problem solving ability rrl

Developing real life problem-solving skills through situational design: a pilot study

• Development Article
• Published: 09 July 2019
• Volume 67 , pages 1529–1545, ( 2019 )

Cite this article

• Lin Zhong   ORCID: orcid.org/0000-0003-2875-3461 1 &
• Xinhao Xu 2  

1665 Accesses

12 Citations

Explore all metrics

Current problem-solving research has advanced our understanding of the problem-solving process but has provided little advice on how to teach problem-solving skills. In addition, literature reveals that individual difference is an essential issue in problem-solving skills instruction but has been rarely addressed in current research. Building upon information-processing theory, this article proposes an instructional design model, namely the situational design model, which serves as an approach to accommodate individual difference in problem-solving skills instruction. This design model was further examined with a pilot study in an introductory technology course and results showed a significant difference in students’ academic performance and problem-solving skills, especially the non-recurrent skills. The proposed situational design model contributes to research and practice by providing a novel lens to explore problem-solving skills and assisting in the design of instruction that aims to develop student’s expertise in solving real world problems.

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

Similar content being viewed by others

Designing Problem-Solving for Meaningful Learning: A Discussion of Asia-Pacific Research

Problem Solving from a Behavioral Perspective: Implications for Behavior Analysts and Educators

Problem-solving support and instructional sequence: impact on cognitive load and student performance

Explore related subjects.

• Artificial Intelligence
• Digital Education and Educational Technology

Angeli, C. (2013). Examining the effects of field dependence–independence on learners’ problem-solving performance and interaction with a computer modeling tool: Implications for the design of joint cognitive systems. Computers & Education, 62, 221–230.

Article   Google Scholar  

Bulu, S. T., & Pedersen, S. (2012). Supporting problem-solving performance in a hypermedia learning environment: The role of students’ prior knowledge and metacognitive skills. Computers in Human Behavior, 28 (4), 1162–1169.

Cronbach, L. J., & Snow, R. E. (1977). Aptitudes and instructional methods . New York: Irvington.

Google Scholar  

Delahaye, B. L., & Smith, H. E. (1995). The validity of the learning preference assessment. Adult Education Quarterly, 45, 159–173.

Eseryel, D., Ge, X., Ifenthaler, D., & Law, V. (2011). Dynamic modeling as a cognitive regulation scaffold for developing complex problem-solving skills in an educational massively multiplayer online game environment. Journal of Educational Computing Research, 45 (3), 265–286.

Frensch, P. A., & Funke, J. (1995). Definitions, traditions, and a general framework for understanding complex problem solving. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European perspective (pp. 3–26). Hillsdale, NJ: Lawrence Erlbaum Associates.

Ge, X. (2013). Designing learning technologies to support self-regulation during ill-structured problem-solving processes. In R. Azevedo & V. Aleven (Eds.), International Handbook of Metacognition and Learning Technologies (pp. 213–228). Berlin: Springer.

Chapter   Google Scholar  

Ge, X., & Land, S. M. (2004). A conceptual framework for scaffolding ill-structured problem-solving processes using question prompts and peer interactions. Educational Technology Research and Development, 52 (2), 5–22.

Ge, X., Law, V., & Huang, K. (2016). Detangling the interrelationships between self-regulation and ill-structured problem solving in problem-based learning. The Interdisciplinary Journal of Problem-Based Learning, 10 (2), 11. https://doi.org/10.7771/1541-5015.1622 .

Guglielmino, L. M. (1978). Development of the self-directed learning readiness scale. (Doctoral dissertation, University of Georgia, 1977). Dissertation. Abstracts International, 38 , 6467.

Hanover Research. (2016). McGraw - hill education 2016 workforce readiness survey . Retrieved from https://www.fastcompany.com/3059940/these-are-the-biggest-skills-that-new-graduates-lack .

Hersey, P., Blanchard, K. H., & Johnson, D. E. (2012). Management of organizational behavior: Leading human resources (10th ed.). Upper Saddle, NJ: Prentice Hall.

Jeotee, K. (2012). Reasoning skills, problem solving ability and academic ability: Implications for study programme and career choice in the context of higher education in Thailand (Doctoral dissertation, Durham University).

Jonassen, D. H. (2007). Learning to solve complex, scientific problems . Mahwah, NJ: Lawrence Erlbaum Associates.

Jonassen, D. H., & Grabowski, B. (2012). Handbook of individual differences, learning, and instruction . New York: Routledge.

Kalyuga, S., & Sweller, J. (2004). Measuring knowledge to optimize cognitive load factors during instruction. Journal of Educational Psychology, 96 (3), 558–568.

Kalyuga, S., & Sweller, J. (2005). Rapid dynamic assessment of expertise to improve the efficiency of adaptive e-learning. Educational Technology Research and Development, 53 (3), 83–93.

Kim, M. K. (2012). Theoretically grounded guidelines for assessing learning progress: Cognitive changes in ill-structured complex problem-solving contexts. Educational Technology Research and Development, 60 (4), 601–622.

Kim, M. C., & Hannafin, M. J. (2011). Scaffolding problem solving in technology-enhanced learning environments (TELEs): Bridging research and theory with practice. Computers & Education, 56 (2), 403–417.

Klegeris, K., Bahniwal, M., & Hurren, H. (2013). Improvement in generic problem-solving abilities of students by use of tutor-less problem-based learning in a large classroom setting. CBE Life Sciences Education, 12, 70–73.

Lee, C. B. (2010). The interactions between problem solving and conceptual change: System dynamic modeling as a platform for learning. Computers & Education, 55 (3), 1145–1158.

Matemba, C. K., Awinja, J., & Otieno, K. O. (2014). Relationship between problem solving approaches and academic performance: A case of Kakamega municipality, Kenya. International Journal of Human Resource Studies, 4 (4), 10.

McCormick, N. J., Clark, L. M., & Raines, J. M. (2015). Engaging students in critical thinking and problem solving: A brief review of the literature. Journal of Studies in Education , 5 (4), 100–113.

Muna, K., Sanjaya, R. E., Syahmani, & Bakti, I. (2017). Metacognitive skills and students’ motivation toward chemical equilibrium problem solving ability: A correlational study on students of XI IPA SMAN 2 Banjarmasin. In AIP Conference Proceedings (Vol. 1911, No. 1, p. 020008). AIP Publishing.

Newell, A., & Rosenbloom, P. (1981). Mechanisms of skill acquisition and the law of practice. In J. R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 1–55). Hillsdale, NJ: Lawrence Erlbaum Associates.

Nokes, T. J., Schunn, C. D., & Chi, M. T. H. (2010). Problem solving and human expertise. In International encyclopedia of education (pp. 265–272). Elsevier Ltd. https://doi.org/10.1016/b978-0-08-044894-7.00486-3 .

Raes, A., Schellens, T., Wever, B. D., & Vanderhoven, E. (2012). Scaffolding information problem solving in web-based collaborative inquiry learning. Computers & Education, 59 (1), 82–94.

Renkl, A., & Atkinson, R. K. (2007). Cognitive skill acquisition: Ordering instructional events in example-based learning. In F. E. Ritter, J. Nerb, E. Lehtinen, & T. O’Shea (Eds.), In order to learn: How ordering effect in machine learning illuminate human learning and vice versa . Oxford: Oxford University Press.

Robertson, I. S. (2016). Problem solving: Perspectives from cognition and neuroscience (2nd ed.). Hove: Psychology Press.

Book   Google Scholar  

Salden, R., Aleve, V., Schwonke, R., & Renkl, A. (2010). The expertise reversal effect and worked examples in tutored problem solving. Instructional Science, 38, 289–307.

Säljö, R., & Wyndhamn, J. (1990). Problem-solving, academic performance and situated reasoning. A study of joint cognitive activity in the formal setting. British Journal of Educational Psychology, 60 (3), 245–254.

Shute, V., Wang, L., Greiff, S., Zhao, W., & Moore, G. (2016). Measuring problem solving skills via stealth assessment in an engaging video game. Computers in Human Behavior, 63, 106–117.

Van Merriënboer, J. J. G. (1997). Training complex cognitive skills . Englewood Cliffs, NJ: Educational Technology Publications.

Van Merriënboer, J. J. G. (2013). Perspectives on problem solving and instruction. Computers & Education, 64 (1), 153–160.

Van Merriënboer, J. J. G. (2016). How people learn. In N. Rushby & D. W. Surry (Eds.), The Wiley handbook of learning technology (pp. 15–34). West Sussex: Wiley.

Van Merriënboer, J. J. G., & Bruin, A. B. H. (2013). Research paradigms and perspectives on learning. In J. M. Spector, et al. (Eds.), Handbook of research on educational communications and technology (pp. 21–29). New York: Springer.

Van Merriënboer, J. J. G., Clark, R. E., & Croock, M. B. M. (2002). Blueprints for complex learning: The 4C/ID-model. Educational Technology Research and Development, 50 (2), 39–64.

Yu, K., Fan, S., & Lin, K. (2014). Enhancing students’ problem-solving skills through context-based learning. International Journal of Science and Mathematics Education, 13, 1377–1401.

Download references

Author information

Authors and affiliations.

Department of Workforce Education and Development, Southern Illinois University Carbondale, 475 Clocktower Drive #4605, Carbondale, IL, 62901, USA

School of Information Science & Learning Technologies, University of Missouri Columbia, 221H Townsend Hall, Columbia, MO, 65211, USA

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Lin Zhong .

Ethics declarations

Conflict of interest.

The authors declare that they have no conflict of interest.

Additional information

Publisher's note.

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

Learning readiness survey

For each of the following questions and statements, please rate yourself for each item. Mark the number that best reflects your situation.

Situational design of lesson 4

Learning goal Improve information visualization skills by demonstrating effective interactive image editing skills for specific purposes by using Thinglink.

Recurrent skills

Basic understanding of information visualization by using images;

Basic understanding of interactive images;

Basic image editing skills.

Non-recurrent skills

Decision-making skills to determine the purpose of the image;

Monitoring skills to ensure task completion;

Comparing and evaluation skills to ensure the quality of the newly created image;

Procedural learning activities Create interactive images by using Thinglink.

HP—create at least three interactive images by using Thinglink.

LP—create one interactive image by using Thinglink.

Supportive learning activities Consider the purpose of the images.

HS—pick up a purpose (educational, commercial, personal) and improve the image quality to achieve that purpose.

LS—consider how to create images for educational purpose.

Relationship activities

HR-interaction with students is mainly two-way communication. For example, relationship activities can focus on reviewing whether the image achieves the chosen purpose or not, checking the quality of the images, providing guidance for further improvement, keeping check emotional level, reducing the fear of making mistakes, and avoiding overwhelming.

LR-interaction with students is mainly one-way communication. For example, relationship activities can focus on clarifying task requirements, checking task completion, making sure all the given tasks are completed and providing step-by-step assistance when necessary.

Rights and permissions

Reprints and permissions

About this article

Zhong, L., Xu, X. Developing real life problem-solving skills through situational design: a pilot study. Education Tech Research Dev 67 , 1529–1545 (2019). https://doi.org/10.1007/s11423-019-09691-2

Download citation

Published : 09 July 2019

Issue Date : December 2019

DOI : https://doi.org/10.1007/s11423-019-09691-2

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

• Problem-solving skills
• Individual differences
• Learning readiness
• Situational design
• Find a journal
• Publish with us
• Track your research

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Download Free PDF

THE PROBLEM SOLVING SKILLS OF GRADE 11 STUDENTS IN

Free related PDFs Related papers

Dissertation - Florida International University, 2016

With evidence that arts engagement and nonlinear thinking style both utilize insight, intuition, and emotion in the decision making process, the literature has driven an investigation of the relationship between levels of arts engagement and thinking style preference. This nonexperimental correlational study (N = 101) explored (a) the prevalence of linear, nonlinear, or balanced linear/nonlinear thinking style of professionals working in museums. (b) Whether thinking style has a relationship with (i) age; (ii) sex; (iii) academic major; (iv) occupation; (v) levels of arts engagement. Two theoretical frameworks underpinned this study: (a) new literacies and (b) cognitive styles. A Web-based self-report survey instrument was used to investigate the relation among the variables of interest. Existing literature was used to provide a foundation for the study and guide the research. Correlational, means, and hierarchical regression analysis were used to test the hypothesized model and examine the hypotheses. The means analyses at the descriptive level revealed that females, those in the 60 or older age group, Humanities majors, and those who worked in education demonstrated more balanced linear/nonlinear thinking styles. The correlations results indicated that there was a statistically significant relationship between thinking style and sex and thinking styles and academic major. The hierarchical regression results suggested that after controlling for select demographic variables, only being a Humanities major uniquely predicted significant variance in thinking style. The lack of significant findings of a relationship between thinking style and age did not correspond to existing research that supports a correlation. Additionally, a significant relationship between thinking style and levels of arts engagement was not found during correlational and hierarchical regression analysis. A limitation of this research study was that the Web-based self-report survey version of the Linear/Nonlinear Thinking Style Profile (LNTSP) instrument did not transfer well to online use because the participants had some problem understanding how to score their answers properly. This issue could be handled readily and recommendations are made to revise the Web-base self-report version of the survey for future research use.

“Human beings differ from one another and there is absolutely no reason to teach and assess all individual in the identical way”. - Dr. Howard Gardner Keeping this in mind, the Multiple Intelligence Theory has paved its way to the teaching process to treat individual differences seriously. The Multiple-Intelligence (MI) theory primarily listed seven intelligences which come and work together: verbal-linguistic, logical-mathematical, interpersonal, intrapersonal, visual-spatial, bodily-kinesthetic and musical/rhythmic. Eventually, he added the naturalist intelligence, the existential intelligence, and the so-called “pedagogical intelligence”. His theory became highly popular with K-12 educators around the world who seeks ways in reaching their students until trying a different approach. Because of these kinds of experiences, the idea of learning styles and multiple intelligences reverberate with many educators. As pointed out by Fliess (2009), Gardner developed the multiple intelligences on 1983 to help educators, psychologists and parenting experts better understand how children process and learn information. While in the excerpt written by Westerberg (2012), Gardner directly says that multiple intelligences are not a statement about learning styles. In addition, he emphasized that Gardner himself describe learning style as an “incoherent hypothesis”. However, either of the two is still learning theory until now. The use of MI and LS, based on most educational researchers, have many benefits in the field of teaching and learning process. On the other hand, McLeod (2010) explore the idea about learning styles regarding with “Kolb-Learning Style Theory”. He found out that both learning stages and cycle present by Kolb could be used by teachers to critically evaluate the learning provision typically available to students, and develop more appropriate learning opportunities. While Liston (2009)in her study about Different Learning styles in mathematics teaching, have found out that conceptions of mathematics open a window to students understanding of mathematics. Students’ view of mathematics affects the quality of the students understanding and learning outcomes. Teachers’ conceptions of mathematics are perhaps most important for the future of mathematics education, since it is these very conceptions that influence teachers’ approaches to teaching and bring about change in the mathematics classroom. In seeking for applicable learning opportunities, many teachers are challenged in their teaching stint. In spite of their cautious preparation in their lesson planning and the use of all sorts of learning aids, the dilemma of academic performance is still on the line, which is commonly the measure of classroom learning. As emphasized by Bruke& Dunn (2006), classroom teachers and educators are aware that each student learns differently. Through education classes and constant discussion, educators are aware that by identifying each student learning style, teaching to his or her learning style and implementing curriculum that compliments student learning can improve on-task behavior and increase content knowledge. The thought of identifying each student learning style may seem impossible and time consuming. However, with the right instrument, that is quick and effective, the process will be much more approachable. A pressure has been placed on teachers to increase students’ grades on academic achievement test. The researchers know that teaching to a students’ learning style will improve scores. The researchers tend to explore on how the multiple-intelligence and the learning styles affects the academic performance of the students specifically in Mathematics. The academic performance of school reflects the academic achievement of the learner’s as the purpose of the National Achievement Test imposed by the Department of Education. As lectured by Benito (2010), NAT, is a Philippine ‐made standardized test designed to determine pupils/students’ achievement level, strengths and weaknesses in five key curricular subject areas at the end of the school year. The result of the National Achievement Test is chosen as a basis of the school’s academic performance. The schools served as samples are the ones where the researchers are taking their field study. Table1 NAT results 2011-2014 (School Ranking in Mathematics) School 2011-2012 2012-2013 2013-2014 Rank MPS Rank MPS Rank MPS Justice Emilio Angeles Gancayco Memorial National High School 17th 59.13 30th 32.03 11th 53.52 LimayNational High School 13th 65.78 18th 46.8 22nd 42.45 Lamao National High School 14th 63.83 10th 61.88 17th 44.28 Mariveles National High School (Cabcaben) 18th 40.3 17th 48.22 15th 47. 24 As the preceding table shows, Limay National High School has shown a decline in the NAT ranking in the past three years when it regards to its performance in Mathematics. In fact, in the recent NAT results, it ranked lowest among the four schools. Because of this, the researchers chose Limay National High School, as the research local. In reality, majority of Math classes consist of a teacher-led lesson, directed at the whole class, followed by individual practice (e.g. board works, drills) and sometimes group-activity reinforcement. It is mainly because Mathematics deals solely with concepts and theories. As the course of classroom learning shifted its gears to progressive classroom, the monotony of classroom instruction in Mathematics is ceased. From the teacher-centered instruction, students’ diversity is also taken into consideration. Gardner’s Multiple Intelligence Theory can greatly help teachers to revolutionize the classroom instruction. On the other hand, Loori (2005) tackles the differences of intelligence preferences according to gender. Males preferred learning activities involving logic and mathematical intelligences, whereas females preferred learning activities involving intrapersonal intelligence. The comparative study between the genders regarding with the differences of intelligences reflects that either male or female, multiple intelligences and learning styles should not incorporate in identical way. It is fair and functional if all individuals perform on its domain rather than be traditionally tested in general intelligence. This would bring the chances of every individual on its field of inclination, expertise and actual intelligence. In addition to the use of MI-based instruction and how it affects the preferred learning styles of students, Orog (2012) states that student with musical inclination are doing a well-coordinated skill level with that of tactile-kinesthetic group of learners, or the presence of both intelligences to the same group of students. This information only reveals that a musically inclined learner is almost have the same level of learning style with tactile-kinesthetic learners as the performance-based assessment, in accordance to Orogs’ study, affirms the correlation to each other. There are many ways to incorporate MI and learning style theory in the curriculum, and there is no set method by which to incorporate these theories. The proponents of this study have been entering the world of field study required in their profession for almost 3 years. It can be typically observed that some students, despite of attending and sitting inside the classroom, are still deprived of learning since, the gap of the teaching style and learning style was not narrowed down. Most of the teachers, specifically mathematics educators, do not incorporate the theories about multiple intelligences and learning styles in classroom instruction. Adding the fact, that it narrows the measurement of academic performance to test scores. Hence, students do not receive the learning they need to acquire, disrupting the utilization of their true potentials. This research may help the teachers to consider incorporating MI and learning styles in the field of instructing mathematics. The primary goal of this research is to help math teachers realize that they should know more about the two concepts, assess the students’ learning styles as soon as possible in order to help students develop their different intelligence factors in a way which is conducive to their individual learning styles. As a result, when these important aspects are understood and acted upon, teaching strategies will become more efficient and effective and learning becomes more enjoyable for students who find difficulties in the traditional classrooms. Consequently, the diversity of students, due to various learning styles and multiple intelligences, can be more appreciated and its implication with the students’ academic performance can be used as a guideline to improve the classroom instruction in Mathematics, as the researchers want to address. All in all, this research aims to initiate change, to the educational system, in order to produce globally-competitive, productive, and life-long learners with the inclusion of MI and LS in the teaching-learning process.

The purpose of this study was to determine the effects of instructional strategies on teacher self-efficacy beliefs about teaching mathematics to more fully understand the relationship between the two groups, and two determine what factors, if any, improve mathematics teaching self- efficacy bThe findings revealed that respondents’ perceived ability to provide feedback and clarification, as well as accommodating individual student needs, were the two principal factors which explain the variance in teacher’s self- efficacy beliefs. These two factors themselves are influenced by the teachers’ understanding mathematical concepts. From the data gathered in this study, we can conclude although teachers may welcome student questions, they do not always feel confident in their ability to answer these questions sufficiently. The data also revealed that overall, teachers lack confidence in their performance in front of superiors, their ability to get students interested in mathematics, as well as their ability to increase student retention. The instructional practices of the respondents were more traditional, and teacher- centric; the data revealed that this was related to underlying beliefs about mathematics instruction as well as the respondents’ perceived understanding of mathematical concepts.

… International Seminar and the Fourth National …, 2011

ABSTRACT Mathematics education experts elaborate that motivational, meta-cognitive, and behavioral processes are as important as cognitive processes of students’ mathematics learning. These processes embodied the students’ self-regulated learning. Hence, this study looked into the self-regulated learning strategies, multiple intelligences, and academic mathematics performance of high and low self-regulated learners. The respondents of the study were grade 10 students comprised of fifteen (15) high self-regulated and fifteen (15) low self-regulated learners of Bulak National High School, in the Cebu Province Division for school year 2016- 2017. A qualitative method was used to delve into the different self-regulated strategies of high and low self-regulated learners. A Pearson Correlation using SPSS 23.0 also unravel the significant correlation between high level of academic self-regulation and logical/ mathematical intelligence, as well as the academic mathematics performance. It was found out that students with high self-regulation utilized higher frequencies of self-regulation strategies compared to their low self-regulated peers. The learners’ high level of self- regulation has also significant relationship with logical/ mathematical intelligence, and high academic performance in mathematics. Thus, high self-regulated learners have used powerful self-regulated strategies in regulating their learning to attain high academic mathematics performance. These strategies involve Meta-cognitive (Self- Evaluation), Motivational (Goal Setting and Planning, Rehearsing and Memorizing, Organizing and Transforming), and Behavioral (Environmental and Structuring) processes of self-regulated learning. Key words: Self- regulated learning strategies, multiple intelligences, academic math performance, Self-regulation

Division of facilities and infrastructures at Trilogi University in Jakarta important role in the smooth implementation of the teaching. Services provided in a campus environment, among others, is to provide the needs of printers among office equipment, paper, pens folders, and so forth. Car lending services office for employees who want to perform office tasks, in addition to providing services to students in rental lockers or classrooms that will be used the meeting. Division advice and infrastructures receive complaints from students or Lecturer who feel uncomfortable because infocus less functioning well, ac not cold, leakage, breakage bench, damage to the table and so on. The services provided to the general public who want to hire in the atrium or auditorium that will be in use as a wedding or a seminar. In providing services to students, faculty, staff within the Trilogi University as well as people outside the campus still done manually, for example when receiving orders and leasing of office equipment lockers are still recorded on paper. Vehicle rental and atrium room or auditorium writing done on the board. By looking at these conditions, the author makes a concept of information system for the division of facilities and infrastructures by using Cardinalities Mapping Keywords : Cardinalities Mapping

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

Mathematical Thinking and Learning, 2006

ICLEHI 2015, 2015

Asia Pacific Journal of Education, Arts and Sciences, 2018

Conference on Learning and Teaching, 2002

Studies in Higher Education

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

• Open access
• Published: 05 February 2018

The role of problem solving ability on innovative behavior and opportunity recognition in university students

• Ji Young Kim 1 ,
• Dae Soo Choi 1 ,
• Chang-Soo Sung 1 &
• Joo Y. Park 2  

Journal of Open Innovation: Technology, Market, and Complexity volume  4 , Article number:  4 ( 2018 ) Cite this article

25k Accesses

31 Citations

1 Altmetric

Metrics details

Universities engage in entrepreneurship education to increase social value creation, through students’ new opportunities recognition. However, there are not enough of empirical researches on whether the current entrepreneurship education can be differentiated from other curriculum to improve the opportunity recognition process. This study argues that it is very important for cognitive abilities to be manifested as behavior when students in university are new opportunities recognition. For this purpose, the relationship between problem solving ability, innovation behavior, and opportunity perception was verified empirically. This study was conducted on 203 students who took entrepreneurship education courses at Korean universities. The results of this study showed that problem solving ability positively influenced innovation behavior and opportunity perception. Innovation behavior was identified as a key parameter that partially mediated the relationship between problem solving ability and innovation behavior. The implication of this study is to prove the relationship between individual ‘s problem - solving ability considering the characteristics of education in Korea and the opportunity through innovative behavior and various learning strategies to help entrepreneurship education to design better courses for the future It has important implications for strategic pedagogy that can enhance behavioral elements in development.

It is the new opportunity recognition that all firms focus on for a new economic paradigm (Ancona and Caldwell, 1992 ). Recognizing high opportunities can significantly improve profit, growth, and / or competitive positioning. And this new opportunity leads to innovation. From a conceptual point of view, research is continuing on the question of ‘what is opportunity’ and ‘where is opportunity’ (Gartner and Carter, 2003 ; Venkataraman & Sarasvathy, 2001 ). Research on the discovery and realization of new opportunities is a very important research area that suggests how to discover and utilize creative opportunities that create new value and profit for pre-service workers, and is the ultimate goal of entrepreneurship education. (Kim et al., 2016 ). Particularly, there is a lot of debate about the relationship between opportunity perception and personal characteristics. Despite many arguments, however, research on individual characteristics and opportunity perceptions is still insufficient, and a unified opinion has not been created due to differences between cognitive and behavioral theories (Ko & Butler, 2003 ). In particular, there is much controversy over the relationship between opportunity recognition and personal traits, and research has been continuing to demonstrate that organizational learning in organizations can influence opportunity recognition (Shane & Venkataraman, 2000 ). In particular, learning enhances cognitive ability, which is an opportunity that leads to opportunity recognition through the manifestation of behavior (Lumpkin and Dess, 2004 ). Many studies have also demonstrated the difference in behavior that successful entrepreneurs see as contributing to their ability to recognize opportunities and create innovative business ideas (Dyer et al., 2008 ; Kim et al., 2017 ). For example, Alvarez and Barney ( 2005 ) argue for mountain climbing and mountain building to understand the implications of entrepreneurial behavior in relation to these theories. In other words, a new opportunity for entrepreneurs is not a passive case that is generally found and climbed by climbers such as mountains, but rather by the actions of entrepreneurs, creating competition for the market, creating another market, Is the same. Therefore, in order for a person’s cognitive ability to recognize a new opportunity, it must focus on manifesting an action that can realize an innovative idea. In this regard, Kanter ( 1988 ) proved the relationship between new opportunity recognition and those with innovative tendencies and regarded this new opportunity recognition as innovation activity through organizational education. Scott and Bruce ( 1994 ) have integrated a number of research flows into innovation pioneers to develop and test individual innovative behavioral models. In particular, they argued that individual problem-solving styles are very important to induce innovative behavior. Although there are a number of studies on problem solving ability, innovation behavior, and new opportunities, most of the opportunistic researches have been conducted in organizational units of companies. Is still insufficient. Furthermore, unified opinions were not created due to differences between cognitive theory and behavioral theory (Ko & Butler, 2003 ). It is also true that the effects of entrepreneurship education in university have not been studied empirically because they are mainly focused on promoting cognitive ability and applied to various kinds of teaching methods.

This study argues that it is very important for cognitive abilities to be manifested as behavior that. “Through” courses, In other words, it is very important to induce students to act through ‘learning through process’ learning through behavioral learning by providing students with some (virtual or real) business to start doing some of the actions of the entrepreneur. When students in university are new opportunity recognition. Especially, entrepreneurship education, which ultimately focuses on whether it is a new opportunity, is very important to induce behavior through behavior learning beyond the cognitive ability as the general education curriculum. Particularly, innovative behaviors that create and realize innovative ideas are very important for new opportunity recognition (Paine & Organ, 2000 ).In order to achieve this, various kinds of teaching methods are being pursued in the university, but studies on the effectiveness of behavioral learning have not been studied yet. In this study, we are based on team-based learning among various teaching methods for behavior learning that leads to innovative behaviors. Team learning instructional activity sequence designed by Michaelsen and Sweet ( 2008 ), the most well known team-based learning in entrepreneurship education as in class-primarily group work and outside class-primarily individual work. In this way, we demonstrate empirically the relationship between individual problem solving ability and opportunity through innovative behavior, and develop a variety of learning strategies that help entrepreneurship education to design better courses for the future. I would like to point out some implications for strategic pedagogy to increase the element.

The paper proceeds as follows: Initially we present the theory of innovative behavior with individual problem-solving ability, innovative behavior and opportunity recognition. We develop hypotheses to confirm its basic predictions in the student context. Finally, we link the findings with the wider social effect of entrepreneurship literature and highlight the theoretical contributions and practical implications.

Theoretical background

‘opportunity recognition’ as entrepreneurship education unit of analysis.

A commonly focused analysis in entrepreneurship research over the last 30 years has been the ‘opportunity’, most simply defined as any situation in which new products or services can be development of production (Casson, 1982 ; Shane & Venkataraman, 2000 ; Venkataraman, 1997 ). The definition of opportunity recognition is defined in many ways, but opportunity is defined as a perceived means of generating economic value (ie, profit) that has not been exploited previously and is not currently exploited by others. If opportunity is defined in this way, opportunity recognition can be defined as a cognitive process (or process) that concludes that an individual has identified an opportunity (Baron and Ensley, 2006 ). Kirzner ( 1997 ) pointed out that the distribution of information in society affects the discovery of entrepreneurial opportunities and that only a few individuals can identify and recognize specific opportunities in the market. The process of finding opportunities also depends on the individual’s ability and discovery (Stevenson & Gumpert, 1985 ). For example, people may miss opportunities due to a lack of cognitive ability to change external environments (Stevenson & Gumpert, 1985 ). Only those who recognize and value the existence of opportunity can benefit from new opportunities (Ardichvili et al., 2003a , b ; Shane & Venkataraman, 2000 ). Opportunity recognition is an early step in transforming value into a business concept that creates value and generates revenue and distinguishes it from the aggressive stages of detailed assessment and development of recognized opportunities and potential economic value. The focus of the new venture business is also an innovative opportunity to create new opportunities rather than merely expanding or repeating existing business models (Gaglio & Katz, 2001 ). As a result, universities need to make use of a variety of initiatives to educate students to recognize innovative opportunities. Therefore, entrepreneurship education aimed at a new opportunity recognition should be able to provide learning opportunities based on various theories of favorable conditions for new business creation and the types of traits required for new ventures (Garavan & O’Cinne’ide, 1994 ).

Based on these considerations, we also define opportunity recognition as the formation of beliefs that can be translated into actions in order to understand the signals of change (new information on new conditions) and respond to these changes.

Problem-solving ability and innovative behavior of education for students

Problem-solving abilities have been proven to be one of the key factors for success in organizations and personal careers (Anderson & Anderson 1995 ). Through decades of research data, organizations and schools have studied factors that affect improvement. Problem-solving abilities are defined in a number of prior studies, and problem-solving abilities in a volatile and sophisticated knowledge- and technology-based industry are an important ability to drive innovation and sustainable growth and development in the industry. Table  1 show the concept of problem solving ability defined in previous research.

There have been a number of previous studies, emphasis has been placed on the importance and meaning of rational problem-solving processes in order to improve problem-solving abilities, and research has focused on individual problem solving styles (Woodman et al., 1993 ; Scott & Bruce, 1994 ). According to the personal innovation behavior model of Scott and Bruce ( 1994 ), climate has shown individual innovative behavior as a result of individuals signaling the organization’s expectations of behavior and the potential consequences of action. Innovative organizations are, last but not least, equipment, facilities and time, including the direction of creativity and innovative change (Kanter, 1983 ; Siegel & Kaemmerer, 1978 ) Proper supply of such resources is important to innovation (Amabile, 1988 ; Van de Ven & Angle, 1989 ; Dubickis & Gaile-Sarkane, 2017 ). Based on a study of Koestler’s ( 1964 ) creative thinking, Jabri conceptualized a problem-solving style consisting of two independent thinking styles. He uses a structured problem-solving styles that is based on associative thinking, follows a set of rules, resolves reasonably logically, and uses an intuitive problem-solving ability that focuses on problem-solving, not tied to existing rules with multiple ideas. Intuitive problem solving styles tend to process information from different paradigms simultaneously. It is therefore more likely to create new problem solutions as possible (Isaksen, 1987 ; Kirton, 1976 ). However, style assessment is not desirable because the style of problem solving affects style differently depending on the individual problem-solving situations (Scott & Bruce, 1994 ). We are proposing a role for the University to encourage innovative behavior based on the individuality of our students in order to recognize new opportunities through education about Scott and Bruce’s innovative behavioral models and diverse entrepreneurship education approaches. And involvement of resources, such as entrepreneurship awareness programs, ultimately leads to the identification of individual characteristics and innovation. In addition, current Korean entrepreneurship education is mainly focused on cognitive learning to improve problem solving ability, and one aspect of cognitive learning plays an important role in learning process of new venture firms. This study has a more direct focus on behavior learning such as team-based learning.

Hypothesis development

Problem-solving ability and innovative behavior.

Problem solving is to discover knowledge and skills that reach the target country by interfering with a set of processes and goals where the solution is unknown, unfamiliar, or reaching a new state of goal (Jonassen, 2004 ; Inkinen, 2015 ). There are various approaches to solve this problem. To solve problems and improve problem solving with a successful solution experience, you should adopt the method that best suits your problem solution. You need to select the appropriate inputs for the solution elements and a flexible process structure. Problem solving ability has been recognized as a key element of innovative behavior in responding to rapid changes with the ability to find various alternatives and predict outcomes from these alternatives to maximize positive results, minimize negative consequences, and select solutions to problems (Barron & Harrington, 1981 ; Jabri, 1991 ; Kirton, 1976 ). We pose the following hypotheses:

Hypothesis 1: Individual problem-solving ability has an effect on the innovative behavior of students.

Innovative behavior and opportunity recognition

Innovation involves introducing ideas from outside the organization, through creative processes, and linking these ideas to products or processes. Many scholars studying innovation recognize that designing ideas is only one step in the innovation process (Kanter, 1988 ). Innovation is changing at the organizational or individual level. Kanter, Scott and Bruce defined personal innovation. In other words, an innovation act starts with recognition of a problem, adoption of a new idea, or creation of a solution, and an individual with an innovative tendency wants to create a realistically realizable group with the sympathy of such an idea. Innovative individuals create prototypes for innovations that enable ideas to be realized specifically with goods or services and become productive use and social day merchandising. According to previous studies, opportunity perception can be seen as an individual’s corporate strategy that focuses on the perception and exploitation of individuals about potential business ideas and opportunities and finds resources to create innovative outcomes (Manev et al., 2005 ). New Venture Ideas (NVI) are imaginary combinations of product/service offerings; potential markets or users, and means of bringing these offerings into existence (Davidsson, 2015 ). From the viewpoint of a potential entrepreneur like a university student, entrepreneurship starts with an idea. This process continues with a range of practices including attractiveness and feasibility of an idea, gathering information to minimize value-related uncertainty and possibility and perhaps the main idea’s conformity ratio in terms of newly discovered needs (Hayton & Cholakova, 2012 ). Earlier we proposed that the program as a whole increases the students’ innovative behavior and that innovative performance is the new venture ideas. Since it is logical to assume that the relationship between innovative behavior and opportunity recognition. We pose the following hypotheses:

Hypothesis 2: Innovative behavior will be a more potent inducer of opportunity recognition.

Problem-solving ability and opportunity recognition

Among the many factors influencing opportunity perception, the problems that arise in the fourth industry, the knowledge-based industry of the twenty-first century, are unpredictable and unstructured; they cannot be solved with existing solutions and require creative problem-solving skills. In order to determine how to solve problem situations that are different from the current situation and have unknown results, problems are solved through the process of adjusting previous experience, knowledge, and intuition (Charles & Lester, 1982 ). Experience, knowledge, and intuition are applied simultaneously to a single problem, not individually or collectively, and the intellectual and creative results that can be quickly and effectively solved in problem solving are seen as problem solving abilities (Ardichvili et al., 2003a , b ). Empirical studies of problem-solving abilities and opportunity perceptions have provided strong evidence that there is a positive relationship between theoretical integrative processes and corporate opportunity recognition (Ucbasaran et al., 2009 ). Therefore, we hypothesized that:

Hypothesis 3: Problem solving ability has an effect on the opportunity recognition.

The respondents for this study were randomly selected from three universities in Korea. Most of the respondents in this study were Korean university students who experienced team-based learning during behavioral learning through entrepreneurship education. Since then, we have been guided by two main criteria when choosing these universities. First, students who take entrepreneurship courses are critical to their innovation behavior. This led us to realize that innovative behavior is an important factor in an individual’s survival and growth. The second is that the parallel process of theoretical and behavioral learning is highly satisfied. A pilot study was conducted to verify the reliability and validity of the research measurements with 28 students at a university. The results of the pilot study showed high clarity and reliability (Cronbach ‘s alphas were all above 0.70) ​​of the research measurements. The sample of the pilot study was not incorporated in the present study.

This study was conducted in a four - year undergraduate course (various majors) that took entrepreneurship courses in Korea university programs. Students in this course have a mix of students who have previously experienced entrepreneurship and those who have not. During the course, students were taught the theoretical lessons for 8 weeks and the team for the 8 weeks. The questionnaire was administered during the last week of the course.

The data were analyzed from 203 participants, out of a total of 209, of which 7 were not appropriate. Of the 203 participants, 27% were female and 73% were male and the grade distribution was 3% for freshmen, 12% for grade 2, 26% for grade 2, and 59% for grade 2. The main distribution is 26% in social science, 16% in business and economics, 39% in engineering, 11% in music and athletics and 7% in others (see Table  2 ).

Measurement

The structure of the model was measured by questionnaires (problem-solving ability, innovation behavior and opportunity recognition questionnaire) consisting of the scale taken from questionnaires verified in previous studies. Tool selection was performed on two criteria. First, the selected tool should measure the same structure (ie, the original measured structure had to be conceptually identical to the way the structure was defined in this study model). Secondly, the psychometric qualities of the instrument for the student had to be high.

Assessment of the factors was carried out through principal component analyses (varimax rotation with eigenvalues of 1.0 or above) of the scales connected to the same level of the model to confirm the uniqueness of the scales with respect to each other. This was supplemented by the computation of the internal consistency reliability of the scales (Cronbach’s α). These analyses were executed using the individual participants’ responses (Nunnally & Bernstein, 1994 ).

Problem- solving ability was measured on a 7-point Likert-scale (1 = ‘completely disagree’; 7 = ‘completely agree’). Jabri ( 1991 ) used a measurement tool to measure individual problem solving ability.

Innovative behavior was measured on a 7-point Likert-scale (1 = ‘completely disagree’; 7 = ‘completely agree’). In order to measure innovation behavior, we modified the questionnaire items to fit the intention of this study among the questionnaire items used by Scott and Bruce ( 1994 ) and Kim and Rho ( 2010 ).

Opportunity recognition was measured on a 7-point Likert-scale (1 = ‘completely disagree’; 7 = ‘completely agree’). In order to measure opportunity recognition, we modified the questionnaire items to fit the intention of this study among the questionnaire items used by Kim and Rho ( 2010 ).

Methods of analysis

The first two parts of the analysis were primarily based on (multiple) regression analyses. The last part of the analysis was informed through the path analyses. The adequacy of the models was assessed by AMOS 18(Arbuckle & Wothke, 2003 ). Models were all tested with standardized coefficients obtained from the Principal Component Analysis. To ascertain the model fit, we analyzed the comparative fit index (CFI), the normed fit index (NFI), the Root Mean Square Err of Approximation (RMSEA), the standardized root mean square residual (SRMR) and the chi-square test statistic.

Reliability and validity are essential psychometrics to be reported. The first step to evaluate those aspects was to use the Cronbach’s alpha and the composite reliability to test reliability of the proposed scales. The usual threshold level is 0.7 for newly developed measures (Fornell and Larcker, 1981 ). Values range from 0.69 to 0.79 in the case of Cronbach’s alpha, and from 0.85 to 0.92 in the case of composite reliability (see Table  3 ). Therefore, these scales may be considered as reliable. Next, we estimated the research model, displayed in Fig.  1 , using structural equation modeling (SEM) and AMOS 18 (Arbuckle & Wothke, 2003 ). Our analysis revealed an adequate measurement model with high factor loadings for all the items on the expected factors and communalities of each item exceeding 0.50. We discuss three fit indices that are generally considered as important (Hu & Bentler, 1998 ). First, the CFI-value represents the overall difference between observed and predicted correlations. A value of 0.04 which is situated well below the cut-off value of 0.08, suggests that the hypothesized model resembles the actual correlations. Secondly, Bentler’s CFI (comparative fit index) greater than 0.90 and 0.95 which is above the cut-off of 0.90 (Schumacker & Lomax, 1996 ). Thirdly, NFI greater greater than 0.90 and 0.95 which is above the cut-off of 0.90 (Schumacker & Lomax, 1996 ). Fourthly, the standardized root mean square residual (SRMR) value of 0.0392 which is situated well below the cut-off value of 0.05(Hu & Bentler, 1998 ), and the chi-square value of 3581.622 which is situated well below the cut-off value of 0.0005. Finally, the RMSEA (root mean square error of approximation) equals 0.04 with a 90% confidence interval between 0.03 and 0.05.

Analysis of mediation effect

The value and confidence interval are situated over but below the cut-off value of 0.1 which suggests not a great but a good fit. Factor analysis was verified by factor analysis using principal component analysis and only factors with an eigenvalue of 1 or more by orthogonal rotation method were selected. Factor loading was considered to be significant at 0.5 or more (Hair et al., 2006a , b ). As a result of the analysis, cumulative explanation for 72.4% of the total variance. Confirmatory factor analysis thus supported the differentiation of the three components Also we tested the confirmatory validity of the construct by testing whether the structural linkage of each square is greater than the mean variance extraction (AVE) of each structure. The AVE ranged from 0.52 to 0.53, reaching the recommended level of .50 for both Fornell and Larcker ( 1981 ). Therefore, all constructs showed sufficient convergent validity (see Table 3 ).

As shown in Table  4 , the AVE value of each variable has a higher value than that of other factors. Therefore, the discriminant validity of the proposed model can be judged as appropriate.

Means, standard deviations, and correlations among the study variables are shown in Table  5 .

The mean scores for the conceptual model were as follows for problem-solving ability (MD. 5.20, SD.1.08), innovative behavior (MD.5.20, SD.1.03), and opportunity recognition (MD. 5.14, SD. 1.06) conditions. The means of problem-solving ability, innovative behavior, and opportunity recognition were high. Furthermore, those variables correlated positively with each other.

Figure  1 showed that all paths and their significance levels are presented in Table  6 . The path between the latent variables problem-solving ability and innovative behavior was significant (p, 0.001), consistent with Hypotheses 1. In addition, there was innovative behavior and opportunity recognition (p, 0.01), this result provide empirical support for Hypothesis 2.

H3 proposed that Problem-solving ability is positively related to opportunity recognition. The results of the correlation analysis: The coefficient of problem solving and opportunity perception weakened from .717 to .444, but it is still partly mediated because it is still significant (C. R  = 7.604 ***). This supports H3 (see Table 6 ).

In order to verify the significance of the indirect effect, the bootstrapping must be performed in AMOS, and the actual significance test should be identified using two-tailed significance. As a result, the significance of indirect effect is 0.04 ( p  < 0.05), which is statistically significant (see Table  7 ).

Discussion and conclusion

We have tried to demonstrate the effects of behavior and its significance by differentiating from the general curriculum emphasizing cognitive effects as a model of problem solving ability emerging as innovative behavior through opportunity of university entrepreneurship education.. This supports the premise that entrepreneurship education can improve opportunities or processes through behavioral learning. The results of this study support the role of entrepreneurship education in creating opportunities for innovative behavior and problem solving abilities. Entrepreneurship education should provide different types of learning for new opportunities and focus on what is manifested in behavior.

In addition, based on previous research, we propose whether the following contents are well followed and whether it is effective. First, the emergence of innovative behavior in problem-solving abilities increases as the cognitive diversity of students with diverse majors and diverse backgrounds increases. Second, the more entrepreneurial learning experiences, the greater the chance of new opportunities. Third, it is necessary to investigate students’ problem solving style and problem-solving ability first, and then a teaching strategy based on this combination of systematic and effective theory and practice is needed. Of course, as demonstrated by many studies, it may be easier to enhance the effectiveness of opportunity recognition through cognitive learning. This is because it emphasizes the achievement of knowledge and understanding with acquiring skills and competence. This process, however, is not enough for entrepreneurship education. However, we do not support full team-based behavioral learning in the class designed by Michaelsen and Sweet ( 2008 ). As with the results of this study, problem solving ability is positively related to opportunity perception directly. As previously demonstrated in previous studies, problem solving ability can be enhanced by cognitive learning (Anderson et al., 2001 ; Charles & Lester, 1982 ).

Therefore, it has been demonstrated that it is more efficient to balance a certain level of cognitive learning and behavior learning in consideration of the level of students in a course. Also this study satisfies the need for empirical research by Lumpkin and Lichtenstein ( 2005 ) and Robinson et al. ( 2016 ) and others. This will help to improve understanding of how entrepreneurship training is linked to various learning models and their effectiveness and to design better courses for the future. Finally, this study sought to provide an awareness of entrepreneurship education as the best curriculum for solutions that evolved into innovative behaviors that create new values and ultimately represent new opportunities. This study shows that it can positively influence the social effect of creating new value, that is, not only the cognitive effect of general pedagogy, but also the innovation behavior. By providing this awareness, we have laid the groundwork for empirical research on entrepreneurship education in order to create more opportunities for prospective students in education through education and to expand their capabilities.

Limitation and future research

Indeed, the concepts presented here and the limitations of this study have important implications that can fruitfully be addressed in future research. First, we selected a sample of college students taking entrepreneurship training. However, since it is not the whole of Korean university students, it is difficult to extend the research results to all college students in Korea. Second, there is no precedent research on the role of innovation behavior as intermedia in college students. Therefore, we were forced to proceed as an exploratory study.

The ability to recognize opportunities can provide significant benefits that can remain firm and competitive in an ever-changing environment. Future research should therefore expand these insights and try to empirically test more ways in which entrepreneurship pedagogy teaches how learning methods can be integrated into venture creation and growth processes to help new process opportunities. By providing this study, we will help entrepreneurship education in the university to create more opportunities and expand the capacity of prospective members.

Alvarez, S. A., & Barney, J. B. (2005). How do entrepreneurs organize firms under conditions of uncertainty? Journal of Management, 31 (5), 776–793.

Article   Google Scholar  

Amabile, T. M. (1988). A model of creativity and innovation in organizations. Research in Organizational Behavior, 10 (1), 123–167.

Google Scholar  

Ancona, D. G., & Caldwell, D. F. (1992). Demography and design: Predictors of new product team performance. Organization Science, 3 (3), 321–341.

Anderson, P. M., & Anderson, P. M. (1995). Analysis of faulted power systems (Vol. 445). New York: IEEE press.

Anderson, L. W., Krathwohl, D. R., Airasian, P., Cruikshank, K., Mayer, R., Pintrich, P., & Wittrock, M. (2001). A taxonomy for learning, teaching and assessing: A revision of Bloom’s taxonomy . New York: Longman Publishing.

Arbuckle, J. L., & Wothke, W. (2003). AMOS 5 user’s guide . Chicago: Smallwaters.

Ardichvili, A., Cardozo, R., & Ray, S. (2003a). A theory of entrepreneurial opportunity identification and development. Journal of Business Venturing, 18 (1), 105–123.

Ardichvili, A., Cardozo, R., & Ray, S. (2003b). A theory of entrepreneurial opportunity identification and development. Journal of Business Venturing, 18 (1), 105–123.

Baron, R. A., & Ensley, M. D. (2006). Opportunity recognition as the detection of meaningful patterns: Evidence from comparisons of novice and experienced entrepreneurs. Management Science, 52 (9), 1331–1344.

Barron, F., & Harrington, D. M. (1981). Creativity, intelligence, and personality. Annual review of psychology, 32 (1), 439–476.

Casson, M. (1982). The entrepreneur: An economic theory . Lanham: Rowman & Littlefield.

Charles, R., & Lester, F. (1982). Teaching problem solving: What, why & how . Palo Alto: Dale Seymour Publications.

Davidsson, P. (2015). Entrepreneurial opportunities and the entrepreneurship nexus: A re-conceptualization. Journal of Business Venturing, 30 (5), 674–695.

Dubickis, M., & Gaile-Sarkane, E. (2017). Transfer of know-how based on learning outcomes for development of open innovation. Journal of Open Innovation : Technology, market, and complexity , 3 (1), 4.

Dyer, J. H., Gregersen, H. B., & Christensen, C. (2008). Entrepreneur behaviors, opportunity recognition, and the origins of innovative ventures. Strategic Entrepreneurship Journal, 2 (4), 317–338.

D'zurilla, T. J., & Nezu, A. M. (1990). Development and preliminary evaluation of the social problem-solving inventory. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 2 (2), 156.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research , 39–50.

Gaglio, C. M., & Katz, J. A. (2001). The psychological basis of opportunity identification: Entrepreneurial alertness. Small Business Economics, 16 (2), 95–111.

Garavan, T. N., & O’Cinneide, B. (1994). Entrepreneurship education and training programmes: A review and evaluation-part 1. Journal of European Industrial Training, 18 (8), 3–12.

Gartner, W. B., & Carter, N. M. (2003). Entrepreneurial behavior and firm organizing processes. In Handbook of entrepreneurship research (pp. 195–221). New Mexico: Springer US.

Hair, E., Halle, T., Terry-Humen, E., Lavelle, B., & Calkins, J. (2006a). Children's school readiness in the ECLS-K: Predictions to academic, health, and social outcomes in first grade. Early Childhood Research Quarterly, 21 (4), 431–454.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006b). Multivariate Data Analysis (6th ed.). Upper Saddle River: Pearson Education, Inc..

Hayton, J. C., & Cholakova, M. (2012). The role of affect in the creation and intentional pursuit of entrepreneurial ideas. Entrepreneurship Theory and Practice, 36 (1), 41–68.

Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3 (4), 424.

Inkinen, T. (2015). Reflections on the innovative city: Examining three innovative locations in a knowledge bases framework. Journal of Open Innovation : Technolodgy, market. Complexity, 1 (1), 8.

Isaksen, S. G. (1987). Frontiers of creativity research: Beyond the basics. Bearly Ltd.

Jabri, M. M. (1991). The development of conceptually independent subscales in the measurement of modes of problem solving. Educational and Psychological Measurement, 51 (4), 975–983.

Jonassen, D. H. (2004). Learning to solve problems: An instructional design guide (Vol. 6). Hoboken: John Wiley & Sons.

Kanter, R. M. (1983). The change masters: Binnovation and entrepreneturship in the American corporation. Touchstone Book.

Kanter, R. M. (1988). Three tiers for innovation research. Communication Research, 15 (5), 509–523.

Kim, H. C., Song, C. H., & An, B. R. (2016). A study on effects of personal characteristics on start-up opportunity and entrepreneurial intention of start-up. Korean Management Consulting review, 16 (3), 75–87.

Kim, S. A., Ryoo, H. Y., & Ahn, H. J. (2017). Student customized creative education model based on open innovation. Journal of Open Innovation : Technology, Market, and Complexity , 3 (1), 6.

Kim, T. H., & Roh, J. H. (2010). A Study of the Impact of Public Service Motivation on Innovative Behavior of Organizational Members. Korean Journal of Public Administration, 48(3).

Kirton, M. (1976). Adaptors and innovators: A description and measure. Journal of Applied Psychology, 61 (5), 622.

Kirzner, I. M. (1997). Entrepreneurial discovery and the competitive market process: An Austrian approach. Journal of Economic Literature, 35 (1), 60–85.

Ko, S., & Butler, J. E. (2003). Alertness, bisociative thinking ability, and discovery of entrepreneurial opportunities in Asian hi-tech firms.

Koestler, A. (1964). The act of creation: A study of the conscious and unconscious processes of humor, scientific discovery and art.

Lumpkin, G. T., & Dess, G. G. (2004). E-Business Strategies and Internet Business Models: How the Internet Adds Value. Organizational Dynamics, 33 (2), 161–173.

Lumpkin, G. T., & Lichtenstein, B. B. (2005). The role of organizational learning in the opportunity-recognition process. Entrepreneurship Theory and Practice, 29 (4), 451–472.

Manev, I. M., Gyoshev, B. S., & Manolova, T. S. (2005). The role of human and social capital and entrepreneurial orientation for small business performance in a transitional economy. International Journal of Entrepreneurship and Innovation Management, 5 (3–4), 298–318.

Michaelsen, L. K., & Sweet, M. (2008). The essential elements of team-based learning. New directions for teaching and learning, 2008 (116), 7–27.

Nunnally, J. C., & Bernstein, I. H. (1994). Validity. Psychometric theory, 99–132.

Paine, J. B., & Organ, D. W. (2000). The cultural matrix of organizational citizenship behavior: Some preliminary conceptual and empirical observations. Human Resource Management Review, 10 (1), 45–59.

Robinson, S., Neergaard, H., Tanggaard, L., & Krueger, N. F. (2016). New horizons in entrepreneurship education: from teacher-led to student-centered learning. Education+ Training, 58(7/8), 661–683.

Schumacker, R. E., & Lomax, R. G. (1996). A beginner's guide to structural equation modeling . Mahwah: Laurence Erlbaum Google Scholar.

Scott, S. G., & Bruce, R. A. (1994). Determinants of innovative behavior: A path model of individual innovation in the workplace. Academy of Management Journal, 37 (3), 580–607.

Shane, S. A. (2003). A general theory of entrepreneurship: The individual-opportunity nexus . Cheltenham: Edward Elgar Publishing.

Book   Google Scholar  

Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25 (1), 217–226.

Siegel, S. M., & Kaemmerer, W. F. (1978). Measuring the perceived support for innovation in organizations. Journal of Applied Psychology, 63 (5), 553–562.

Spivack, G., Platt, J. J., & Shure, M. B. (1976). The problem-solving approach to adjustment . San Francisco: Jossey-Bass.

Stevenson, H., & Gumpert, D. (1985). The heart of entrepreneurship.

Stevenson, H. H. & J. C. Jarillo (1990). 'A paradigm of entrepreneurship: Entrepreneurial management', Strategic Management Journal, 11, pp. 17–27.

Ucbasaran, D., Westhead, P., & Wright, M. (2009). The extent and nature of opportunity identification by experienced entrepreneurs. Journal of Business Venturing, 24 (2), 99–115.

Van de Ven, A. H., & Angle, H. L. (1989). Suggestions for managing the innovation journey (No. 9). Strategic Management Research Center, University of Minnesota.

Venkataraman, S. (1997). The distinctive domain of entrepreneurship research. Advances in entrepreneurship, firm emergence and growth, 3 (1), 119–138.

Venkataraman, S., & Sarasvathy, S. D. (2001). Strategy and entrepreneurship: Outlines of an untold story.

Warner, M. (2002). Publics and counterpublics. Public Culture, 14 (1), 49–90.

Woodman, R. W., Sawyer, J. E., & Griffin, R. W. (1993). Toward a theory of organizational creativity. Academy of Management Review, 18 (2), 293–321.

Download references

Author information

Authors and affiliations.

Dept. of Technology Entrepreneurship (Graduate School), Dongguk University, 904 Chungmurogwn, Toegye-ro 36Gil, Jung-gu, Seoul, 100-272, South Korea

Ji Young Kim, Dae Soo Choi & Chang-Soo Sung

Yonsei School of Business, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-749, South Korea

Joo Y. Park

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Joo Y. Park .

Ethics declarations

Publisher’s note.

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

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Cite this article.

Kim, J.Y., Choi, D.S., Sung, CS. et al. The role of problem solving ability on innovative behavior and opportunity recognition in university students. J. open innov. 4 , 4 (2018). https://doi.org/10.1186/s40852-018-0085-4

Download citation

Received : 12 September 2017

Accepted : 22 January 2018

Published : 05 February 2018

DOI : https://doi.org/10.1186/s40852-018-0085-4

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

• Problem-solving ability
• Innovative behavior
• Opportunity recognition
• Entrepreneurship education

IEEE Account

• Change Username/Password
• Update Address

Purchase Details

• Payment Options
• Order History
• View Purchased Documents

Profile Information

• Communications Preferences
• Profession and Education
• Technical Interests
• US & Canada: +1 800 678 4333
• Worldwide: +1 732 981 0060
• Contact & Support
• About IEEE Xplore
• Accessibility
• Terms of Use
• Nondiscrimination Policy
• Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. © Copyright 2024 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.

More From Forbes

How we can encourage young women to succeed as future entrepreneurs.

• Share to Facebook
• Share to Twitter
• Share to Linkedin

Encouraging girls and young women to become entrepreneurs is not just about providing them with the ... [+] right tools but about creating a culture that values creativity, resilience, and leadership. Through mentorship, exposure to role models, and opportunities to develop entrepreneurial skills, we can empower the next generation of business leaders to succeed.

In today's fast-evolving world, the importance of fostering entrepreneurial spirit in young girls and women cannot be overstated.

The 2024 Wells Fargo Impact of Women-Owned Business Report , in collaboration with Ventureneer, CoreWoman, and Women Impacting Public Policy (WIPP), revealed that between 2019 and 2023, women-owned businesses grew at nearly double the rate of male-owned businesses. Even more impressively, from 2022 to 2023, the growth rate surged to 4.5 times that of businesses owned by men. Still, the global representation of women in senior leadership roles has seen only a modest increase , rising from 31.1% in 2016 to 32.2% in 2023.

With trailblazing female leaders like Kamala Harris, Sheryl Sandberg, and countless others breaking barriers, the stage is set for the next generation of female entrepreneurs.

Yet, challenges persist, and it's up to parents, educators, communities, and businesses to ensure girls and young women have the tools, confidence, and support to succeed in entrepreneurship.

The Importance of Early Inspiration and Representation

Mentorship plays a critical role in helping girls and young women build the skills they need to ... [+] succeed in business. Mentorship doesn't just offer advice; it provides a real-world perspective and allows girls to understand how to apply what they learn in school to the entrepreneurial world.

One of the key elements in encouraging young girls to consider entrepreneurship is early exposure to role models and relatable success stories. Clare Hutton, the author of American Girl's 2025 Girl of the Year novel, shares insights on how Summer Summer McKinny’s entrepreneurial journey can resonate with young girls.

Hurricane Helene Remnants Hit Kentucky As At Least 41 Dead In Its Wake—Here’s What To Know

Sean ‘diddy’ combs’ accused of rape in latest sexual assault lawsuit: here’s a complete look at the allegations, today’s nyt mini crossword clues and answers for friday, september 27.

"I think the idea of starting and running a business can be intimidating to kids," says Hutton. "Summer's journey is about a girl they can relate to with enjoyable interests—animals and baking—that she is able to turn into an actual profitable small business." Summer's story breaks down the challenges of entrepreneurship in a way that feels approachable, allowing young readers to imagine themselves doing the same.

The need for relatable role models cannot be understated. According to Dr. Rosina Racioppi, President and CEO of WOMEN Unlimited , "To create more opportunities for young women to see female role models in leadership, schools should consider inviting successful female alumni to share their career journeys." This visibility can have a profound impact, giving young women the chance to visualize their own futures as entrepreneurs. It's vital for them to see that success is achievable—not just for others, but for themselves.

Mentorship: A Game Changer for Future Female Entrepreneurs

To foster entrepreneurship in young women, we must create formal mentorship structures—partnerships ... [+] between schools, businesses, and community organizations.

Mentorship plays a critical role in helping girls and young women build the skills they need to succeed in business. Mentorship doesn't just offer advice; it provides a real-world perspective and allows girls to understand how to apply what they learn in school to the entrepreneurial world.

"Mentors play a big role in supporting women's growth and development in business," says Dr. Racioppi. "They provide perspectives that are crucial for understanding our business and provide opportunities for feedback." Through mentorship, young women gain not only guidance but also confidence in navigating the challenges of entrepreneurship.

Marina Middleton, Co-Owner & CEO of Create & Cultivate , echoes this sentiment. "A good mentor connects the dots between what you learn in school and what it takes to build something from the ground up," Middleton emphasizes that we need to make mentorship accessible early on through youth programs and events designed to introduce girls to business leaders and entrepreneurs. "Communities and event facilitators need to create those experiences to make mentorship more accessible from a young age, setting up the next generation for success," she adds.

To foster entrepreneurship in young women, we must create formal mentorship structures—partnerships between schools, businesses, and community organizations. These programs can connect aspiring young women with experienced professionals who can guide them through the intricacies of starting and running a business. Early access to mentorship ensures that girls gain the skills, networks, and support they need to succeed.

Encouraging Entrepreneurial Thinking from a Young Age

Empowering woman and girl gender rights concept for international day of girl child, and sports for ... [+] development and peace with healthy strong kid with dumbbell exercise doodle on school chalkboard

Entrepreneurship isn't just about starting a business; it's about developing a mindset focused on creativity, problem-solving, and resilience. Parents, educators, and communities all play a role in fostering this mindset in girls from a young age.

"Parents can serve as their child's first mentor and role model by encouraging curiosity, problem-solving, and resilience," says Dr. Racioppi. By involving daughters in conversations about work and careers, parents can spark an interest in business and leadership. Similarly, schools can integrate entrepreneurial skills into the curriculum through hands-on projects and student-run enterprises.

Middleton suggests creating safe spaces for girls to express their ideas, take risks, and learn from failures. "Exposure to women-led businesses through field trips, guest speakers, or events helps girls envision themselves as future business leaders," she says. Creating environments where girls can explore their interests and develop leadership skills is key to building confidence and an entrepreneurial spirit.

Clare Hutton also highlights the importance of nurturing creativity and teamwork in entrepreneurship. "Summer's business is very much her own, but she has a team she can rely on for support," she says. In Summer Gets to Work , Summer's journey isn't a solitary one—she learns from her aunt, father, and sister and leans on their support to overcome challenges. This aspect of the story shows young girls that they don't have to go it alone—collaboration and mentorship are vital tools for success.

Perseverance and Problem-Solving: Key Traits for Success

Entrepreneurship is filled with obstacles, but those who succeed are the ones who don't give up when ... [+] faced with setbacks.

One of the most important lessons we can teach young girls is the value of perseverance in overcoming challenges. Entrepreneurship is filled with obstacles, but those who succeed are the ones who don't give up when faced with setbacks.

Hutton highlights this in Summer's story, where she faces difficulties in her business and personal life but never gives up. "Summer approaches her business with the same can-do attitude, whether it's deciding the most appealing way to package the dog treats she's selling or figuring out how to rearrange her schedule to make time for the kids' business fair," says Hutton.

Entrepreneurs are problem-solvers at heart, and girls need to be encouraged to approach challenges with creativity and determination. Whether it's a minor setback or a major roadblock, teaching young women that every problem has a solution is crucial to building their confidence as future business leaders.

Creating Opportunities for Growth

As we look toward the future, it's essential to create more opportunities for young women to develop ... [+] entrepreneurial skills and see themselves as leaders.

As we look toward the future, it's essential to create more opportunities for young women to develop entrepreneurial skills and see themselves as leaders. School programs, community initiatives, and internships with women-led businesses can all provide valuable experiences that inspire girls to pursue entrepreneurship.

One way to foster entrepreneurial thinking is through exposure to leadership roles in corporate life, where innovation and problem-solving are valued. "Seeing women in these roles shows young women that they can be entrepreneurial within an organization," says Dr. Racioppi. This not only broadens their understanding of business but also opens doors for career growth and leadership opportunities.

In addition, events like Create & Cultivate provide platforms where young women can learn from successful female entrepreneurs. "It's not just about celebrating the wins," says Middleton. "It's crucial to share the stories and lessons learned through the difficult parts." When young women see the full journey—failures, struggles, and resilience—they learn that success is not a straight line and that stumbling is part of the process.

Empowering the Next Generation of Entrepreneurs

By fostering these qualities in young women today, we ensure a brighter, more inclusive future for ... [+] the world of entrepreneurship tomorrow.

Encouraging girls and young women to become entrepreneurs is not just about providing them with the right tools but about creating a culture that values creativity, resilience, and leadership. Through mentorship, exposure to role models, and opportunities to develop entrepreneurial skills, we can empower the next generation of business leaders to succeed.

As Clare Hutton reflects on Summer McKinny's journey, she hopes young girls walk away knowing that "their labor and interests can have financial value, just like adults can" and that they "can pursue their goals and address their problems with logic, perseverance, teamwork, and a creative spirit."

By fostering these qualities in young women today, we ensure a brighter, more inclusive future for the world of entrepreneurship tomorrow.

• Editorial Standards
• Forbes Accolades

Join The Conversation

One Community. Many Voices. Create a free account to share your thoughts. 

Forbes Community Guidelines

Our community is about connecting people through open and thoughtful conversations. We want our readers to share their views and exchange ideas and facts in a safe space.

In order to do so, please follow the posting rules in our site's  Terms of Service.   We've summarized some of those key rules below. Simply put, keep it civil.

Your post will be rejected if we notice that it seems to contain:

• False or intentionally out-of-context or misleading information
• Insults, profanity, incoherent, obscene or inflammatory language or threats of any kind
• Attacks on the identity of other commenters or the article's author
• Content that otherwise violates our site's  terms.

User accounts will be blocked if we notice or believe that users are engaged in:

• Continuous attempts to re-post comments that have been previously moderated/rejected
• Racist, sexist, homophobic or other discriminatory comments
• Attempts or tactics that put the site security at risk
• Actions that otherwise violate our site's  terms.

So, how can you be a power user?

• Stay on topic and share your insights
• Feel free to be clear and thoughtful to get your point across
• ‘Like’ or ‘Dislike’ to show your point of view.
• Protect your community.
• Use the report tool to alert us when someone breaks the rules.

Thanks for reading our community guidelines. Please read the full list of posting rules found in our site's  Terms of Service.