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Engaging Students with Integrated STEM Education: a Happy Marriage or a Failed Engagement?

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Abstract

The “leaky pipeline” with regard to students’ engagement in Science, Technology, Engineering, and Mathematics (STEM) has triggered extensive research to understand and prevent students dropping out from STEM. To boost enrolment and interest in STEM fields, integrated STEM (iSTEM) education could be harnessed by providing students with relevant challenges. This study investigated (1) the evolution of affective outcomes regarding science and mathematics over time in traditional education, (2) the impact of an iSTEM curriculum on affective outcomes with regard to science and mathematics, and (3) the differential effectiveness of the iSTEM curriculum regarding student characteristics. Therefore, an iSTEM intervention was developed and evaluated over the course of 2 years. In total, 859 grade 9 students, distributed across 39 different Belgian schools, participated in the longitudinal study. The results of multilevel analyses show that students’ attitudes, motivation, and self-efficacy with regard to science and mathematics tend to become less positive over time in traditional education. On the other hand, iSTEM education had positive effects on attitudes towards science and mathematics. However, negative results were observed with regard to motivation and self-efficacy outcomes. In addition, intervention effects differed for boys and girls and for students at different socioeconomic status levels. Our results indicate that iSTEM has the potential to improve students’ attitudes towards STEM, but that we should be careful with regard to the implementation of this approach in terms of student motivation and self-efficacy.

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References

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

    Article  Google Scholar 

  • Ardies, J., De Maeyer, S., & Gijbels, D. (2015). A longitudinal study on boys’ and girls’ career aspirations and interest in technology. Research in Science & Technological Education, 33(3), 366–386.

    Article  Google Scholar 

  • Ardies, J., De Maeyer, S. D., & Gijbels, D. (2013). Reconstructing the pupils’ attitude towards technology-survey. Design and Technology Education: An International Journal, 18(1), 8–19.

    Google Scholar 

  • Armitage, C. J., & Conner, M. (2001). Efficacy of the theory of planned behaviour: A meta-analytic review. British Journal of Social Psychology, 40(4), 471–499.

    Article  Google Scholar 

  • Bandura, A. (1997). Self-efficacy: The exercise of control. Freeman.

  • Bandura, A., Barbaranelli, C., Caprara, G. V., & Pastorelli, C. (2001). Self-efficacy beliefs as shapers of children’s aspirations and career trajectories. Child Development, 72(1), 187–206.

    Article  Google Scholar 

  • Becker, K., & Park, K. (2011). Effects of integrative approaches among science, technology, engineering, and mathematics (STEM) subjects on students’ learning: A preliminary meta-analysis. Journal of STEM Education, 12(5/6), 23–27.

    Google Scholar 

  • Bornstein, M. H., & Bradley, R. H. (2003). Socioeconomic status, parenting, and child development. Lawrence Erlbaum Associates.

  • Cohen, L., Manion, L., & Morrison, K. (2013). Research methods in education. Routledge.

  • Czerniak, C. M., & Johnson, C. C. (2014). Interdisciplinary science and STEM teaching. In N. G. Lederman & S. K. Abell (Eds.), Handbook of research on science education (2nd ed.). Lawrence Erlbaum Associates, Inc..

  • Czerniak, C. M., Weber, W., Sandmann, A., & Ahern, J. (1999). A literature review of science and mathematics integration. School Science and Mathematics, 99(8), 421–430.

    Article  Google Scholar 

  • De Loof, H., Struyf, A., Boeve-de Pauw, J., & Van Petegem, P. (2019). Teachers’ motivating style and students’ motivation and engagement in STEM: The relationship between three key educational concepts. Research in Science Education, 49, 1–19.

  • Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Plenum.

  • Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268.

    Article  Google Scholar 

  • Deci, E. L., Vallerand, R. J., Pelletier, L. G., & Ryan, R. M. (1991). Motivation and education: The self-determination perspective. Educational Psychologist, 26(3–4), 325–346.

    Article  Google Scholar 

  • DeWitt, J., & Archer, L. (2015). Who aspires to a science career? A comparison of survey responses from primary and secondary school students. International Journal of Science Education, 37(13), 2170–2192.

    Article  Google Scholar 

  • Dweck, C. S. (2002). The development of ability conceptions. In A. Wigfield & J. S. Eccles (Eds.), Development of achievement motivation. A volume in the educational psychology series: Vol. xvii (pp. 57–88). Academic Press.

  • English, L. D. (2016). STEM education K-12: Perspectives on integration. International Journal of STEM Education, 3(1), 3.

    Article  Google Scholar 

  • George, R. (2006). A cross-domain analysis of change in students’ attitudes toward science and attitudes about the utility of science. International Journal of Science Education, 28(6), 571–589.

    Article  Google Scholar 

  • Honey, M., Pearson, G., & Schweingruber, H. (2014). STEM integration K-12 education: Status, prospects, and an agenda for research. National Academies Press.

  • Jeffries, D., Curtis, D. D., & Conner, L. N. (2020). Student factors influencing STEM subject choice in year 12: A structural equation model using PISA/LSAY data. International Journal of Science and Mathematics Education, 18(3), 441–461.

    Article  Google Scholar 

  • Judson, E., & Sawada, D. (2000). Examining the effects of a reformed junior high school science class on students’ math achievement. School Science and Mathematics, 100(8), 419–425.

    Article  Google Scholar 

  • Keith, K. (2018). Case Study: Exploring the Implementation of an Integrated STEM Curriculum Program in Elementary First Grade Classes (Doctoral dissertation). Concordia University, Portland.

  • Klopfer, L. E. (1971). Evaluation of learning in science. In B. S. Bloom, J. T. Hastings, & G. F. Madaus (Eds.), Handbook of formative and summative evaluation of student learning. McGraw-Hill.

  • Knipprath, H., Thibaut, L., Buyse, M. P., Ceuppens, S., De Loof, H., De Meester, J., Goovaerts, L., Struyf, A., Boeve-De Pauw, J., Depaepe, F., Deprez, J., De Cock, M., Hellinckx, L., Langie, G., Struyven, K., Van de Velde, D., Van Petegem, P., & Dehaene, W. (2018). STEM education in Flanders: How STEM@ school aims to foster STEM literacy and a positive attitude towards STEM. IEEE Instrumentation & Measurement Magazine, 21(3), 36–40.

  • Kusurkar, R. A., Ten Cate, T. J., Vos, C. M. P., Westers, P., & Croiset, G. (2013). How motivation affects academic performance: A structural equation modelling analysis. Advances in Health Sciences Education, 18(1), 57–69.

    Article  Google Scholar 

  • Lau, S., & Roeser, R. W. (2002). Cognitive abilities and motivational processes in high school students’ situational engagement and achievement in science. Educational Assessment, 8, 139–162.

    Article  Google Scholar 

  • Lent, R. W., Brown, S. D., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45(1), 79–122.

    Article  Google Scholar 

  • Little, R. J. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404), 1198–1202.

    Article  Google Scholar 

  • Maas, C. J. M., & Hox, J. J. (2005). Sufficient sample sizes for multilevel modeling. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 1, 86–92.

    Article  Google Scholar 

  • Ntoumanis, N. (2005). A prospective study of participation in optional school physical education using a self-determination theory framework. Journal of Educational Psychology, 97(3), 444–453.

    Article  Google Scholar 

  • O’Donnell, C. L. (2008). Defining, conceptualizing, and measuring fidelity of implementation and its relationship to outcomes in K–12 curriculum intervention research. Review of Educational Research, 78(1), 33–84.

    Article  Google Scholar 

  • Olsson, D., & Gericke, N. (2016). The adolescent dip in students’ sustainability consciousness—Implications for education for sustainable development. The Journal of Environmental Education, 47(1), 35–51.

    Article  Google Scholar 

  • Osborne, J., Simon, S., & Collins, S. (2003). Attitudes towards science: A review of the literature and its implications. International Journal of Science Education, 25(9), 1049–1079.

    Article  Google Scholar 

  • Pajares, M. F. (1992). Teachers’ beliefs and educational research: Cleaning up a messy construct. Review of Educational Research, 62(3), 307–332.

    Article  Google Scholar 

  • Roehrig, G. H., Moore, T. J., Wang, H.-H., & Park, M. S. (2012). Is adding the E enough? Investigating the impact of K-12 engineering standards on the implementation of STEM integration. School Science and Mathematics, 112(1), 31–44.

    Article  Google Scholar 

  • Ryan, R. M., & Connell, J. P. (1989). Perceived locus of causality and internalization: Examining reasons for acting in two domains. Journal of Personality and Social Psychology, 57(5), 749–761.

    Article  Google Scholar 

  • Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68–78.

    Article  Google Scholar 

  • SAS Institute. (2000). JMP: Statistics and graphics guide. Sas Inst.

  • Schoon, I., & Parsons, S. (2002). Teenage aspirations for future careers and occupational outcomes. Journal of Vocational Behavior, 60(2), 262–288.

    Article  Google Scholar 

  • Shin, J., Lee, H., McCarthy-Donovan, A., Hwang, H., Yim, S., & Seo, E. (2015). Home and motivational factors related to science-career pursuit: Gender differences and gender similarities. International Journal of Science Education, 37(9), 1478–1503.

    Article  Google Scholar 

  • Tate, W. F. (1997). Race-ethnicity, SES, gender, and language proficiency trends in mathematics achievement: An update. Journal for Research in Mathematics Education, 28(6), 652–679.

    Google Scholar 

  • Taylor, R. C. (2015). Using the theory of planned behaviour to understand students’ subject choices in post-compulsory education. Research Papers in Education, 30(2), 214–231.

    Article  Google Scholar 

  • Thibaut, L., Ceuppens, S., De Loof, H., De Meester, J., Goovaerts, L., Struyf, A., Boeve-de Pauw, J., Dehaene, W., Deprez, J., De Cock, M., Hellinckx, L., Knipprath, H., Langie, G., Struyven, K., Van de Velde, D., Van Petegem, P., & Depaepe, F. (2018). Integrated STEM education: A systematic review of instructional practices in secondary education. European Journal of STEM Education, 3(1), 1–12.

  • Thibaut, L., Knipprath, H., Dehaene, W., & Depaepe, F. (2019). Teachers’ attitudes toward teaching integrated stem: The impact of personal background characteristics and school context. International Journal of Science and Mathematics Education, 17(5), 987–1007.

    Article  Google Scholar 

  • Thoman, D. B., Arizaga, J. A., Smith, J. L., Story, T. S., & Soncuya, G. (2014). The grass is greener in non-science, technology, engineering, and math classes: Examining the role of competing belonging to undergraduate women’s vulnerability to being pulled away from science. Psychology of Women Quarterly, 38(2), 246–258.

    Article  Google Scholar 

  • Thomas, G. P., Anderson, D., & Nashon, S. M. (2008). Development and validity of an instrument designed to investigate elements of science students’ metacognition, self-efficacy and learning processes: The SEMLI-S. International Journal of Science Education, 30(13), 1701–1724.

    Article  Google Scholar 

  • Vallera, F. L., & Bodzin, A. M. (2020). Integrating STEM with AgLIT (agricultural literacy through innovative technology): The efficacy of a project-based curriculum for upper-primary students. International Journal of Science and Mathematics Education, 18(3), 419–439.

    Article  Google Scholar 

  • Vallerand, R. J., & Bissonnette, R. (1992). Intrinsic, extrinsic, and amotivational styles as predictors of behavior: A prospective study. Journal of Personality, 60(3), 599–620.

    Article  Google Scholar 

  • Vallerand, R. J., Fortier, M. S., & Guay, F. (1997). Self-determination and persistence in a real-life setting: Toward a motivational model of high school dropout. Journal of Personality and Social Psychology, 72(5), 1161–1176.

    Article  Google Scholar 

  • Wang, H. H., Moore, T. J., Roehrig, G. H., & Park, M. S. (2011). STEM integration: Teacher perceptions and practice. Journal of Pre-College Engineering Education Research, 1(2), 1–13.

    Google Scholar 

  • Wang, M. T., & Degol, J. L. (2017). Gender gap in science, technology, engineering, and mathematics (STEM): Current knowledge, implications for practice, policy, and future directions. Educational Psychology Review, 29(1), 119–140.

    Article  Google Scholar 

  • Wang, X. (2013). Why students choose STEM majors: Motivation, high school learning, and postsecondary context of support. American Educational Research Journal, 50(5), 1081–1121.

    Article  Google Scholar 

  • Watt, H. M., Eccles, J. S., & Durik, A. M. (2006). The leaky mathematics pipeline for girls: A motivational analysis of high school enrolments in Australia and the USA. Equal Opportunities International, 25(8), 642–659.

    Article  Google Scholar 

  • Watt, H. M., Shapka, J. D., Morris, Z. A., Durik, A. M., Keating, D. P., & Eccles, J. S. (2012). Gendered motivational processes affecting high school mathematics participation, educational aspirations, and career plans: A comparison of samples from Australia, Canada, and the United States. Developmental Psychology, 48(6), 1594–1611.

    Article  Google Scholar 

  • Yildirim, B. (2016). An analyses and meta-synthesis of research on STEM education. Journal of Education and Practice, 7(34), 23–33.

    Google Scholar 

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Funding

We wish to express our gratitude to the Flemish government agency for Innovation by Science and Technology (IWT) for funding the project STEM@School and thereby making this study possible.

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Correspondence to Haydée De Loof.

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De Loof, H., Boeve-de Pauw, J. & Van Petegem, P. Engaging Students with Integrated STEM Education: a Happy Marriage or a Failed Engagement?. Int J of Sci and Math Educ 20, 1291–1313 (2022). https://doi.org/10.1007/s10763-021-10159-0

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