia. The category “learning difficulties” rather refers to students with lower academic competences in all subjects and lower intelligence scores compared to their peers (for a detailed information about learning difficulties in Austria, see Gebhardt et al., 2013 ). Generally, within the group of students with SEN, the proportion of students with SEN related to learning disabilities is highest in Austria (see Schwab et al., 2015b ). Moreover, within this study, students with some disabilities (e.g., severe mental disabilities) were not included as the study design was inappropriate for this subsample.
• ^ The self-version was used to avoid missing some information (teacher ratings were not available for all students).
• ^ For the data analysis of this study, only the ratings of students without SEN were used. However, students with SEN participated at the data collection too and filled out the identical questionnaires.

Aboud, F. E., and Mendelson, M. J. (1996). “Determinants of friendships selection and quality: developmental perspectives,” in The Company they Keep: Friendship in Childhood and Adolescence , 1st Edn, eds W. M. Bukowski, A. F. Newbomb, and W. W. Hartup (New York: Cambridge University Press), 87–112.

Google Scholar

Ajzen, I. (1991). The theory of planned behavior. Organ. Behav. Hum. Decision Process. 50, 179–211.

Allport, G. W. (1935). “Attitudes,” in A Handbook of Social Psychology , ed. C. A. Murchison (Worcester, MA: Clark University Press), 798–844.

Allport, G. W. (1954). The Nature of Prejudice. New York: Doubleday Anchor Books.

Armstrong, M., Morris, C., Abraham, C., Ukoumunne, O. C., and Tarrant, M. (2016a). Children’s contact with people with disabilities and their attitudes towards disability: a cross-sectional study. Disabil. Rehabil. 38, 879–888. doi: 10.3109/09638288.2015.1074727

PubMed Abstract | CrossRef Full Text | Google Scholar

Armstrong, M., Morris, C., Tarrant, M., Abraham, C., and Horton, M. C. (2016b). Rasch analysis of the chedoke-mcmaster attitudes towards children with handicaps scale. Disabil. Rehabil. 39, 281–290. doi: 10.3109/09638288.2016.1140833

Bajzek, V., Helmhart, M., Pilz, A., and Stoimaier, J. (2014). “SchülerInnen mit sonderpädagogischem Förderbedarf in Integrationsklassen – Wie integriert sind sie wirklich?,” in Ausschnitte Aus der Grazer Inklusionsforschung , ed. S. Schwab (Hamburg: Kovać), 47–70.

Bossaert, G., Colpin, H., Pijl, S. J., and Petry, K. (2013). Truly included? a literature study focusing on the social dimension of inclusion in education. Int. J. Inclusive Educ. 17, 60–79. doi: 10.1080/13603116.2011.580464

CrossRef Full Text | Google Scholar

Bossaert, G., and Petry, K. (2013). Factorial validity of the Chedoke-McMaster attitudes towards children with handicaps scale (CATCH). Res. Dev. Disab . 34, 1336–1345. doi: 10.1016/j.ridd.2013.01.007

de Boer, A., and Pijl, S. P. (2016). The acceptance and rejection of peers with ADHD and ASD in general secondary education. J. Educ. Res. 109, 325–332. doi: 10.1080/00220671.2014.958812

de Boer, A., Pijl, S. J., Post, W., and Minnaert, A. (2013). Peer acceptance and friendships of students with disabilities in general education: the role of child, peer, and classroom variables. Soc. Dev. 22, 831–844.

DeVries, J. M., Voß, S., and Gebhardt, M. (2018). Do learners with special education needs really feel included? evidence from the perception inclusion questionnaire and strengths and difficulties questionnaire. Res. Dev. Disabil. 83, 28–36. doi: 10.1016/j.ridd.2018.07.007

Eagly, A. H., and Chaiken, S. (1998). “Attitude structure and function,” in The Handbook of Social Psychology , eds D. T. Gilbert, S. T. Fiske, and G. Lindzey (New York: McGraw - Hill), 269–322.

Festinger, L. (1957). A Theory of Cognitive Dissonance. Stanford, CA: Stanford University Press.

Gebhardt, M., Krammer, M., Schwab, S., Rossmann, P., and Gasteiger-Klicpera, B. (2013). What is behind the diagnosis of learning disabilities in Austrian schools? an empirical evaluation of the diagnostic process. Int. J. Special Educ. 28, 160–166.

George, A. C., and Schwab, S. (2019). “Österreichs integrationsklassen: kompetenzdefizite durch soziale benachteiligung? ein vergleich zwischen integrations- und regelklassen,” in Fünf Jahre Flächendeckende Bildungsstandardüberprüfungen in Österreich , eds C. Schreiner, C. Wiesner, A. C. George, K. Pacher, and M. Pointinger (Münster: Waxmann), 103–114.

Goodman, A., and Goodman, R. (2011). Population mean scores predict child mental disorder rates: validating SDQ prevalence estimators in Britain. J. Child Psychol. Psychiatry 52, 100–108. doi: 10.1111/j.1469-7610.2010.02278.x

Grütter, J., Gasser, L., Zuffianò, A., and Meyer, B. (2018). Promoting inclusion: the mediating role of change in trust and sympathy. Child Dev. 89, 414–430.

Hassani, S., Aroni, K., Toulia, A., Alves, S., Górel, G., Lóper, M. F., et al. (2020). School-based Interventions to Support Student Participation. a Comparison of Different Programs. Results from the Friend-Ship Project. Vienna: University of Vienna.

Henke, T., Bogda, K., Lambrecht, J., Bosse, S., Koch, H., Maaz, K., et al. (2017). Will you be my friend? a multilevel network analysis of friendships of students with and without special educational needs backgrounds in inclusive classrooms. Zeitschrift für Erziehungswissenschaft 20, 449–474. doi: 10.1007/s11618-017-0767-x

Jones, A. P., and Frederickson, N. (2010). Multi-informant predictors of social inclusion for students with autism spectrum disorders attending mainstream school. J. Autism. Dev. Disord. 40, 1094–1103. doi: 10.1007/s10803-010-0957-3

Jonkmann, K., Trautwein, U., and Lüdtke, O. (2009). Social dominance in adolescence: the moderating role of the classroom context and behavioral heterogeneity. Child Dev. 80, 338–355. doi: 10.1111/j.1467-8624.2009.01264.x

Keith, J. M., Bennetto, L., and Rogge, R. D. (2015). The relationship between contact and attitudes: reducing prejudice toward individuals with intellectual and developmental disabilities. Res. Dev. Disabil. 47, 14–26. doi: 10.1016/j.ridd.2015.07.032

Kidger, J., Araya, R., Donovan, J., and Gunnell, D. (2012). The effect of the school environment on the emotional health of adolescents: a systematic review. Pediatrics 129, 925–949. doi: 10.1542/peds.2011-2248

Klasen, H., Woerner, W., Wolke, D., Meyer, R., Overmeyer, S., Kaschnitz, W., et al. (2000). Comparing the german versions of the strengths and difficulties questionnaire (SDQ-Deu) and the child behavior checklist. Eur. Child Adolesc. Psychiatry 9, 271–276. doi: 10.1007/s007870070030

Koster, M., Nakken, H., Pijl, S. J., and van Houten, E. J. (2009). Being part of the peer group: a literature study focussing on the social dimension of inclusion in education. Int. J. Inclusive Educ. 13, 117–140. doi: 10.1080/13603110701284680

Låftman, S. B., and Östberg, V. (2006). The pros and cons of social relations: an analysis of adolescents health complaints. Soc. Sci. Med. 63, 611–623. doi: 10.1016/j.socscimed.2006.02.005

Lu, T., Lin, S., Ji, L., Liu, L., Chen, X., and French, D. C. (2018). Longitudinal associations between popularity and aggression in chinese middle and high school adolescents. Dev. Psychol. 54, 2291–2301. doi: 10.1037/dev0000591

MacMillan, M., Tarrant, M., Abraham, C., and Morris, C. (2013). The association between children’s contact with people with disabilities and their attitudes towards disability: a systematic review. Dev. Med. Child Neurol. 56, 529–546. doi: 10.1111/dmcn.12326

Mamas, C., and Avramidis, E. (2013). Promoting social interaction in the inclusive classroom: lessons from inclusive schools in England and Cyprus. Learn. Cult. Soc. Interact. 2, 217–226. doi: 10.1016/j.lcsi.2013.07.001

Mamas, C., Bjorklund, P., Daly, A. J., and Moukarzel, S. (2020). Friendship and support networks among students with disabilities in middle school. Int. J. Educ. Res. 103:101608. doi: 10.1016/j.ijer.2020.101608

Mand, J. (2007). Social position of special needs pupils in classroom: a comparison between german special schools for pupils with learning difficulties and integrated primary school classes. Eur. J. Special Needs Educ. 1, 7–14. doi: 10.1080/08856250601082182

Mjaavatn, P. E., Frostad, P., and Pijl, S. J. (2016). Adolescents: differences in friendship patterns related to gender. Issues Educ. Res. 26, 45–64.

Müller, C. M., Begert, T., Hofmann, V., and Studer, F. (2013). Effekte der Klassenzusammensetzung auf individuelles schulisches problemverhalten – welche rolle spielt das verhalten der gesamtklasse, der;coolen“, der;extremen “und der persönlichen freunde? (effects of class composition on individual problem behaviour at school - what role does the behaviour of the whole class, the “cool”, the “extreme” and personal friends play). Zeitschrift für Pädagogik 59, 722–742.

Nepi, L. D., Fioravanti, J., Nannini, P., and Peru, A. (2015). Social acceptance and the choosing of favourite classmates: a comparison between students with special educational needs and typically developing students in a context of full inclusion. Br. J. Special Educ. 42, 319–337. doi: 10.1111/1467-8578.12096

Newcomb, A. F., Bukowski, W. M., and Pattee, L. (1993). Children’s peer relations: a meta-analytic review of popular, rejected, neglected, controversial, and average sociometric status. Psychol. Bull. 113, 99–128. doi: 10.1037/0033-2909.113.1.99

Petry, K. (2018). The relationship between class attitudes toward peers with a disability and peer acceptance, friendships and peer interactions of students with a disability in regular secondary schools. Eur. J. Special Needs Educ. 33, 254–268. doi: 10.1080/08856257.2018.1424782

Pettigrew, T. F., and Tropp, L. R. (2000). “Does inter-group contact reduce prejudice: recent meta-analytic findings,” in Reducing Prejudice and Discrimination. The Claremont Symposium on Applied Social Psychology , ed. S. Oskamp (Mahwah, NJ: Lawrence Erlbaum Associates), 93–114.

Rosenbaum, P., Armstrong, R., and King, S. (1986). Children’s attitudes toward disabled peers: a self-report measure. J. Pediatr. Psychol. 11, 517–530. doi: 10.1093/jpepsy/11.4.517

Schwab, S. (2014). Schulische Integration, Soziale Partizipation und Emotionales Wohlbefinden in der Schule. Ergebnisse einer empirischen Längsschnittstudie (Inclusive Education, Social Participation and Emotional Well-being in School. Results from an Empirical Longitudinal Study. Münster: Lit. Verlag.

Schwab, S. (2015). Einflussfaktoren auf die Einstellung von schülerinnen gegenüber peers mit unterschiedlichen Behinderungen (determinants of students‘ attitudes towards peers with different kinds of disabilities. Zeitschrift für Entwicklungspsychologie und Pädagogische Psychologie 47, 177–187.

Schwab, S. (2017). The impact of contact on students attitudes towards peers with disabilities. Res. Dev. Disabil. 62, 160–165. doi: 10.1016/j.ridd.2017.01.015

Schwab, S. (2018a). Attitudes Towards Inclusive Schooling. A study on Students Teachers and Parents Attitudes. Münster: Waxmann Verlag.

Schwab, S. (2018b). “Peer-relations of students with special educational needs in inclusive education,” in Diritti Cittadinanza Inclusione , eds S. Polenghi, M. Fiorucci, and L. Agostinetto (Rovato: Pensa MultiMedia), 15–24.

Schwab, S. (2020). Inclusive and Special Education in Europe. Oxford Research Encylopedia of Education. Oxford: Oxford University Press.

Schwab, S., Gebhardt, M., Hessels, M. G. P., and Nusser, L. (2016). Predicting a high rate of self-assessed and parent-assessed peer problems – is it typical for students with disabilities? Res. Dev. Disabil. 4, 196–204. doi: 10.1016/j.ridd.2015.11.026

Schwab, S., Gebhardt, M., Krammer, M., and Gasteiger-Klicpera, B. (2015a). Linking self-rated social inclusion to social behaviour. an empirical study of students with and without special education needs in secondary schools. Eur. J. Special Needs Educ. 30, 1–14.

Schwab, S., Hessels, M. G. P., Obendrauf, T., Polanig, M. C., and Wölflingseder, L. (2015b). Assessing special educational needs in Austria: description of labeling practices and their evolution from 1996 to 2013. J. Cogn. Educ. Psychol. 14, 329–342. doi: 10.1891/1945-8959.14.3.329

Schwab, S., Rossman, P., Tanzer, N., Hagn, J., Oitzinger, S., Thurner, V., et al. (2015c). Schulisches wohlbefinden von schülerinnen mit und ohne sonderpädagogischen förderbedarf. integrations- und regelklassen im vergleich (school well-being of students with and without special educational needs. comparison of integration and regular classes). Zeitschrift für Kinder- und Jugendpsychatrie 43, 265–274.

Underwood, M. K. (2004). “Gender and peer relations: are the two gender cultures really all that different?,” in Children’s Peer Relations: From Development to Intervention , eds J. B. Kupersmidt and K. A. Dodge (Washington, DC: American Psychological Association), 21–36. doi: 10.1037/10653-002

Keywords : students, behavior disorders, special educational needs, attitudes, peer interaction

Citation: Schwab S, Lehofer M and Tanzer N (2021) The Impact of Social Behavior and Peers’ Attitudes Toward Students With Special Educational Needs on Self-Reported Peer Interactions. Front. Educ. 6:561662. doi: 10.3389/feduc.2021.561662

Received: 17 June 2020; Accepted: 07 April 2021; Published: 29 April 2021.

Reviewed by:

Copyright © 2021 Schwab, Lehofer and Tanzer. 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: Susanne Schwab, [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.

• Financial Profile
• Our Supporters
• Diversity, Equity, and Inclusion

Founded in 1974, MDRC is committed to improving the lives of people with low incomes. We design promising new interventions, evaluate existing programs, and provide technical assistance to build better programs.

• Publications

MDRC develops evidence about solutions to some of the nation’s most difficult problems. Explore our projects and variety of products, including publications, videos, podcast episodes, and resources for researchers and practitioners.

• Issues We Focus On
• Services We Offer

Student Context, Student Attitudes and Behavior, and Academic Achievement

An Exploratory Analysis

What are the key factors that promote academic success among students whose demographic characteristics and school circumstances place them at high risk of failure? This paper provides highly suggestive, although not conclusive, answers to this question. Through path analysis modeling techniques applied to data collected in MDRC’s evaluation of the First Things First school reform initiative in a large urban school district, the paper explores the influence of two psychological variables — student engagement and perceived academic competence — on achievement in reading and mathematics. This study’s findings may have important implications for understanding how students learn in the classroom. Consonant with previous research, they indicate that both engagement in school and students’ perception of their own academic competence influence achievement in mathematics for high school students. But the study departs from earlier work in suggesting that perceived academic competence may be more influential than engagement in boosting achievement in both mathematics and reading. Indeed, analyses indicate that perceived competence had a stronger influence on subsequent engagement than engagement had on students’ perceptions of themselves as competent learners. The findings also make clear that supportive teachers and clear and high expectations about behavior are key to the development of both student engagement and perceived competence. This study suggests that the earlier schools and teachers begin to build students’ confidence in their ability to do well, the better off students will be. Because students’ perceptions of their capacity for success are key to their engagement in school and learning, schools should be designed to enhance students’ feelings of accomplishment. Teachers whom students see as supportive and who set clear expectations about behavior help create an atmosphere in which students feel in control and confident about their ability to succeed in future educational endeavors.

Document Details

Sign up for email updates..

Get the latest info on MDRC publications, projects, and other news. We send email updates a couple of times each month.

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Journal Proposal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Factors influencing students’ behavior and attitude towards online education during covid-19.

1. Introduction

2. literature review, 2.1. online learning and education, 2.2. online education and teachers, 2.3. students behavior and attitude toward online education, 3. materials and methods, 3.1. sample and measurement tool, 3.2. purpose of the study.

• Student’s individual characteristics (age, gender, education level);
• Student’s needs: frequency of entering the online platform (F), hours spent on the virtual platform (H), hours to study and learn from materials proposed by teachers (S), and how useful are digital platforms for their needs and for their better understanding (U);
• Student’s knowledge regarding the type of knowledge, evaluation portfolio, syntheses, test, written examination and online examination (E1, E2, E3, E4 and E5);
• Student’s perception about quality of online education: courses quality (Q), education and learning quality (QE1) and quality of materials presented and information (R).

Factors Influencing Students Behavior

5. discussion, 5.1. variables correlation, 5.2. correlations between items, 5.3. conventional students cluster, 6. conclusions, a swot analyze of online education.

• The topics and tasks proposed to the students following the courses and seminars are several;
• Teachers tend to monitor the student’s progress;
• There is final and ongoing evaluation for the continuity of the learning process;
• The transfer of educational activities in the online environment rather negatively affects only the seminar activities;
• The teacher and student no longer interact enough;
• Total transfer to virtualization of activities.

Institutional Review Board Statement

Informed consent statement, data availability statement, conflicts of interest.

• Frecker, K.; Bieniarz, E. Why Online Education Is Here to Stay. Available online: https://www.lighthouselabs.ca/en/blog/why-education-is-moving-online-for-good (accessed on 29 March 2021).
• Zhu, Z.-T.; Yu, M.-H.; Riezebos, P. A research framework of smart education. Smart Learn. Environ. 2016 , 3 , 1. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Hartono, S.; Kosala, R.; Supangkat, S.H.; Ranti, B. Smart Hybrid Learning Framework Based on Three-Layer Architecture to Bolster Up Education 4.0. In Proceedings of the 2018 International Conference on ICT for Smart Society (ICISS), West Java, Indonesia, 10–12 October 2018; pp. 1–5. [ Google Scholar ]
• Bond, M.A.; Lockee, B.B. Evaluating the effectiveness of faculty inquiry groups as communities of practice for faculty pro-fessional development. J. Form. Design Learn. 2018 , 1–7. [ Google Scholar ] [ CrossRef ]
• Jackson, B.L. Online professional development courses in online teaching for higher education faculty. In Proceedings of the Society for Information Technology and Teacher Education (SITE 2018), San Diego, CA, USA, 26–30 March 2018; pp. 187–195. [ Google Scholar ]
• Elzainy, A.; El Sadik, A.; Al Abdulmonem, W. Experience of e-learning and online assessment during the COVID-19 pandemic at the College of Medicine, Qassim University. J. Taibah Univ. Med. Sci. 2020 , 15 , 456–462. [ Google Scholar ] [ CrossRef ]
• Intentional Futures, Instructional Design in Higher Education: A Report on the Role, Workflow, and Experience of Instructional Designers. 2016. Available online: https://intentionalfutures.com/wp-content/uploads/2017/08/Instructional-Design-in-Higher-Education-Report.pdf (accessed on 29 March 2021).
• McGee, P.; Windes, D.; Torres, M. Experienced online instructors: Beliefs and preferred supports regarding online teaching. J. Comput. High. Educ. 2017 , 29 , 331–352. [ Google Scholar ] [ CrossRef ]
• Rhode, J.; Krishnamurthi, M. Preparing Faculty to Teach Online: Recommendations for Developing. Int. J. Inf. Educ. Technol. 2016 , 6 , 376–382. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Iwai, Y. Online Learning during the COVID-19 Pandemic: What do we gain and what do we lose when classrooms go virtual? Sci. Am. 2020 , 13 , 32–37. [ Google Scholar ]
• Dandara, O. Platformele electronice—Mijloc de modernizare a tehnologiilor educaționale. Studia Univ. Mold. 2013 , 5 , 13. [ Google Scholar ]
• Allen, I.E.; Seaman, J. Digital Learning Compass: Distance Education Enrollment Report 2017 ; Babson Survey Research Group, Babson College: Wellesley, MA, USA, 2017. [ Google Scholar ]
• Espiritu, J.L.; Budhrani, K. Cultivating an e-learning culture. Sci. Pedagog. Exp. 2019 , 56 , 3–32. [ Google Scholar ]
• Dhawan, S. Online Learning: A Panacea in the Time of COVID-19 Crisis. J. Educ. Technol. Syst. 2020 , 49 , 5–22. [ Google Scholar ] [ CrossRef ]
• Jæger, M.M.; Blaabæk, E.H. Inequality in learning opportunities during Covid-19: Evidence from library takeout. Res. Soc. Strat. Mobil. 2020 , 68 , 100524. [ Google Scholar ] [ CrossRef ]
• European Commission. Digital Education Action Plan (2021–2027)|Education and Training. Available online: https://ec.europa.eu/education/education-in-the-eu/digital-education-action-plan_en (accessed on 27 April 2021).
• Schmidt, S.W.; Tschida, C.M.; Hodge, E.M. How faculty learns to teach online: What administrators need to know. Online J. Distance Learn. Adm. 2016 , 19 , 1–10. [ Google Scholar ]
• Mishra, L.; Gupta, T.; Shree, A. Online teaching-learning in higher education during lockdown period of COVID-19 pandemic. Int. J. Educ. Res. Open 2020 , 1 , 100012. [ Google Scholar ] [ CrossRef ]
• Bojović, Ž.; Bojović, P.D.; Vujošević, D.; Šuh, J. Education in times of crisis: Rapid transition to distance learning. Comput. Appl. Eng. Educ. 2020 , 28 , 1467–1489. [ Google Scholar ] [ CrossRef ]
• Moskal, P.; Thompson, K.; Futch, L. Enrollment, Engagement and Satisfaction in the BlendKit Faculty Development Open, Online Course. Online Learn. 2015 , 19 , 1–12. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Moore, R.L.; Fodrey, B.P.; Piña, A.A.; Lowell, V.L.; Harris, B.R. Distance Education and Technology Infrastructure: Strategies and Opportunities. In Leading and Managing e-Learning ; Springer: Berlin/Heidelberg, Germany, 2017; pp. 87–100. [ Google Scholar ]
• Mohr, S.C.; Shelton, K. Best Practices Framework for Online Faculty Professional Development: A Delphi Study. Online Learn. 2017 , 21 , 123–140. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Baran, E.; Correia, A.-P. A professional development framework for online teaching. TechTrends 2014 , 58 , 95–101. [ Google Scholar ] [ CrossRef ]
• Baran, E.; Correia, A.P.; Thompson, A. Tracing successful online teaching in high education: Voices of exemplary online teachers. Teach. Coll. Rec. 2013 , 115 , 1–41. [ Google Scholar ]
• Brinthaupt, T.M.; Cruz, L.; Otto, S.; Pinter, M. A framework for the strategic leveraging of outside resources to enhance CTL effectiveness. Improv. Acad. 2019 , 38 , 82–94. [ Google Scholar ] [ CrossRef ]
• Elliott, M.; Rhoades, N.; Jackson, C.; Mandernach, J. Professional Development: Designing Initiatives to Meet the Needs of Online Faculty. J. Educ. Online 2015 , 12 , 160–188. [ Google Scholar ] [ CrossRef ]
• Martin, F.; Wang, C.; Sadaf, A. Student perception of helpfulness of facilitation strategies that enhance instructor presence, connectedness, engagement and learning in online courses. Internet High. Educ. 2018 , 37 , 52–65. [ Google Scholar ] [ CrossRef ]
• Cazacu, D. Utilizarea Platformelor Educaționale în Predarea Geografiei. Available online: https://edict.ro/utilizarea-platformelor-educationale-in-predarea-geografiei/ (accessed on 29 March 2021).
• Chatterjee, I.; Chakraborty, P. Use of Information Communication Technology by Medical Educators Amid COVID-19 Pandemic and Beyond. J. Educ. Technol. Syst. 2021 , 49 , 310–324. [ Google Scholar ] [ CrossRef ]
• Grishchenko, N. The gap not only closes: Resistance and reverse shifts in the digital divide in Russia. Telecommun. Policy 2020 , 44 , 102004. [ Google Scholar ] [ CrossRef ]
• Hasan, N.; Bao, Y. Impact of “e-Learning crack-up” perception on psychological distress among college students during COVID-19 pandemic: A mediating role of “fear of academic year loss”. Child. Youth Serv. Rev. 2020 , 118 , 105355. [ Google Scholar ] [ CrossRef ]
• Ionescu, C.; Paschia, L.; Nicolau, N.G.; Stanescu, S.; Stancescu, V.N.; Coman, M.; Uzlau, M. Sustainability Analysis of the E-Learning Education System during Pandemic Period—COVID-19 in Romania. Sustainability 2020 , 12 , 9030. [ Google Scholar ] [ CrossRef ]
• Is Online Learning a Sustainable Model for Higher Education? Available online: https://u2b.com/2020/03/20/online-learning-sustainable/ (accessed on 16 June 2021).
• Singh, E.P.; Adhikary, K.; Gupta, M.S.; Singh, S. User Interface Consideration for ScalableC. An Online Collaborative Platforms. In Proceedings of the International Conference on Enterprise Information Systems and Web Technologies, Madeira, Portugal, 8–12 June 2010; pp. 111–116. [ Google Scholar ]
• Diaz, M.C.G.; Walsh, B.M. Telesimulation-based education during COVID-19. Clin. Teach. 2020 . [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Becker, S.A.; Cummins, M.; Davis, A.; Freeman, A.; Hall, C.G.; Ananthanarayanan, V. NMC Horizon Report: 2017 Higher Education Edition ; The New Media Consortium: Austin, TX, USA, 2017. [ Google Scholar ]
• Budhrani, K.; Ji, Y.; Lim, J.H. Unpacking conceptual elements of smart learning in the Korean scholarly discourse. Smart Learn. Environ. 2018 , 5 , 23. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Martin, F.; Bolliger, D.U. Engagement Matters: Student Perceptions on the Importance of Engagement Strategies in the Online Learning Environment. Online Learn. 2018 , 22 , 205–222. [ Google Scholar ] [ CrossRef ]
• Beaunoyer, E.; Dupéré, S.; Guitton, M.J. COVID-19 and digital inequalities: Reciprocal impacts and ditigation strategies. Comput. Hum. Behav. 2020 , 111 , 106424. [ Google Scholar ] [ CrossRef ]
• Zhu, X.; Liu, J. Education in and After Covid-19: Immediate Responses and Long-Term Visions. Post Digit. Sci. Educ. 2020 , 2 . Available online: https://www.researchgate.net/publication/340936542_Education_in_and_After_Covid-19_Immediate_Responses_and_Long-Term_Visions (accessed on 29 March 2021).
• George-Andrei, U.; Olga, P.; Maria, U. Simulation of Electrical Circuits Using Data Acquisition Boards for Online Education. In Proceedings of the 2020 International Conference and Exposition on Electrical and Power Engineering (EPE), Iasi, Romania, 22–23 October 2020; pp. 484–487. [ Google Scholar ]
• Windes, D.L.; Lesht, F.L. The effects of online teaching experience and institution type on faculty perceptions of teaching online. Online J. Distance Learn. Adm. 2014 , 17 , 12. [ Google Scholar ]
• Chakraborty, P.; Mittal, P.; Gupca, M.P.; Yadav, S.; Arira, A. Opinion of students online education during the Covid-19 pandemic. Hum. Behav. Emerg. Technol. 2020 , 1–9. [ Google Scholar ] [ CrossRef ]
• Aguilera-Hermida, A.P. College students’ use and acceptance of emergency online learning due to COVID-19. Int. J. Educ. Res. Open 2020 , 1 , 100011. [ Google Scholar ] [ CrossRef ]
• Hodges, C.; Moore, S.; Lockee, B.; Trust, T.; Bond, A. The difference between emergency remote teaching and online learning. Educ. Rev. 2020 , 27 , 1–12. [ Google Scholar ]
• Si, J.; Kong, H.-H.; Lee, S.-H. Exploring medical educators’ readiness and the priority of their educational needs for online teaching. Korean J. Med. Educ. 2021 , 33 , 37–44. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Lunsford, L.; Baker, V.; Pifer, M. Faculty mentoring faculty: Career stages, relationship quality, and job satisfaction. Int. J. Mentor. Coach. Educ. 2018 , 7 , 139–154. [ Google Scholar ] [ CrossRef ]
• Uden, L.; Liberona, D.; Sanchez, G.; Rodriguez Gonzalez, S. (Eds.) Learning Technology for Education Challenges, Proceedings of the 8th International Workshop, LTEC 2019, Zamora, Spain, 15–18 July 2019 ; Springer: Berlin/Heidelberg, Germany, 2019; Available online: https://www.springer.com/gp/book/9783030207977 (accessed on 9 June 2021).
• Carroll, N.; Conboy, K. Normalising the “new normal”: Changing tech-driven work practices under pandemic time pressure. Int. J. Inf. Manag. 2020 , 55 , 102186. [ Google Scholar ] [ CrossRef ]
• Polly, D.; Martin, F.; Guilbaud, T.C. Examining barriers and desired supports to increase faculty members’ use of digital technologies: Perspectives of faculty, staff and administrators. J. Comput. High. Educ. 2021 , 33 , 135–156. [ Google Scholar ] [ CrossRef ]
• Coman, C.; Țîru, L.G.; Meseșan-Schmitz, L.; Stanciu, C.; Bularca, M.C. Online Teaching and Learning in Higher Education during the Coronavirus Pandemic: Students’ Perspective. Sustain. J. Rec. 2020 , 12 , 10367. [ Google Scholar ] [ CrossRef ]
• Arora, A.; Chakraborty, P.; Bhatia, M.P.S.; Mittal, P. Role of emotion in addictive use of twitter during COVID-19 imposed lockdown in India. J. Technol. Behav. Sci. 2020 , 1–8. [ Google Scholar ] [ CrossRef ]
• Trammell, B.; LaForge, C. Common challenges for instructors in large online courses: Strategies to mitigate student and in-structor frustration. J. Educ. Online 2017 , 14 , 10–19. [ Google Scholar ]
• Stark, A.M.; Smith, G.A. Communities of practice as agents of future faculty development. J. Fac. Dev. 2016 , 30 , 59–67. [ Google Scholar ]
• Sheffield, S.L.-M.; McSweeney, J.M.; Panych, A. Exploring Future Teachers’ Awareness, Competence, Confidence, and Attitudes Regarding Teaching Online: Incorporating Blended/Online Experience into the Teaching and Learning in Higher Education Course for Graduate Students. Can. J. High. Educ. 2015 , 45 , 1–14. [ Google Scholar ] [ CrossRef ]
• Trust, T.; Krutka, D.G.; Carpenter, J.P. “Together we are better”: Professional learning networks for teachers. Comput. Educ. 2016 , 102 , 15–34. [ Google Scholar ] [ CrossRef ]
• Rhode, J.; Richter, S.; Miller, T. Designing Personalized Online Teaching Professional Development through Self-Assessment. TechTrends 2017 , 61 , 444–451. [ Google Scholar ] [ CrossRef ]
• Adhikary, K.; Gupta, M.S.; Singh, E.P.; Singh, S. Collaborating Towards Learning: Using Web 2.0 for Educational Idea Development. In Proceedings of the Fifth Conference of Learning International Networks Consortium, Cambridge, MA, USA, 23–26 March 2010; pp. 465–474. [ Google Scholar ]
• Skulmoski, A.; Rey, G.D. COVID-19 as an accelerator for digitalization at a German university. Establishing hybrid campuses in times of crisis. Hum. Behav. Emerg. Technol. 2020 , 2 , 212–216. [ Google Scholar ] [ CrossRef ]
• Toquero, C.M.D.; Talidong, K.J.B. Socio-educational implications of technology use during COVID-19: A case study in general Santos City, Philippines. Hum. Behav. Emerg. Technol. 2020 . [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Zhang, W.; Wang, Y.; Yang, L.; Wang, C. Suspending classes without stopping learning: China’s education emergency man-agement policy in the COVID-19 outbreak. J. Risk Financ. Manag. 2020 , 13 , 55. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Islam, M.A.; Barna, S.D.; Raihan, H.; Khan, M.N.A.; Hossain, M.T. Depression and anxiety among university students during the COVID-19 pandemic in Bangladesh: A web-based cross-sectional survey. PLoS ONE 2020 , 15 , e0238162. [ Google Scholar ] [ CrossRef ]
• Davis, F.D. User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. Int. J. Man-Mach. Stud. 1993 , 38 , 475–487. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Liu, I.-F.; Chen, M.C.; Sun, Y.S.; Wible, D.; Kuo, C.-H. Extending the TAM model to explore the factors that affect Intention to Use an Online Learning Community. Comput. Educ. 2010 , 54 , 600–610. [ Google Scholar ] [ CrossRef ]
• Al Kurdi, B.; Alshurideh, M.; Salloum, S.A.; Obeidat, Z.M.; Al-Dweeri, R.M. An Empirical Investigation into Examination of Factors Influencing University Students’ Behavior towards Elearning Acceptance Using SEM Approach. Int. J. Interact. Mob. Technol. 2020 , 14 , 19–41. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Al Kurdi, B.; Alshurideh, M.; Salloum, S.A. Investigating a theoretical framework for e-learning technology acceptance. Int. J. Electr. Comput. Eng. 2020 , 10 , 6484–6496. [ Google Scholar ] [ CrossRef ]
• Mailizar, M.; Burg, D.; Maulina, S. Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: An extended TAM model. Educ. Inf. Technol. 2021 , 1–21. [ Google Scholar ] [ CrossRef ]
• Bao, W. COVID-19 and online teaching in higher education: A case study of Peking University. Hum. Behav. Emerg. Technol. 2020 , 2 , 113–115. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
• Lee, J.W. Online support service quality, online learning acceptance, and student satisfaction. Internet High. Educ. 2010 , 13 , 277–283. [ Google Scholar ] [ CrossRef ]
• Hung, W.-C.; Jeng, I. Factors influencing future educational technologists’ intentions to participate in online teaching. Br. J. Educ. Technol. 2012 , 44 , 255–272. [ Google Scholar ] [ CrossRef ]
• Hatabu, A.; Mao, X.; Zhou, Y.; Kawashita, N.; Wen, Z.; Ueda, M.; Takagi, T.; Tian, Y.-S. Knowledge, attitudes, and practices toward COVID-19 among university students in Japan and associated factors: An online cross-sectional survey. PLoS ONE 2020 , 15 , e0244350. [ Google Scholar ] [ CrossRef ]
• Zia, A. Exploring factors influencing online classes due to social distancing in COVID-19 pandemic: A business students perspective. Int. J. Inf. Learn. Technol. 2020 , 37 , 197–211. [ Google Scholar ] [ CrossRef ]
• Alzahrani, L.; Seth, K.P. Factors influencing students’ satisfaction with continuous use of learning management systems during the COVID-19 pandemic: An empirical study. Educ. Inf. Technol. 2021 , 1–19. [ Google Scholar ] [ CrossRef ]
• Yunus, M.; Ang, W.S.; Hashim, H. Factors Affecting Teaching English as a Second Language (TESL) Postgraduate Stu dents’ Behavioural Intention for Online Learning during the COVID-19 Pandemic. Sustainability 2021 , 13 , 3524. [ Google Scholar ] [ CrossRef ]
• Essadek, A.; Rabevron, T. Mental health of French students during the Covid-19 pandemic. J. Affect. Disord. 2020 , 277 , 392–393. [ Google Scholar ] [ CrossRef ]
• Paea, S.; Sharma, B.; Bulivou, G.; Paea, M.K. Card Sorting: A new pedagogy for understanding challenges in Mathematics during Emergencies and Crises. Res. Sq. 2021. [ CrossRef ]
• Cao, W.; Fang, Z.; Hou, G.; Han, M.; Xu, X.; Dong, J.; Zheng, J. The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Res. 2020 , 287 , 112934. [ Google Scholar ] [ CrossRef ]
• Hrastinski, S. A Study of Asynchronous and Synchronous e-Learning Methods Discovered that Each Supports Different Purposes. Educ. Q. 2008 , 38 , 51–55. Available online: https://www.researchgate.net/publication/238767486 (accessed on 8 March 2021).
• Amiti, F. Synchronous and asynchronous e-learning. Eur. J. Open Educ. E-Learn. Stud. 2020 , 5 , 60–70. [ Google Scholar ]
• Saraçli, S.; Yilmaz, V.; Arslan, T. The Effects of Mothers’ Educational Levels on University Students’ Environmental Protection Commitments and Environmental Behaviors. Eurasian J. Educ. Res. 2014 , 55 , 177–200. [ Google Scholar ] [ CrossRef ]
• Gumus, H.; Saracli, S.; Yagmur, R.; Isik, O.; Ersoz, Y. The investigation of sportsmanship behaviors of university students. J. Sport Psychol. 2020 , 29 , 13–20. [ Google Scholar ]
• What Does Cronbach’s Alpha Mean? UCLA, Institute for Digital Research and Education, Statistical Consulting. Available online: https://www.statisticshowto.com/probability-and-statistics/statistics-definitions/cronbachs-alpha-spss/ (accessed on 15 June 2021).
• Brown, J.D. The Cronbach alpha reliability estimate. JALT Test. Eval. SIG Newsl. 2002 , 6 , 17–18. [ Google Scholar ]
• Schermelleh-Engel, K.; Moosbrugger, H.; Müller, H. Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures. Methods Psychol. Res. 2003 , 8 , 23–74. [ Google Scholar ]

Click here to enlarge figure

Share and Cite

Boca, G.D. Factors Influencing Students’ Behavior and Attitude towards Online Education during COVID-19. Sustainability 2021 , 13 , 7469. https://doi.org/10.3390/su13137469

Boca GD. Factors Influencing Students’ Behavior and Attitude towards Online Education during COVID-19. Sustainability . 2021; 13(13):7469. https://doi.org/10.3390/su13137469

Boca, Gratiela Dana. 2021. "Factors Influencing Students’ Behavior and Attitude towards Online Education during COVID-19" Sustainability 13, no. 13: 7469. https://doi.org/10.3390/su13137469

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

The influence of college students’ sports policy attitude on sports anomie behavior: a masked chain mediation model

• Published: 23 September 2024

Cite this article

• Yuqing Yang 1 ,
• Liping Liu 1 ,
• Tiantian Guo 2 ,
• Shanping Chen 1 &
• Yao Shang 1  

Explore all metrics

College students’ sports anomie behavior will destroy the regular order of sports activities and restrict the development of young participants’ psychological and physical health. The implementation of sports policy can restrict the behavior of sports anomie. However, implementing the sports policy depends mainly on the attitude of the target group. Previous studies have not paid attention to the relationship between sports policy attitude and sports anomie behavior, and related studies have shown that there is a process of isolation between attitude and behavior, which motivation factors may influence. Therefore, this paper discusses the influence of sports policy attitude on sports anomie behavior and the internal mechanism of sports motivation from the perspective of college students to provide a theoretical basis for improving the effect of policy implementation and reducing sports anomie behavior. A total of 2,340 college students from twenty universities in China across the country voluntarily participated in this survey. The results showed that: (1) sports policy attitude, extrinsic sports motivation and intrinsic sports motivation were both significantly and positively correlated; sports policy attitude, intrinsic sports motivation were significantly and negatively correlated with sports anomie behavior, and extrinsic sports motivation was significantly and positively correlated with sports anomie behavior; (2) Sports policy attitude was negatively and significantly predict sports anomie behavior ( β = − 0.180, P  < 0.001); Sports policy attitude has a significant positive impact on intrinsic sports motivation ( β  = 0.053, P  < 0.001) and extrinsic sports motivation ( β  = 0.260, P  < 0.001). Intrinsic sports motivation had a significant negative impact on sports anomie behavior ( β = − 0.202, P  < 0.001). Extrinsic sports motivation has a significant positive impact on sports anomie behavior ( β  = 0.126, P  < 0.001); extrinsic sports motivation has a significant positive impact on intrinsic sports motivation ( β  = 0.713, P  < 0.001); (3) Sports policy attitude can influence sports anomie behavior through three paths: Ind1: sports policy attitude → intrinsic sports motivation → sports anomie behavior, with intrinsic sports motivation having a partially mediating effect ( t = − 0.011, 95% CI: − 0.018, − 0.005); Ind2: sports policy attitude → extrinsic sports motivation → sports anomie behavior has the opposite sign of the coefficients of the paths, with extrinsic sports motivation having a masked effect ( t  = 0.033, 95%CI: 0.018, 0.049), which reduced the prediction of sports policy attitude on sports anomie behavior; Ind3: sports policy attitude → extrinsic sports motivation → intrinsic sports motivation → sports anomie behavior, and extrinsic and intrinsic sports motivation had chain mediation effects ( t = − 0.037, 95%CI: − 0.051, − 0.026). The study concluded that educating and guiding college students to form positive attitudes toward sports policy is an effective way to reduce sports anomie behavior. Positive sports policy attitudes can stimulate both extrinsic and intrinsic motivations of college students’ sports behaviors. Extrinsic sports motivation alone may exacerbate the occurrence of sports anomie behavior, while intrinsic sports motivation alone will inhibit the occurrence of sports anomie behavior, but the effect is not ideal. Under the effect of college students’ positive sports policy attitude, if extrinsic sports motivation can be transformed into intrinsic sports motivation, it will have a more desirable inhibiting effect on sports anomie behavior.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Data availability

The data that support the findings of this study are not openly available and are available from the corresponding author upon reasonable request.

Ardeńska, A., Tomik, R., Berber, S., et al. (2016). A comparison of physical education students’ motivation using Polish and Turkish versions of the academic motivation scale. Journal of Human Kinetics, 54 , 207. https://doi.org/10.1515/hukin-2016-0046

Article   PubMed   PubMed Central   Google Scholar  

Chen, S. P., Li, X. S., & Yung, J. Z. (2008). Intrinsic and extrinsic sports motivation of college students’ physical activity. Chinese Sports Science and Technology, 04 , 135–138. https://doi.org/10.16470/j.csst.2008.04.030

Article   Google Scholar  

Chen, S. P., Liu, L. P., Bao, J., et al. (2018). Review and prospect of research on youth sports anomie behavior. Sports Research and Education, 33 (6), 16–20. https://doi.org/10.16207/j.cnki.2095-235x.2018.06.004

Chen, S. P., Liu, L. P., Zhang, Z. J., & Bao, J. (2023a). Psychological examination and realistic avoidance of college students’ sports anomie behavior in the context of moral education. Journal of Xi’an Physical Education University, 40 (01), 111–117. https://doi.org/10.16063/j.cnki.issn1001-747x.2023.01.013

Chen, S. P., Liu, L. P., Zhang, Z. J., et al. (2020). Empirical analysis of the theoretical model of National Student Physical Health Standard policy attitude. Journal of Xi’ an Institute of Physical Education, 37 (2), 196–202. https://doi.org/10.16063/j.cnki.issn1001-747x.2020.02.010

Chen, S. P., Liu, L. P., Zhang, Z. J., et al. (2021). Theoretical Construction and empirical research on students’ sports anomie behavior . Xi’an Jiaotong University.

Google Scholar  

Chen, S. P., Shang, Y., Xie, L. J., et al. (2023b). The true value of extrinsic motivation? The effect of intrinsic and extrinsic sports motivation on sports anomie behavior in college students. Current Psychology . https://doi.org/10.1007/s12144-023-04524-1

Article   PubMed   Google Scholar  

Chen, S. P., Song, D., Xie, L. J., Zhang, Z. J., & Liu, L. P. (2023c). Cluster analysis of physical activity motivation and sports behavior characteristics of Chinese college students. Journal of Capital Institute of Physical Education, 35 (01), 57–67. https://doi.org/10.14036/j.cnki.cn11-4513.2023.01.007

Chen, S. P., Wang, Y. B., Rong, J. Z., Pan, X. G., & Bao, J. (2013). The Simplified Version of the MPAM-R: Reliability and validity. Journal of Beijing Sport University, 36(02), 66–70.

Chen, S. P., Zhang, Z. J., Pan, X. G., & Liu, L. P. (2016). The influence of school sports policy attitude on college students’ physical health standard test data. Journal of Chengdu Sport University, 42 (02), 110–115. https://doi.org/10.15942/j.jcsu.2016.02.019

Deci, E. L., & Ryan, R. M. (2000). The what and why of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11 (4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior. An introduction to theory and research . Addison-Wesley.

Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., & Babin, B. J. (2016). Common methods variance detection in business research. Journal of Business Research, 69 (8), 3192–3198. https://doi.org/10.1016/j.jbusres.2015.12.008

Gao, P. F., & Zhou, X. Q. (2016). Social distance and industry anomie: Refle-ctions on the value of School Physical Education Curriculum. Sports and Science, 03 , 63–68. https://doi.org/10.13598/j.issn1004-4590.2016.03.011

Gao, H. L., Lu, C. T., Zhang, B. X., et al. (2021). Theoretical investigation of autonomous motivation generation for physical literacy development–an analysis based on self-determination theory. Journal of Xi’an Institute of Physical Education, 38 (03), 307–314. https://doi.org/10.16063/j.cnki.issn1001-747x.2021.03.007

Guagnano, G. A., Stern, P. C., & Dietz, T. (1995). Influences on attitude-behavior relationships: A natural experiment with curbside ecycling. Environment and Behavior, 27 (5), 699–718. https://doi.org/10.1177/00139165952750

Guo, & Cao, Y. M. (2019). An in-depth analysis of the impact of learning motivation on learning outcomes: An empirical study based on a large-scale student survey. Educational Science Research , (03), 62–67. CNKI:SUN:JYKY.0.2019-03-013.

Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76 (4), 408–420. https://doi.org/10.1080/03637750903310360

Hodge, K., & Gucciardi, D. F. (2015). Antisocial and prosocial behavior in sport: The role of motivational climate, basic psychological needs, and moral disengagement. Journal of Sport & Exercise Psychology, 37 , 257–273. https://doi.org/10.1123/jsep.2014-0225

Hodge, K., & Lonsdale, C. (2011). Prosocial and antisocial behavior in sport: The role of autonomous vs. controlled motivation coaching style, and moral disengagement. Journal of Sport & Exercise Psychology, 33 , 527–547. https://doi.org/10.1123/jsep.33.4.527

Hou, S. J. (2023). Psychological exploration of the influence of Exercise Motivation on College Students’ sports participation motivation. Contemporary Sports Science and Technology, 13 (20), 151–154. https://doi.org/10.16655/j.cnki.2095-2813.2303-1579-0988

Lin, S. H. (2017). Rural residents participate in waste management . Guangdong Academy of Social Sciences.

Liu, W. Z. (2007). Analysis of policy applicable subjects and their policy attitudes. Social Science Research, 4 , 41–45.

Liu, Z. L., Liu, T. T., & Mu, S. K. (2021). Statistical analysis framework of suppression effect and its application. Psychological Technology and Application , (10), 610–618. https://doi.org/10.16842/j.cnki.issn2095-5588.2021.10.004

Lv, H. M. (2020). Exploring the role of personal meaning in the internalization of extrinsic motivation. Shanghai Educational Research , (02), 31–35. https://doi.org/10.16194/j.cnki.31-1059/g4.2020.02.007

Ma, J. (2019). The relationship between the professional identity of public-funded normal students in Ningxia and attitude towards education policy and teaching motivation. Education Observation, 8 (23), 61–64. https://doi.org/10.16070/j.cnki.cn45-1388/g4s.2019.23.020

Ma, C., Wang, X., Wang, R., et al. (2023). The influence of psychological capital on college students’ perceived stress: the mediating effect of cognitive reappraisal and the masking effect of expression suppression. Chinese Journal of Health Psychology, 1-15.

Mac Kinnon, D. P., & Lockwood, C. M., Williams. J (2004). Confidence limits for the indirect effect:Distribution of the product and resampling methods. Multivariate Behavioral Research, 39 , 99–128. https://doi.org/10.1207/s15327906mbr3901_4

Pang, M. X. (2020). The effect of parents’ mathematics attitude on students’ mathematics achievement: The chain mediating effect of mathematics motivation and mathematics anxiety. Adolescence Journal, 01 , 22–27. https://doi.org/10.16399/j.cnki.qsnyj.2020.01.005

Podsakoff, P. M., Mackenzie, S. B., Lee, J. Y., et al. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Applied Psychology, 88 (55), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior research methods, instruments, & computers, 36, 717-731.

Ragheb, M. G., & Tate, R. L. (1993). A behavioral model of leisure participation, based on leisure attitude, motivation and satisfaction. Leisure Studies, 12 (1), 61–70.

Richard, M., Christina, M. F., Deborah, L. S., Rubio, N., & Kennon, M. S. (1997). Intrinsic motivation and exercise adherence. International Journal of Sport Psychology, 28(4), 335–354.

Robbins, S. P. & Judge, T. A. (2007). Organizational Behavior (Li Yuan & Sun J. M translated).  China Renmin University Press.

Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25 (01), 54–67. https://doi.org/10.1006/ceps.1999.1020

Ryan, R. M., & Deci, E. L. (2017). Self -determination theory: Basic psychological needs in motivation, development, and wellness . The Guilford.

Book   Google Scholar  

Song, M. Q. (2018). Research on physical education teacher training students’ physical education attitude, teacher career motivation and their relationship . Nanjing Normal University.

Tang, D. D., & Wen, Z. L. (2020). Common method deviation test: Issues and recommendations. Journal of Psychological Science, 43 (01), 215–223. https://doi.org/10.16719/j.cnki.1671-6981.20200130

Teng, Z. H. (2018). Research on the effects of attitude, motivation, and self-efficacy on college students’ sports participation. Journal of Anhui Engineering University, 33 (03), 75–79. CNKI:SUN:AHJD.0.2018-03-017.

Wang, X. Z., Yang, Y. G., Kong, L., Zhang, J. X., & Yu, H. S. (2023). Challe-nges and paths of sports health promotion for children and adolescents in China on the new journey-based on the study and thinking of the spirit of the 20th National Congress of the Communist Party of China. Journal of Tianjin University of Physical Education , (01), 9–16. https://doi.org/10.13297/j.cnki.issn1005-0000.2023.01.002

Wen, Z. L., & Ye, B. J. (2014). Mediating effect analysis: Method and model development. Advances in Psychological Science, 22 (5), 731–745. https://doi.org/10.3724/SP.J.1042.2014.00731

Wen, Z. L., Hou, J. T., & Zhang, L. (2005). A comparison of moderator and mediator and their applications. Acta Psychologica Sinica, 7 (02), 268–274.

Wen, Z. L., Zhang, L., Hou, J. T., & Liu, H. Y. (2004). Testing and application of the mediating effects. Acta Psychologica Sinica, 36 (05), 614–620.

Xie, L., Zhao, D. P., & Yan, J. H. (2009). A study on the relationship between physical activity attitude and behavior of adolescents. Journal of Tianjin Sports Institute, 24 (01), 72–74.

Zhang, X. L. (2017). Research on the influence of learning motivation on learning behavior based on self-determination theory. Journal of Zhejiang Ocean University (Human Sciences Edition), 34 (03), 62–67.

Zhang, L., & Wang, Z. Q. (2022). Study on the participation of primary and secondary school students in ice and snow sports from the perspective of self-determination theory: The mediating effect of the perception of difficulty. Journal of Xi’an Physical Education University, 39 (02), 150–160. https://doi.org/10.16063/j.cnki.issn1001-747x.2022.02.004

Zhang, Q. F., Yan, L., Shen, B. L., et al. (2018). Equity and quality: Imbalance and development in the National Student Physical Fitness Standards. Journal of Tianjin Sports Institute, 33 (02), 110–114. https://doi.org/10.13297/j.cnki.issn1005-0000.2018.02.003

Zhen, H. J. (2023). Study on the influence of college students’ exercise attitude and sports participation behavior on interpersonal skills and their correlation . Inner Mongolia Normal University.

Download references

Acknowledgements

This study was supported by the National Social Science Fund Project (17BTY001); Social Science Foundation of Shaanxi Province (2018R07); 2022 Xi’ an Jiaotong University Undergraduate Experimental Practice and Innovation and Entrepreneurship Teaching Reform Project (2022SJZX68).

Author information

Authors and affiliations.

Center for Physical Education, Xi’an Jiaotong University, Xi’an, China

Yuqing Yang, Liping Liu, Shanping Chen & Yao Shang

Institute of Physical Education, Minnan University of Science and Technology, Quanzhou, China

Tiantian Guo

You can also search for this author in PubMed   Google Scholar

Contributions

L.L., Y.S. and S.C.: methodology and software. Y.Y.: data curation. Y.Y. and T.G.: analysis, and writing — original draft preparation. Both authors have read and agreed to the published version of the manuscript. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Liping Liu .

Ethics declarations

Ethical statement.

The studies involving human participants were reviewed and approved by the Ethics Committee at the Xi’an Jiaotong University following the Declaration of Helsinki. The participants provided written informed consent to participate in the study.

Conflict of interest

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

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Yang, Y., Liu, L., Guo, T. et al. The influence of college students’ sports policy attitude on sports anomie behavior: a masked chain mediation model. Curr Psychol (2024). https://doi.org/10.1007/s12144-024-06456-w

Download citation

Accepted : 21 July 2024

Published : 23 September 2024

DOI : https://doi.org/10.1007/s12144-024-06456-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Sports policy attitude
• Sports anomie behavior
• Sports motivation
• Masked effect
• Chain mediation
• College students
• Find a journal
• Publish with us
• Track your research