Explaining variation in student efforts towards using math and science knowledge in engineering contexts

References

• Barnett, M. (2005). Engaging inner city students in learning through designing remote operated vehicles. Journal of Science Education and Technology, 14(1), 87–100. doi: 10.1007/s10956-005-2736-z
   Google Scholar
• Berland, L. K. (2013). Designing for STEM integration. Journal of Pre-Collegiate Engineering Education, 3(1), 22–31.
   Google Scholar
• Berland, L. K., & Busch, K. C. (2012, June). Negotiating STEM epistemic commitments for engineering design challenges. Paper presented at the annual meeting of the American Society for Engineering Education, San Antonio, TX.
   Google Scholar
• Berland, L. K., Martin, T., Ko, P., Peacock, S., Rudolph, J., & Golubski, C. (2013). Student learning in challenge-based engineering curricula. Journal of Pre-Collegiate Engineering Education, 3(1), 52–64.
   Google Scholar
• Berland, L. K., McKenna, W., & Peacock, S. (2012). Understanding students’ perceptions on the utility of engineering notebooks. Advances in Engineering Education, 3(2), Retrieved from https://www.researchgate.net/publication/287576495_Understanding_students'_perceptions_on_the_utility_of_engineering_notebooks
   Google Scholar
• Berland, L. K., Steingut, R., & Ko, P. (2014). High school student perceptions of the utility of engineering design process: Creating opportunities to engage in the engineering practices and apply math and science content. Journal of Science Education and Technology, 23(6), 705–720. doi: 10.1007/s10956-014-9498-4
   Web of Science ®Google Scholar
• Cantrell, P., Pekcan, G., Itani, A., & Velasquez-Bryant, N. (2006). The effects of engineering modules on student learning in middle school science classrooms. Journal of Engineering Education, 95(4), 301–309. Retrieved from http://doi.org/10.1002/j.2168-9830.2006.tb00905.x doi: 10.1002/j.2168-9830.2006.tb00905.x
   Web of Science ®Google Scholar
• Carr, R. L., Bennett, L. D., & Strobel, J. (2012). Engineering in the K-12 STEM standards of the 50 U.S. States: An analysis of presence and extent. Journal of Engineering Education, 101(3), 539–564. Retrieved from http://doi.org/10.1002/j.2168-9830.2012.tb00061.x doi: 10.1002/j.2168-9830.2012.tb00061.x
   Web of Science ®Google Scholar
• Chiu, J. L., & Linn, M. C. (2011). Knowledge integration and WISE engineering. Journal of Pre-College Engineering Education Research (J-PEER), 1(1), Article 2, 1–14. Retrieved from http://docs.lib.purdue.edu doi: 10.7771/2157-9288.1026
   Google Scholar
• Crismond, D. P. (2001). Learning and using science ideas when doing investigate-and-redesign tasks: A study of naive, novice, and expert designers doing constrained and scaffolded design work. Journal of Research in Science Teaching, 38(7), 791–820. Retrieved from http://doi.org/10.1002/tea.1032 doi: 10.1002/tea.1032
   Web of Science ®Google Scholar
• Crismond, D. P., & Adams, R. S. (2012). The informed design teaching and learning matrix. Journal of Engineering Education, 101(4), 738–797. Retrieved from http://doi.org/10.1002/j.2168-9830.2012.tb01127.x doi: 10.1002/j.2168-9830.2012.tb01127.x
   Web of Science ®Google Scholar
• Dally, J. W., & Zhang, G. M. (1993). A freshman engineering design course. Journal of Engineering Education, 82(2), 83–91. Retrieved from http://doi.org/10.1002/j.2168-9830.1993.tb00081.x doi: 10.1002/j.2168-9830.1993.tb00081.x
   Google Scholar
• Deci, E. L., Eghrari, H., Patrick, B. C., & Leone, D. R. (1994). Facilitating internalization: The self-determination theory perspective. Journal of Personality, 62(1), 119–142. doi: 10.1111/j.1467-6494.1994.tb00797.x
   PubMed Web of Science ®Google Scholar
• Dietrich, J., Dicke, A.-L., Kracke, B., & Noack, P. (2015). Teacher support and its influence on students’ intrinsic value and effort: Dimensional comparison effects across subjects. Learning and Instruction, 39, 45–54. Retrieved from http://doi.org/10.1016/j.learninstruc.2015.05.007 doi: 10.1016/j.learninstruc.2015.05.007
   Web of Science ®Google Scholar
• Durik, A. M., Vida, M., & Eccles, J. S. (2006). Task values and ability beliefs as predictors of high school literacy choices: A developmental analysis. Journal of Educational Psychology, 98(2), 382–393. Retrieved from http://doi.org/10.1037/0022-0663.98.2.382 doi: 10.1037/0022-0663.98.2.382
   Web of Science ®Google Scholar
• Dym, C. L., Agogino, A. M., Eris, O., Frey, D. D., & Leifer, L. J. (2005). Engineering design thinking, teaching, and learning. Journal of Engineering Education, 94(1), 103–120. Retrieved from http://doi.org/10.1002/j.2168-9830.2005.tb00832.x doi: 10.1002/j.2168-9830.2005.tb00832.x
   Web of Science ®Google Scholar
• Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53(1), 109–132. doi: 10.1146/annurev.psych.53.100901.135153
   PubMed Web of Science ®Google Scholar
• Eccles (Parsons), J. (1983). Expectancies, values, and academic behaviors. In J. T. Spence (Eds.), Achievement and achievement motives: Psychological and sociological approaches (pp. 75–146). San Francisco, CA: Freeman.
   Google Scholar
• Edelson, D. C. (2001). Learning-for-use: A framework for integrating content and process learning in the design of inquiry activities. Journal of Research in Science Teaching, 38, 355–385. doi: 10.1002/1098-2736(200103)38:3<355::AID-TEA1010>3.0.CO;2-M
   Web of Science ®Google Scholar
• Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 12(2), 121–138. Retrieved from http://doi.org/10.1037/1082-989X.12.2.121 doi: 10.1037/1082-989X.12.2.121
   PubMed Web of Science ®Google Scholar
• Fortus, D., Krajcik, J., Dershimer, R. C., Marx, R. W., & Mamlok-Naaman, R. (2005). Design-based science and real-world problem-solving. International Journal of Science Education, 27, 855–879. doi: 10.1080/09500690500038165
   Web of Science ®Google Scholar
• Fredricks, J. A., & McColskey, W. (2012). The Measurement of Student Engagement: A Comparative Analysis of Various Methods and Student Self-report Instruments. In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of Research on Student Engagement (pp. 763–782). Boston, MA: Springer US. Retrieved from http://link.springer.com/10.1007/978-1-4614-2018-7_37
   Google Scholar
• Guerra, L., Allen, D., Berland, L., Crawford, R., & Farmer, C. (2012). A unique approach to characterizing the engineering design process. Presented at the American Society for Engineering Education, San Antonio, TX.
   Google Scholar
• Guzey, S. S., Moore, T. J., Harwell, M., & Moreno, M. (2016). STEM integration in middle school life science: Student learning and attitudes. Journal of Science Education and Technology, 25(4), 550–560. Retrieved from http://doi.org/10.1007/s10956-016-9612-x doi: 10.1007/s10956-016-9612-x
   Web of Science ®Google Scholar
• Hmelo, C. E., Holton, D. L., & Kolodner, J. L. (2000). Designing to learn about complex systems. The Journal of the Learning Sciences, 9, 247–298. doi: 10.1207/S15327809JLS0903_2
   Web of Science ®Google Scholar
• Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16, 235–266. doi: 10.1023/B:EDPR.0000034022.16470.f3
   Web of Science ®Google Scholar
• Hotaling, N., Fasse, B. B., Bost, L. F., Hermann, C. D., & Forest, C. R. (2012). A quantitative analysis of the effects of a multidisciplinary engineering capstone design course. Journal of Engineering Education, 101(4), 630–656. Retrieved from http://doi.org/10.1002/j.2168-9830.2012.tb01122.x doi: 10.1002/j.2168-9830.2012.tb01122.x
   Web of Science ®Google Scholar
• Hughes, J. N., Luo, W., Kwok, O.-M., & Loyd, L. K. (2008). Teacher-student support, effortful engagement, and achievement: A 3-year longitudinal study. Journal of Educational Psychology, 100 (1), 1–14. Retrieved from https://doi.org/10.1037/0022-0663.100.1.1 doi: 10.1037/0022-0663.100.1.1
   PubMed Web of Science ®Google Scholar
• Hulleman, C. S., Godes, O., Hendricks, B. L., & Harackiewicz, J. M. (2010). Enhancing interest and performance with a utility value intervention. Journal of Educational Psychology, 102(4), 880–895. Retrieved from http://doi.org/10.1037/a0019506 doi: 10.1037/a0019506
   Web of Science ®Google Scholar
• Jones, B. D., Paretti, M. C., Hein, S. F., & Knott, T. W. (2010). An analysis of motivation constructs with first-year engineering students: Relationships among expectancies, values, achievement, and career plans. Journal of Engineering Education, 99(4), 319–336. Retrieved from http://doi.org/10.1002/j.2168-9830.2010.tb01066.x doi: 10.1002/j.2168-9830.2010.tb01066.x
   Web of Science ®Google Scholar
• Kanter, D. E. (2010). Doing the project and learning the content: Designing project-based science curricula for meaningful understanding. Science Education, 94, 525–551. doi: 10.1002/sce.20391
   Web of Science ®Google Scholar
• Kolodner, J. L., Camp, P. J., Crismond, D., Fasse, B., Gray, J., Holbrook, J., … Ryan, M. (2003). Problem-based learning meets case-based reasoning in the middle-school science classroom: Putting learning by design into practice. The Journal of the Learning Sciences, 12, 495–547. doi: 10.1207/S15327809JLS1204_2
   Web of Science ®Google Scholar
• Krajcik, J., Blumenfeld, P. C., Marx, R. W., Bass, K. M., Fredricks, J., & Soloway, E. (1998). Inquiry in project-based science classrooms: Initial attempts by middle school students. Journal of the Learning Sciences, 7, 313–350. doi: 10.1080/10508406.1998.9672057
   Web of Science ®Google Scholar
• Leonard, M. (2005). Examining tensions in a “design for science” activity system: science versus engineering goals and knowledge. Tidskrift För Lärarutbildning Och Forskning [Journal of Research in Teacher Education], 3, 132–146.
   Google Scholar
• Maas, C. J., & Hox, J. J. (2005). Sufficient sample sizes for multilevel modeling. Methodology, 1(3), 86–92. doi: 10.1027/1614-2241.1.3.86
   Google Scholar
• McAuley, E., Duncan, T., & Tammen, V. V. (1987). Psychometric properties of the intrinsic motivation inventory in a competitive sport setting: A confirmatory factor analysis. Research Quarterly for Exercise and Sport, 60, 48–58. doi: 10.1080/02701367.1989.10607413
   Web of Science ®Google Scholar
• Meece, J. L., Wigfield, A., & Eccles, J. S. (1990). Predictors of math anxiety and its influence on young adolescents’ course enrollment intentions and performance in mathematics. Journal of Educational Psychology, 82(1), 60–70. doi: 10.1037/0022-0663.82.1.60
   Web of Science ®Google Scholar
• Mehalik, M., Doppelt, Y., & Schunn, C. (2008). Middle-school science through design-based learning versus scripted inquiry: Better overall science concept learning and equity gap reduction. Journal of Engineering Education, 97(1), 71–85. doi: 10.1002/j.2168-9830.2008.tb00955.x
   Web of Science ®Google Scholar
• Mentzer, N., Becker, K., & Sutton, M. (2015). Engineering design thinking: High school students’ performance and knowledge. Journal of Engineering Education, 104(4), 417–432. Retrieved from http://doi.org/10.1002/jee.20105 doi: 10.1002/jee.20105
   Web of Science ®Google Scholar
• Moore, T. J., Glancy, A. W., Tank, K. M., Kersten, J. A., Smith, K. A., & Stohlmann, M. S. (2014). A framework for quality K-12 engineering education: Research and development. Journal of Pre-College Engineering Education Research (J-PEER), 4(1), Article 2. Retrived from http://docs.lib.purdue.edu doi: 10.7771/2157-9288.1069
   Google Scholar
• Nathan, M. J., Srisurichan, R., Walkington, C., Wolfgram, M., Williams, C., & Alibali, M. W. (2013). Building cohesion across representations: A mechanism for STEM integration. Journal of Engineering Education, 102(1), 77–116. Retrieved from http://doi.org/10.1002/jee.20000 doi: 10.1002/jee.20000
   Web of Science ®Google Scholar
• National Academy of Engineering, & National Research Council. (2009). Engineering in K-12 education: Understanding the status and improving the prospects. Washington, DC: National Academies Press. Retrieved from http://www.nap.edu/catalog.php?record_id=12635
   Google Scholar
• National Academy of Engineering, & National Research Council. (2014). STEM integration in K-12 education: Status, prospects, and an agenda for research. Washington, DC: The National Academies Press. Retrieved from http://www.nap.edu/openbook.php?record_id=18612&page=52
   Google Scholar
• National Research Council, J. (1999). How people learn: Brain, mind, experience, and school. Washington, DC: National Academies Press.
   Google Scholar
• National Research Council. (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. Washington, DC: National Academies Press.
   Google Scholar
• NGSS Lead States. (2013). Next generation science standards: For states, by states. Washington, DC: The National.
   Google Scholar
• Noftle, E. E., & Robins, R. W. (2007). Personality predictors of academic outcomes: Big five correlates of GPA and SAT scores. Journal of Personality and Social Psychology, 93(1), 116–130. Retrieved from https://doi.org/10.1037/0022-3514.93.1.116 doi: 10.1037/0022-3514.93.1.116
   PubMed Web of Science ®Google Scholar
• Penner, D. E., Giles, N. D., Lehrer, R., & Schauble, L. (1997). Building functional models: Designing an elbow. Journal of Research in Science Teaching, 34(2), 125–143. doi: 10.1002/(SICI)1098-2736(199702)34:2<125::AID-TEA3>3.0.CO;2-V
   Web of Science ®Google Scholar
• Penner, D. E., Schauble, L., & Lehrer, R. (1998). From physical models to biomechanics: A design-based modeling approach. Journal of the Learning Sciences, 7, 429–449. doi: 10.1080/10508406.1998.9672060
   Web of Science ®Google Scholar
• Prevost, A., Nathan, M. J., Stein, B., Tran, N., & Phelps, L. A. (2009). Integration of mathematics in pre-college engineering: The search for explicit connections. Proceedings of the American Society of Engineering Education (ASEE), 2009, 1763–1790.
   Google Scholar
• Project Lead the Way. (2013, October 1). Project lead the way [Text]. Retrieved September 30, 2014, from https://www.pltw.org/our-programs
   Google Scholar
• Puntambekar, S., & Kolodner, J. L. (2005). Toward implementing distributed scaffolding: Helping students learn science from design. Journal of Research in Science Teaching, 42(2), 185–217. Retrieved from http://doi.org/10.1002/tea.20048 doi: 10.1002/tea.20048
   Web of Science ®Google Scholar
• Raudenbush, S. W., Bryk, A. S., & Congdon, R. (2004). HLM 6 for windows. Skokie, IL: Scientific Software International.
   Google Scholar
• Reeve, J., Jang, H., Hardre, P., & Omura, M. (2002). Providing a rationale in an autonomy-supportive way as a strategy to motivate others during an uninteresting activity. Motivation and Emotion, 26(3), 183–207. Retrieved from http://doi.org/10.1023/A:1021711629417 doi: 10.1023/A:1021711629417
   Web of Science ®Google Scholar
• Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138 (2), 353–387. Retrieved from https://doi.org/10.1037/a0026838 doi: 10.1037/a0026838
   PubMed Web of Science ®Google Scholar
• Roth, W.-M. (1996). Art and artifact of children’s designing: A situated cognition perspective. The Journal of the Learning Sciences, 5(2), 129–166. doi: 10.1207/s15327809jls0502_2
   Web of Science ®Google Scholar
• Ryan, R. M. (1982). Control and information in the intrapersonal sphere: An extension of cognitive evaluation theory. Journal of Personality and Social Pscyhology, 43, 450–461. doi: 10.1037/0022-3514.43.3.450
   Web of Science ®Google Scholar
• Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. The American Psychologist, 55(1), 68–78. doi: 10.1037/0003-066X.55.1.68
   PubMed Web of Science ®Google Scholar
• Schank, R. C. (1982). Dynamic memory: A theory of reminding and learning in computers and people. New York, NY: Cambridge University Press.
   Google Scholar
• Schnittka, C., & Bell, R. (2011). Engineering design and conceptual change in science: Addressing thermal energy and heat transfer in eighth grade. International Journal of Science Education, 33(13), 1861–1887. Retrieved from http://doi.org/10.1080/09500693.2010.529177 doi: 10.1080/09500693.2010.529177
   Web of Science ®Google Scholar
• Silk, E. M., Schunn, C. D., & Strand Cary, M. (2009). The impact of an engineering design curriculum on science reasoning in an Urban setting. Journal of Science Education and Technology, 18(3), 209–223. Retrieved from http://doi.org/10.1007/s10956-009-9144-8 doi: 10.1007/s10956-009-9144-8
   Web of Science ®Google Scholar
• Simpkins, S. D., Davis-Kean, P. E., & Eccles, J. S. (2006). Math and science motivation: A longitudinal examination of the links between choices and beliefs. Developmental Psychology, 42(1), 70–83. Retrieved from http://doi.org/10.1037/0012-1649.42.1.70 doi: 10.1037/0012-1649.42.1.70
   PubMed Web of Science ®Google Scholar
• Steingut, R. R., Patall, E. A., & Trimble, S. S. (in press). The Effect of Rationale on Motivation and Performance Outcomes: A Meta-Analysis. Motivation Science
   Google Scholar
• Stern, L., & Roseman, J. E. (2004). Can middle-school science textbooks help students learn important ideas? Findings from project 2061’s curriculum evaluation study: Life science. Journal of Research in Science Teaching, 41(6), 538–568. Retrieved from http://doi.org/10.1002/tea.20019 doi: 10.1002/tea.20019
   Web of Science ®Google Scholar
• Tran, N. A., & Nathan, M. J. (2010). Pre-college engineering studies: An investigation of the relationship between pre-college engineering studies and student achievement in science and mathematics. Journal of Engineering Education, 99(2), 143–157. Retrieved from http://doi.org/10.1002/j.2168-9830.2010.tb01051.x doi: 10.1002/j.2168-9830.2010.tb01051.x
   Web of Science ®Google Scholar
• Trautwein, U., Lüdtke, O., Kastens, C., & Köller, O. (2006). Effort on homework in grades 5–9: Development, motivational antecedents, and the association with effort on classwork. Child Development, 77(4), 1094–1111. Retrieved from http://doi.org/10.1111/j.1467-8624.2006.00921.x doi: 10.1111/j.1467-8624.2006.00921.x
   PubMed Web of Science ®Google Scholar
• Wendell, K., & Rogers, C. (2013). Engineering design-based science, science content performance, and science attitudes in elementary school: Engineering design-based science in elementary school. Journal of Engineering Education, 102(4), 513–540. Retrieved from http://doi.org/10.1002/jee.20026 doi: 10.1002/jee.20026
   Web of Science ®Google Scholar
• Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68–81. Retrieved from http://doi.org/10.1006/ceps.1999.1015 doi: 10.1006/ceps.1999.1015
   PubMed Web of Science ®Google Scholar
• Yadav, A., Subedi, D., Lundeberg, M. A., & Bunting, C. F. (2011). Problem-based learning: Influence on students’ learning in an electrical engineering course. Journal of Engineering Education, 100(2), 253–280. Retrieved from http://doi.org/10.1002/j.2168-9830.2011.tb00013.x doi: 10.1002/j.2168-9830.2011.tb00013.x
   Web of Science ®Google Scholar