Advancements in science, technology, engineering, and mathematics (STEM) are critical to the success of modern societies. However, STEM education and careers are often hindered by cognitive factors, such as mindset, motivation, and learning strategies. This paper examines the complex interplay between cognitive factors and STEM education and careers, highlighting the profound influence of these factors on success in these fields. Through a comprehensive review of existing literature and empirical evidence, this paper presents a compelling case for the need to prioritize cognitive development in STEM education and career pathways. We argue that by fostering a growth mindset, cultivating intrinsic motivation, and promoting effective learning strategies, individuals can overcome cognitive barriers and achieve success in STEM education and careers. Ultimately, this paper underscores the critical role of cognitive factors in shaping the future of STEM fields and offers practical recommendations for educators, policymakers, and STEM professionals to support cognitive development and enhance STEM outcomes.
Ahmed, W., & Mudrey, R. R. (2018). The role of motivational factors in predicting {STEM} career aspirations. International Journal of School & Educational Psychology, 7(3), 201–214. https://doi.org/10.1080/21683603.2017.1401499.
Blaise, M., Marksteiner, T., Krispenz, A., & Bertrams, A. (2021). Measuring motivation for cognitive effort as state. Frontiers in Psychology, 12:785094.
https://doi.org/10.3389/fpsyg.2021.785094.
Butler, A. C., Marsh, E. J., Slavinsky, J. P., & Baraniuk, R. G. (2014). Integrating cognitive science and technology improves learning in a STEM classroom. Educational Psychology Review, 26(2), 331–340. https://doi.org/10.1007/s10648-014-9256-4
Cameron, J., Pierce, W. D., Banko, K. M., & Gear, A. (2005). Achievement-based rewards and intrinsic motivation: A test of cognitive mediators. Journal of Educational Psychology, 97(4), 641–655. https://doi.org/10.1037/0022-0663.97.4.641.
Deci, E. L., & Ryan, R. M. (1985). Conceptualizations of intrinsic motivation and self-determination. In: Intrinsic Motivation and Self-Determination in Human Behavior. Perspectives in Social Pscyhology. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-2271-7_2.
De Loof, H., Boeve-de Pauw, J., & Van Petegem, P. (2022). Integrated STEM education: The effects of a long-term intervention on students cognitive performance. European Journal of STEM Education, 7(1), 13. https://doi.org/10.20897/ejsteme/12738.
Di Vesta, F. J. (1987). The cognitive movement and education. In: Glover, J.A., Ronning, R.R. (eds) Historical foundations of educational psychology. Perspectives on individual differences. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-3620-2_11
Drysdale, M. T. B., Ross, J. L., & Schulz, R. A. (2001). Cognitive learning styles and academic performance in 19 first-year university courses: Successful students versus students at risk. Journal of Education for Students Placed at Risk (JESPAR), 6(3), 271–289. https://doi.org/10.1207/s15327671espr0603_7.
Dutta, A., Kang, H.-J., Kaya, C., Benton, S. F., Sharp, S. E., Chan, F., … Kundu, M. (2015). Social-cognitive career theory predictors of STEM career interests and goal persistence in minority college students with disabilities: A path analysis. Journal of Vocational Rehabilitation, 43(2), 159–167. https://doi.org/10.3233/jvr-150765.
Dweck, C. S. (2000). Self-theories: Their role in motivation, personality, and development. Psychology Press. https://doi.org/10.4324/9781315783048.
Evans, C., Cools, E., & Charlesworth, Z. M. (2010). Learning in higher education: How cognitive and learning styles matter. Teaching in Higher Education, 15(4), 467–478. https://doi.org/10.1080/13562517.2010.493353.
Firdaus, A. R., & Rahayu, G. D. S. (2019). Effect of STEM-based Learning on the cognitive skills improvement. Mimbar Sekolah Dasar, 6(2), 198. https://doi.org/10.17509/mimbar-sd.v6i2.17562.
Graf, S., Lin, T., & Kinshuk. (2008). The relationship between learning styles and cognitive traits getting additional information for improving student modelling. Computers in Human Behavior, 24(2), 122–137. https://doi.org/10.1016/j.chb.2007.01.004.
Graf, S., & Kinshuk. (2010). Using cognitive traits for improving the detection of learning styles. Workshops on Database and Expert Systems Applications. Bilbao, Spain, 74-78. https://doi.org/10.1109/dexa.2010.35.
Hatisaru, V. (2021). Theory-driven determinants of school students stem career goals: A preliminary investigation. European Journal of STEM Education, 6(1), 2. https://doi.org/10.20897/ejsteme/9558.
Hayes, J., & Allinson, C. W. (1998). Cognitive style and the theory and practice of individual and collective learning in organizations. Human Relations, 51(7), 847–871. https://doi.org/10.1177/001872679805100701.
Hegarty, M., Canham, M. S., & Fabrikant, S. I. (2010). Thinking about the weather: How display salience and knowledge affect performance in a graphic inference task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36(1), 37.
Henderson, C., Mestre, J. P., & Slakey, L. L. (2015). Cognitive science research can improve undergraduate STEM instruction. Policy Insights from the Behavioral and Brain Sciences, 2(1), 51–60. https://doi.org/10.1177/2372732215601115.
Hofstein, A., & Rosenfeld, S. (1996). Bridging the gap between formal and informal science learning. Studies in Science Education, 28(1), 87–
112. https://doi.org/10.1080/03057269608560085.
Husmann, P., & O’Loughlin, V. (2018). Another nail in the coffin for learning styles? Disparities among undergraduate anatomy students’ study strategies, class performance, and reported VARK learning styles. Anatomical Sciences Education, 12. https://doi.org/10.1002/ase.1777.
Idris, R., & Bacotang, J. (2023). Exploring STEM education trends in Malaysia: Building a talent pool for Industrial Revolution 4.0 and Society 5.0. International Journal of Academic Research in Progressive Education and Development, 12(2), 381–393. http://dx.doi.org/10.6007/IJARPED/v12-i2/16825.
Idris, R., Govindasamy, P., & Nachiappan, S. (2023). Challenge and obstacles of STEM education in Malaysia. International Journal of Academic Research in Business and Social Sciences, 13(4), 820 – 828. http://dx.doi.org/10.6007/IJARBSS/v13-i4/16676.
Ilcin, N., Tomruk, M., Yesilyaprak, S. S., Karadibak, D., & Savci, S. (2018). The relationship between learning styles and academic performance in Turkish physiotherapy students. BMC Medical Education, 18(1), 291. https://doi.org/10.1186/s12909-018-1400-2.
Kostromina, S. N., & Dvornikova, T. A. (2016). Psychological factors of cognitive learning strategies formation in students. Vestnik of Saint Petersburg University. Psychology, 6(4), 110–119. https://doi.org/10.21638/11701/spbu16.2016.409.
Kozhan, A., & Tapalova, O. B. (2020). Cognitive basis of students motivation and psychological stability. BULLETIN Series Psychology, 65(4), 186–190. https://doi.org/10.51889/2020-4.1728-7847.36.
Kozhevnikov, M., Evans, C., & Kosslyn, S. M. (2014). Cognitive style as environmentally sensitive individual differences in cognition: A modern synthesis and applications in education, business, and management. Psychological science in the public interest: A journal of the American Psychological Society, 15(1), 3–33.
https://doi.org/10.1177/1529100614525555.
Kreitler, S., & Kreitler, H. (1988). The cognitive approach to motivation in retarded individuals. International Review of Research in Mental Retardation, 15, 81–123.
https://doi.org/10.1016/s0074-7750(08)60220-7.
Kreitler, S. (2013). Cognition and motivation: Forging an interdisciplinary perspective. Cambridge University Press.
Kruglanski, A. W., Belanger, J. J., Chen, X., Kopetz, C., Pierro, A., & Mannetti, L. (2012). The energetics of motivated cognition: A force-field analysis. Psychological Review, 119(1), 1–20. https://doi.org/10.1037/a0025488.
Kumar, A., Singh, N., & Ahuja, N. J. (2017). Learning styles based adaptive intelligent tutoring systems: Document analysis of articles published between 2001 and 2016. International Journal of Cognitive Research in Science, Engineering and Education, 5(2), 83–98. https://doi.org/10.5937/IJCRSEE1702083K.
Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108(3), 480–498. https://doi.org/10.1037/0033-2909.108.3.480.
LeBlanc, T. R. (2018). Learning Styles: academic fact or urban myth? A recent review of the literature. Journal of College Academic Support Programs, 1(1), 34-40. https://doi.org/10.36896/1.1fa4.
Lundgren, S. R., & Prislin, R. (1998). Motivated cognitive processing and attitude change. Personality and Social Psychology Bulletin, 24(7), 715–726.
https://doi.org/10.1177/0146167298247004.
Lwande, C., Muchemi, L., & Oboko, R. (2021). Identifying learning styles and cognitive traits in a learning management system. Heliyon, 7(8), 1-9.
https://doi.org/10.1016/j.heliyon.2021.e07701.
Minshew, L. M., Olsen, A. A., & McLaughlin, J. E. (2021). Cognitive apprenticeship in STEM graduate education: A qualitative review of the literature. AERA Open, 7(1), 1-16. https://doi.org/10.1177/23328584211052044.
National Academy of Engineering and National Research Council. (2014). STEM Integration in K-12 Education: Status, Prospects, and an Agenda for Research. Washington, DC: The National Academies Press. https://doi.org/10.17226/18612.
Niemivirta, M. (1999). Motivational and cognitive predictors of goal setting and task performance. International Journal of Educational Research, 31(6), 499–513. https://doi.org/10.1016/s0883-0355(99)00018-x.
Palo, V. D., Sinatra, M., Tanucci, G., Monacis, L., Bitonto, P. D., Roselli, T., & Rossano, V. (2012). How cognitive styles affect the e-learning process. 2012 IEEE 12th International Conference on Advanced Learning Technologies, 359-363.
https://doi.org/10.1109/ICALT.2012.79.
Pintrich, P. R., & Groot, E. D. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82, 33-40. https://doi.org/10.1037/0022-0663.82.1.33.
Pithers R. T. (2002) Cognitive learning style: A review of the field dependent- field independent approach, Journal of Vocational Education and Training, 54(1), 117-132. https://doi.org/10.1080/13636820200200191.
Qureshi, A., & Qureshi, N. (2021). Challenges and issues of STEM education. Advances in Mobile Learning Educational Research, 1(2), 146–161.
https://doi.org/10.25082/amler.2021.02.009.
Rayner, S. G. (2015). Cognitive styles and learning styles. International Encyclopedia of the Social & Behavioral Sciences, 4(2), 110–117. https://doi.org/10.1016/b978-0-08-097086-8.92008-7.
Riding, R., & Rayner, S. (1998). Cognitive styles and learning strategies: Understanding style differences in learning and behavior (1st ed.). David Fulton Publishers. https://doi.org/10.4324/9781315068015.
Rivera, H., & Li, J.-T. (2020). Potential factors to enhance students’ STEM college learning and career orientation. Frontiers in Education, 5.
https://doi.org/10.3389/feduc.2020.00025.
Ros, S., Tobarra, L., Robles-Gomez, A., Caminero, A. C., Hernandez, R., Pastor, R., … Cano, J. (2016). Work in progress: On the improvement of STEM education from preschool to elementary school. IEEE Global Engineering Education Conference (EDUCON). https://doi.org/10.1109/educon.2016.7474671.
Sadler-Smith, E., & Badger, B. (1998). Cognitive style, learning and innovation. Technology Analysis & Strategic Management, 10(2), 247–266.
https://doi.org/10.1080/09537329808524314.
Sadler-Smith, E., & Riding, R. (1999). Cognitive style and instructional preferences. Instructional Science, 27(5), 355–371. https://doi.org/10.1007/bf00892031.
Sadler-Smith, E., Allinson, C. W., & Hayes, J. (2000). Learning preferences and cognitive style. Management Learning, 31(2), 239–256. https://doi.org/10.1177/1350507600312006.
Sahin, A., Ekmekci, A., & Waxman, H. C. (2017). Collective effects of individual, behavioral, and contextual factors on high school students future STEM career plans. International Journal of Science and Mathematics Education, 16(S1), 69–89.
https://doi.org/10.1007/s10763-017-9847-x.
Schunk, D. H., & Usher, E. L. (2012). Social cognitive theory and motivation. The Oxford Handbook of Human Motivation. Oxford University Press.
https://doi.org/10.1093/oxfordhb/9780195399820.013.0002.
Schunk, D. H., & DiBenedetto, M. K. (2020). Motivation and social cognitive theory. Contemporary Educational Psychology, 60, 101832.
https://doi.org/10.1016/j.cedpsych.2019.101832.
Seo, M. G., Barrett, L. F., & Bartunek, J. M. (2004). The role of affective experience in work motivation. The Academy of Management Review, 29(3), 423.
https://doi.org/10.2307/20159052.
Shi, C. (2011). A study of the relationship between cognitive styles and learning strategies. Higher Education Studies, 1(1). https://doi.org/10.5539/hes.v1n1p20.
Shifrer, D., & Freeman, M. D. (2021). Problematizing perceptions of STEM potential: Differences by cognitive disability status in high school and postsecondary educational outcomes. Socius: Sociological Research for a Dynamic World, 7.
https://doi.org/10.1177/2378023121998116.
Spiegel, S., Grant-Pillow, H., & Higgins, E. T. (2004). How regulatory fit enhances motivational strength during goal pursuit. European Journal of Social Psychology, 34(1), 39–54. https://doi.org/10.1002/ejsp.180.
Steinhart, Y., & Wyer Jr., R. S. (2009). Motivational correlates of need for cognition. European Journal of Social Psychology, 39(4), 608–621. https://doi.org/10.1002/ejsp.565.
Stoet, G., & Geary, D. C. (2013). Sex differences in mathematics and reading achievement are inversely related: Within and across-nation assessment of 10 years of PISA data. PloS one, 8(3). https://doi.org/10.1371/journal.pone.0057988.
Tinajero, C., Lemos, S. M., Araujo, M., Ferraces, M. J., & Paramo, M. F. (2012). Cognitive style and learning strategies as factors which affect academic achievement of Brazilian university students. Psicologia: Reflexão e Crítica, 25(1), 105–113.
https://doi.org/10.1590/s0102-79722012000100013.
Wang, M.-T., Ye, F., & Degol, J. L. (2016). Who chooses STEM careers? Using a relative cognitive strength and interest model to predict careers in science, technology, engineering, and mathematics. Journal of Youth and Adolescence, 46(8), 1805–1820. https://doi.org/10.1007/s10964-016-0618-8.
Weisberg, S. M., & Newcombe, N. S. (2017). Embodied cognition and STEM learning: Overview of a topical collection in CR:PI. Cognitive Research: Principles and Implications, 2(1). https://doi.org/10.1186/s41235-017-0071-6.
Witkin, H. A., Moore, C. A., Goodenough, D. R., & Cox, P. W. (1977). Field-dependent and field-independent cognitive styles and their educational implications. Review of Educational Research, 47, 1 - 64. https://doi.org/10.3102/00346543047001001.
Yasmeen, S., Batool, I., Bajwa, S. & Saqib, M., (2020). Does learning styles and employee creative behavior; An exploration through cognitive styles. Journal of Business and Social Review in Emerging Economies, 6(1), 43-54.
https://doi.org/10.26710/jbsee.v6i1.1024.
Zeng, Z., Yao, J., Gu, H., & Przybylski, R. (2018). A meta-analysis on the effects of STEM education on students abilities. Science Insights Education Frontiers, 1(1), 3–16. https://doi.org/10.15354/sief.18.re005.
