Abstract
Employers in Science, Technology, Engineering, and Mathematics (STEM) fields report that recent graduates are deficient in important skills such as collaboration and professional writing. Scientific societies and science educators have responded to the gap between student skills and employer expectations by recommending that undergraduate STEM curricula focus on cross-disciplinary, workplace-related skills in addition to discipline-specific skills and content knowledge. This study examined the disciplinary cultures in which STEM faculty teach and STEM students learn. We developed and validated the Survey of Teaching Beliefs and Practices for Undergraduates (STEP-U), which assesses the extent to which students value specific cross-disciplinary skills, as well as their experiences with teaching practices thought to reinforce such skills. We surveyed > 2000 students majoring in biological sciences, chemistry, physics, mathematics, and computer science. We interviewed five students from each discipline to supplement survey data. Next, we surveyed faculty members (N = 147) within these disciplines regarding the extent to which they valued the same cross-disciplinary skills and how this influenced their teaching practices. Student values differed according to academic discipline, classroom experiences, and individual characteristics, such as prior research experience. We offer a conceptual framework by which the relationship between faculty values, faculty teaching practices, and student values can be studied. Specifically, it predicts that faculty values are embodied in their teaching practices, and student values are shaped by their classroom experiences, leading to transmission of disciplinary values from faculty to students. Future studies should examine these relationships across different disciplines and institution types.
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Notes
Cohen (1988) considers ηp2 to indicate a small effect if at least .02, a medium effect if at least .13, and a large effect if at least .26.
References
Adedokun, O. A., Bessenbacher, A. B., Parker, L. C., Kirkham, L. L., & Burgess, W. D. (2013). Research skills and STEM undergraduate research students aspirations for research careers: mediating effects of research self-efficacy. Journal of Research in Science Teaching, 50(8), 940–951.
American Association for the Advancement of Science [AAAS]. (2011). Vision and change in undergraduate biology education: a call to action. Washington, DC: AAAS Retrieved from http://visionandchange.org/files/2013/11/aaas-VISchange-web1113.pdf. Accessed 15 April 2019.
American Chemical Society Committee on Professional Training (2015).Undergraduate professional education in chemistry: ACS guidelines and evaluation procedures for bachelor’s degree programs. https://www.acs.org/content/dam/acsorg/about/governance/committees/training/2015-acs-guidelines-for-bachelors-degree-programs.pdf. Accessed 15 April 2019.
Armbruster, P., Patel, M., Johnson, E., & Weiss, M. (2009). Active learning and student-centered pedagogy improve student attitudes and performance in introductory biology. CBE Life Sciences Education, 8(3), 203–213.
Association of American Colleges & Universities [AAC&U]. (2019). Creating a 21st–century general education: responding to seismic shifts. https://www.aacu.org/conferences/gened/19. Last accessed March 2019.
Bandura, A. (1997). Self-efficacy: the exercise of control. New York: Freeman.
Bangera, G., & Brownell, S. E. (2014). Course-based undergraduate research experiences can make scientific research more inclusive. CBE Life Sciences Education, 13(4), 602–606.
Becher, T. (1994). The significance of disciplinary differences. Studies in Higher Education, 19(2), 151–161.
Biggs, J. B. (1987). Student approaches to learning and studying. Hawthorn: Australian Council for Educational Research.
Biglan, A. (1973). Relationships between subject matter characteristics and the structure and output of university departments. The Journal of Applied Psychology, 57(3), 204–213.
Bloom, B. (1984). Taxonomy of educational objectives, handbook, 1.
Brownell, S. E., & Tanner, K. D. (2012). Barriers to faculty pedagogical change: lack of training, time, incentives, and… tensions with professional identity? CBE Life Sciences Education, 11(4), 339–346.
Chamorro-Premuzic, T., Arteche, A., Bremner, A. J., Greven, C., & Furnham, A. (2010). Soft skills in higher education: Importance and improvement ratings as a function of individual differences and academic performance. Educational Psychology: An International Journal of Experimental Educational Psychology, 30(2), 221–241.
Charette, R. N. (2015). STEM graduates not workforce ready? Employers should look in the mirror as to why. Retrieved from https://www.advanc-ed.org/source/stem-graduates-not-workforce-ready-employers-should-look-mirror-why.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates.
Computing Curricula. (2001). Computer science, final report, the joint task force on computing curricula. IEEE Computer Society and Association for Computing Machinery, IEEE Computer Society.
Computing Curricula. (2005). The overview report. A volume of the Computing Curricula Series.–A cooperative project of the ACM, the AIS, the IEEE-CS.
Denofrio, L. A., Russell, B., Lopatto, D., & Lu, Y. (2007). Linking student interests to science curricula. Science, 318(5858), 1872–1873.
Donald, J. G. (1997). Improving the environment for learning: academic leaders talk about what works. San Francisco, CA: Jossey-Bass.
Feather, N. T. (1988). Values, valences, and course enrollment: Testing the role of personal values within an expectancy-value framework. Journal of Education & Psychology, 80(3), 381–391.
Finch, D. J., Hamilton, L. K., Baldwin, R., & Zehner, M. (2013). An exploratory study of factors affecting undergraduate employability. Education and Training, 55(7), 681–704.
Finelli, C. J., DeMonbron, M., Shekhar, P., Borrego, M., Henderson, C., Prince, M., Waters, C. K. (2014). A classroom observation instrument to assess student response to active learning. In: Frontiers in education conference (FIE), IEEE, 1–4.
Gray, F. E., Emerson, L., & MacKay, B. (2005). Meeting the demands of the workplace: science students and written skills. Journal of Science Education and Technology, 14(4), 425–435.
Hart Research Associates. (2015). Falling short? College learning and career success. https://www.aacu.org/sites/default/files/files/LEAP/2015employerstudentsurvey.pdf. Accessed 15 April 2019.
Hart Research Associates. (2018). Fulfilling the American dream: liberal education and the future of work. https://www.aacu.org/sites/default/files/files/LEAP/2018EmployerResearchReport.pdf. Accessed 15 April 2019
Hativa, N. (1995). The department-wide approach to improving faculty instruction in higher-education: qualitative evaluation. Research in Higher Education, 36(4), 377–413.
Henderson, C., & Dancy, M. H. (2007). Barriers to the use of research-based instructional strategies: the influence of both individual and situational characteristics. Physical Review Special Topics - Physics Education Research, 3(2), 020102.
Henderson, C., Beach, A., & Finkelstein, N. (2011). Facilitating change in undergraduate STEM instructional practices: an analytic review of the literature. Journal of Research in Science Teaching, 48(8), 952–984.
Heron, H et al (2016). Joint Task Force on Undergraduate Physics Programs. Phys21: preparing physics student for 21st-century careers. http://www.compadre.org/JTUPP/report.cfm. Accessed 15 April 2019.
Holland, J. L. (1997). Making vocational choices: a theory of vocational personalities and work environment (3rd ed.). Odessa, FL: Psychological Assessment Resources.
Hora, M. T., Benbow, R. J. & Oleson, A. K. (2016). Beyond the skills gap: preparing college students for life and work. Cambridge, MA: Harvard Education Press.
Jang, H. (2016). Identifying 21st century STEM competencies using workplace data. Journal of Science Education and Technology, 25(2), 284–301.
Kezar, A. (2014). Higher education change and social networks: a review of research. Journal of Higher Education, 85(1), 91–125.
Knorr Cetina, K. (1999). Epistemic cultures: how the sciences make knowledge. Cambridge, MA: Harvard University Press.
Kuh, G. D. (2008). Excerpt from high-impact educational practices: what they are, who has access to them, and why they matter. Association of American Colleges and Universities.
Lievens, F., & Sackett, P. R. (2012). The validity of interpersonal skills assessment via situational judgment tests for predicting academic success and job performance. The Journal of Applied Psychology, 97(2), 460–468.
Lopatto, D. (2007). Undergraduate research experiences support science career decisions and active learning. CBE Life Sciences Education, 6(4), 297–306.
MacPhee, D., Farro, S., & Canetto, S. S. (2013). Academic self-efficacy and performance of underrepresented STEM majors: gender, ethnic, and social class patterns. Analyses of Social Issues and Public Policy, 13(1), 347–369.
Marbach-Ad, G., Schaefer, K. L., & Thompson, K. V. (2012). Faculty teaching philosophies, reported practices, and concerns inform the design of professional development activities of a disciplinary teaching and learning center. Journal on Centers for Teaching and Learning, 4
Marbach-Ad, G., Ziemer, K. S., Orgler, M., & Thompson, K. V. (2014). Science Teaching Beliefs and Reported Approaches within a Research University: Perspectives from Faculty, Graduate Students, and Undergraduates. International Journal of Teaching and Learning in Higher Education, 26(2), 232–250.
Marbach-Ad, G., Rietschel, C., & Thompson, K. V. (2016). Validation and application of the survey of teaching beliefs and practices for undergraduates (STEP-U): Identifying factors associated with valuing important workplace skills among biology students. CBE—Life Sciences Education, 15(4), ar59.
Martinho, M., Albergaria-Almeida, P., & Dias, J. T. (2015). Cooperation and competitiveness in higher education science: does gender matter? Procedia - Social and Behavioral Sciences, 2, 191554–191558.
Mayer, R. E. (2002). Rote versus meaningful learning. Theory Into Practice, 41(4), 226–232.
Maykut, P., Maykut, P. S., Morehouse, R. (1994). Beginning qualitative research: a philosophic and practical guide (Vol. 6). Psychology Press.
McGunagle, D., & Zizka, L. (2018). Meeting real world demands of the global economy: an employer's perspective. Journal of Aviation/Aerospace Education & Research, 27(2), 59–76.
Michaelsen, L. K., Knight, A. B., & Fink, L. D. (2004). Team-based learning: a transformative use of small groups in college teaching. Sterling, VA: Stylus.
Nerland, M., Jensen, K., & Bekele, T. A. (2010). Changing cultures of knowledge and learning in higher education. Department of Educational Research: University of Oslo http://www.uv.uio.no/iped/forskning/prosjekter/eie-utd2020forprosjekt/HEIK-Utd2020-Part2-Changing_cultures.pdf. Accessed 15 April 2019.
Pajares, M. F. (1992). Teachers’ beliefs and educational research: cleaning up a messy construct. Review of Educational Research, 62(3), 307–332.
Pender, M., Marcotte, D. E., Domingo, M. R. S., & Maton, K. I. (2010). The STEM pipeline: the role of summer research experience in minority students' Ph. D. aspirations. Education Policy Analysis Archives, 18(30), 1.
Pike, G. R., Smart, J. C., & Ethington, C. A. (2012). The mediating effects of student engagement on the relationships between academic disciplines and learning outcomes: an extension of Holland’s theory. Research in Higher Education, 53(5), 550–575.
Prinsley, R., & Baranyani, K. (2015). Stem skills in the workforce: what do employers want? Australian Government: Office of Chief Scientist.
Prochaska, J. O. (2013). Transtheoretical model of behavior change. In Encyclopedia of behavioral medicine (pp. 1997-2000). Springer New York.
Prosser, M., & Trigwell, K. (2014). Qualitative variation in approaches to university teaching and learning in large first-year classes. Higher Education, 67(6), 783–795.
Quardokus, K., & Henderson, C. (2015). Promoting instructional change: using social network analysis to understand the informal structure of academic departments. Higher Education, 70(3), 315–335.
Redish, E. F., & Cooke, T. J. (2013). Learning each other's ropes: negotiating interdisciplinary authenticity. CBE Life Sciences Education, 12(2), 175–186.
Robert, J., & Carlsen, W. S. (2017). Teaching and research at a large university: case studies of science professors. Journal of Research in Science Teaching, 54(7), 937–960.
Rokeach, M. (1973). The nature of human values. New-York: Free press.
Rosenberg, S., Heimler, R., & Morote, E. (2012). Basic employability skills: a triangular design approach. Education and Training, 54(1), 7–20.
Saxe, K, & Braddy, L. (2015). A common vision for undergraduate mathematical sciences programs in 2025. https://www.maa.org/sites/default/files/pdf/CommonVisionFinal.pdf. Accessed 15 April 2019
Shekhar, P., Demonbrun, M., Borrego, M., Finelli, C., Prince, M., Henderson, C., & Waters, C. (2015). Development of an observation protocol to study undergraduate engineering student resistance to active learning. International Journal of Engineering Education, 31, 597–609.
Shulman, L. S. (1986). Paradigms and research programs in the study of teaching: a contemporary perspective. Handbook of research on teaching (pp. 3–36). York: Macmillan.
Smart, J. C. (1982). Faculty teaching goals: a test of Holland’s theory. Journal of Education & Psychology, 74(2), 180–188.
Smart, J. C., & Ethington, C. A. (1995). Disciplinary and institutional differences in undergraduate education goals. New Directions for Teaching and Learning, 64, 49–57.
Smart, J. C., & Umbach, P. D. (2007). Faculty and academic environments: using Holland’s theory to explore differences in how faculty structure undergraduate courses. Journal of College Student Development, 48(2), 183–195.
Springer, L., Stanne, M. E., & Donovan, S. S. (1999). Effects of small-group learning in science, mathematics, engineering, and technology: a meta-analysis. Review of Educational Research, 69(1), 21–51.
Stark, J. S. (2000). Planning introductory college courses: content, context, and form. Instructional Science, 28(5), 413–438.
Tanner, K., Chatman, L. S., & Allen, D. (2003). Approaches to cell biology teaching: cooperative learning in the science classroom—Beyond students working in groups. Cell Biology Education, 2(1), 1–5.
Thompson, M. D., & Smart, J. C. (1999). Student competencies emphasized by faculty in disparate academic environments. Journal of College Student Development, 40, 365–376.
Trigwell, K., Prosser, M., & Waterhouse, F. (1999). Relations between teachers' approaches to teaching and students’ approaches to learning. Higher Education, 37(1), 57–70.
Weimer, M. (2013). Learner-centered teaching: five key changes to practice. San Francisco, CA: Jossey-Bass.
Wieman, C. (2017). Improving how universities teach science: lessons from the science education initiative. Harvard University Press.
Wieman, C., Perkins, K., & Gilbert, S. (2010). Transforming science education at large research universities: a case study in progress. Change: The Magazine of Higher Learning, 42(2), 6–14.
Wilson, K. J., Brickman, P., Brame, C. J. (2018). Group work. CBE-Life Sciences Education, 17(1), fel.
Acknowledgments
The preparation of this article was supported in part by a grant from the Howard Hughes Medical Institute Undergraduate Science Education program. This work has been approved by the Institutional Review Board (IRB protocols # 375954-8 and 404045-9). We thank the faculty members and students who participated in this study.
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This research was supported in part by a grant from the Howard Hughes Medical Institute Undergraduate Science Education program (#52008117).
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Marbach-Ad, G., Hunt, C. & Thompson, K.V. Exploring the Values Undergraduate Students Attribute to Cross-disciplinary Skills Needed for the Workplace: an Analysis of Five STEM Disciplines. J Sci Educ Technol 28, 452–469 (2019). https://doi.org/10.1007/s10956-019-09778-8
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DOI: https://doi.org/10.1007/s10956-019-09778-8