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The CLEM model: Path analysis of the mediating effects of attitudes and motivational beliefs on the relationship between perceived learning environment and course performance in an undergraduate non-major biology course

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Abstract

In this study, the following questions were addressed in an undergraduate non-major biology course using a large lecture format: Is there a relationship between students’ perceptions of their learning environment and course performance, and what roles do motivation and attitudes play in mediating that relationship? The purpose of this study was to test a path model describing the mediating effects of motivation and attitudes on learning environments and course performance. The study considered contemporary understanding of teaching and learning, as well as motivation and attitudes, in suggesting a direction for future reform efforts and to guide post-secondary science education instructors and leaders in the design of learning environments for undergraduate non-major biology courses. Among the classroom learning environment variables assessed in this study, personal relevance was the major contributor to predicting attitudes, motivation and course performance. Although the classroom learning environment had a very weak direct effect on course performance, there was a moderate total effect on self-efficacy and intrinsic goal orientation. The classroom learning environment also had a moderate total effect on attitudes toward biology. Attitudes toward biology had a moderate direct effect on self-efficacy. While attitudes toward biology was significantly correlated with course performance, the direct effect was extremely weak and was dropped from the model. However, attitudes toward biology had a moderate indirect effect on course performance due to the mediating effects of self-efficacy. Self-efficacy had a strong direct effect on course performance and therefore seemed to be particularly important. The model tested in this study explained 33 % of the variance in course performance, 56 % of the variance in self-efficacy, 24 % of the variance in attitudes toward biology, and 18 % of the variance in intrinsic goal orientation. To improve course performance, instructors should focus on building self-efficacy among their students and ensure that students find the course personally relevant.

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References

  • Aldridge, J. M., Fraser, B. J., Taylor, P. C., & Chen, C. (2000). Constructivist learning environments in a crossnational study in Taiwan and Australia. International Journal of Science Education, 22, 37–55.

    Article  Google Scholar 

  • American Association for the Advancement of Science. (1990). The liberal art of science: Agenda for action. Washington, DC: Author.

    Google Scholar 

  • Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84, 261–271.

    Article  Google Scholar 

  • Angelo, T. A. (1990). Classroom assessment: Improving learning quality where it matters most. New Directions for Teaching and Learning, 42, 71–82.

    Article  Google Scholar 

  • Angelo, T. A., & Cross, K. P. (1993). Classroom assessment techniques: A handbook for college teachers (2nd ed.). San Francisco, CA: Jossey-Bass.

    Google Scholar 

  • Apedoe, X. S., & Reeves, T. C. (2006). Inquiry-based learning and digital libraries in undergraduate science education. Journal of Science Education and Technology, 15, 321–330.

    Article  Google Scholar 

  • Bandura, A. (1997). Self-efficacy. Harvard Mental Health Letter, 13(9), 4.

    Google Scholar 

  • Bandura, A. (2006). Toward a psychology of human agency. Perspectives on Psychological Science, 1, 164–180.

    Article  Google Scholar 

  • Bandura, A., Adams, N. E., & Beyer, J. (1977). Cognitive processes mediating behavioral change. Journal of Personality and Social Psychology, 35, 125–139.

    Article  Google Scholar 

  • Beatty, A. (1997). Learning from TIMSS: Results of the third international mathematics and science study. Washington, DC: National Academy of Sciences, National Research Council.

    Google Scholar 

  • Black, A. E., & Deci, E. L. (2000). The effects of instructors’ autonomy support and students’ autonomous motivation on learning. Science Education, 84, 740–756.

    Article  Google Scholar 

  • Bodner, G. M. (1986). Constructivism: A theory of knowledge. Journal of Chemical Education, 63(10), 873–878.

    Article  Google Scholar 

  • Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How people learn. Washington, DC: National Academy Press.

  • Bybee, R. W. (1993). Leadership, responsibility, and reform in science education. Science Educator, 2, 1–9.

    Google Scholar 

  • Campbell, J. R., Voelkl, K. E., & Donahue, P. L. (1997). NAEP 1996 trends in academic progress. Achievement of U.S. students in science, 1969 to 1996; mathematics, 1973 to 1996; reading, 1971 to 1996; writing, 1984 to 1996. Princeton, NJ: Educational Testing Service.

  • Caprio, M. W. (1994). Easing into constructivism. Journal of College Science Teaching, 23, 210–212.

    Google Scholar 

  • Daempfle, P. A. (2004). An analysis of the high attrition rates among first year college science, math, and engineering majors. Journal of College Student Retention, 5(1), 37–52.

    Article  Google Scholar 

  • Davis, J. A. (1985). The logic of causal order. Beverly Hills, CA: Sage Publications.

    Google Scholar 

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

    Google Scholar 

  • 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, 227–268.

    Article  Google Scholar 

  • Donovan, M. S., Bransford, J. D., & Pellegrino, J. W. (1999). How people learn: Bridging research and practice. Washington, DC: National Academy of Sciences, National Research Council.

    Google Scholar 

  • Dorman, J., & Adams, J. (2004). Associations between students’ perceptions of classroom environment and academic efficacy in Australian and British secondary schools. Westminster Studies in Education, 27, 69–85.

    Google Scholar 

  • Druger, M., & Dick, T. (2004). Collegiate science and mathematics learning and teaching (part 2). School Science & Mathematics, 104, 305–306.

    Article  Google Scholar 

  • Fennema, E., & Leder, G. C. (1990). Mathematics and gender. Teachers, New York: College Press.

    Google Scholar 

  • Flowerday, T., Schraw, G., & Stevens, J. (2004). The role of choice and interest in reader engagement. Journal of Experimental Education, 72, 93–114.

    Article  Google Scholar 

  • Fraser, B. J. (1998). Classroom environment instruments: Development, validity and applications. Learning Environments Research, 1, 7–34.

    Article  Google Scholar 

  • Fraser, B. J., & Kahle, J. B. (2007). Classroom, home and peer environment influences on student outcomes in science and mathematics: An analysis of systemic reform data. International Journal of Science Education, 29, 1891–1909.

    Article  Google Scholar 

  • Fraser, B. J., & Walberg, H. J. (2005). Research on teacher–student relationships and learning environments: Context, retrospect and prospect. International Journal of Educational Research, 43, 103–109.

    Article  Google Scholar 

  • French, D., Cheesman, I., Swails, N., Thomas, J., & Cheesman, K. (2007). Is there any common curriculum for undergraduate biology majors in the 21st century? BioScience, 57, 516–522.

    Article  Google Scholar 

  • Glasson, G. E., & Lalik, R. V. (1993). Reinterpreting the learning cycle from a social constructivist perspective: A qualitative study of teachers’ beliefs and practices. Journal of Research in Science Teaching, 30, 187–207.

    Article  Google Scholar 

  • Gore, A. (2007). The assault on reason. New York: Penguin Press.

    Google Scholar 

  • Gore, A. (2008). An inconvenient truth. Vital Speeches of the Day, 74(2), 55–58.

    Google Scholar 

  • Governor’s commission on higher education and the economy. Retrieved 6/16/2008, 2008, from http://www.chee.ohio.gov/.

  • Haladyna, T., Olsen, R., & Shaughnessy, J. (1982). Relations of student, teacher, and learning environment variables to attitudes toward science. Science Education, 66, 672–687.

    Google Scholar 

  • Hanuscin, D. L., Akerson, V. L., & Phillipson-Mower, T. (2006). Integrating nature of science instruction into a physical science content course for preservice elementary teachers: NOS views of teaching assistants. Science Education, 90, 912–935.

    Article  Google Scholar 

  • Hewson, P. W., & Tabachnick, B. R. (1999). Educating prospective teachers of biology: Introduction and research methods. Science Education, 83, 247–273.

    Article  Google Scholar 

  • Koestner, R., Weinberger, J., & McClelland, D. C. (1991). Task-intrinsic and social-extrinsic sources of arousal for motives assessed in fantasy and self-report. Journal of Personality, 59, 57–82.

    Article  Google Scholar 

  • Lawson, A. E. (1992). Using reasoning ability as the basis for assigning laboratory partners in nonmajors biology. Journal of Research in Science Teaching, 29, 729–741.

    Article  Google Scholar 

  • Lawson, A. E., Baker, W. P., Didonato, L., Verdi, M. P., & Johnson, M. A. (1993). The role of hypothetico-deductive reasoning and physical analogues of molecular interactions in conceptual change. Journal of Research in Science Teaching, 30, 1073–1085.

    Article  Google Scholar 

  • Lawson, A. E., Rissing, S. W., & Faeth, S. H. (1990). An inquiry approach to non-majors’ biology. Journal of College Science Teaching, 19, 340–346.

    Google Scholar 

  • Lemke, J. L. (2001). Articulating communities: Sociocultural perspectives on science education. Journal of Research in Science Teaching, 38, 296–316.

    Article  Google Scholar 

  • Leonard, W. H. (1989). Research and teaching: Ten years of research on investigative laboratory instruction strategies. Journal of College Science Teaching, 18, 304–306.

    Google Scholar 

  • Lepper, M. R., & Hoddell, M. (1988). Instrinsic motivation in the classroom. In C. Ames & R. Ames (Eds.), Research on motivation in education (pp. 75–105). New York: Academic.

    Google Scholar 

  • Lester, F. K., Jr., & Garofalo, J. (1987, April). The influence of affects, beliefs, and metacognition on problem solving behavior: Some tentative speculations. Paper presented at the annual meeting of the American Educational Research Association, Washington, DC.

  • Lord, T. R. (1994). Using constructivism to enhance student learning in college biology. Journal of College Science Teaching, 23, 346–348.

    Google Scholar 

  • Lorsbach, A., & Tobin, K. (1995). Toward a critical approach to the study of learning environments in science classrooms. Research in Science Education, 25(1), 19–32.

    Google Scholar 

  • Mattern, N., & Schau, C. (2002). Gender differences in science attitude-achievement relationships over time among white middle-school students. Journal of Research in Science Teaching, 39, 324–340.

    Article  Google Scholar 

  • McLean, M., & Van Wyk, J. (2006). Twelve tips for recruiting and retaining facilitators in a problem-based learning programme. Medical Teacher, 28, 675–679.

    Article  Google Scholar 

  • Mitchell, M. (1997, March). Situational interest in the statistics classroom. Paper presented at the Annual Meeting of the American Educational Research Association, Chicago, IL.

  • Montgomery, H. (2005). Constructivist pedagogical preferences of undergraduate students in geoscience service courses at the University of Texas at Dallas. Texas Science Teacher, 34, 25–30.

    Google Scholar 

  • Myers, R. E., I. I. I., & Fouts, J. T. (1992). A cluster analysis of high school science classroom environments and attitude toward science. Journal of Research in Science Teaching, 29, 929–937.

    Article  Google Scholar 

  • National Research Council. (1996). National science education standards. Washington, DC: Author.

    Google Scholar 

  • Nix, R., Fraser, B., & Ledbetter, C. (2005). Evaluating an integrated science learning environment using the constructivist learning environment survey. Learning Environments Research, 8, 109–133.

    Article  Google Scholar 

  • Nussbaum, J., & Novick, S. (1982). Alternative frameworks, conceptual conflict and accommodation: Toward a principled teaching strategy. Instructional Science, 11, 183–200.

    Article  Google Scholar 

  • Ohio Board of Regents. (2006a). A policymaker’s guide to higher education in Ohio: 2006. Retrieved 11/01/2007, from http://www.regents.state.oh.us/policymakersguide.

  • Ohio Board of Regents. (2006b). Economic growth Challenge/Innovation incentive: Implementing the incentive. Columbus, OH: Ohio Board of Regents.

  • Ohio Board of Regents, C. (2007). Results through productivity report for Ohio public higher education, 2007. Columbus, OH: Ohio Board of Regents.

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

    Article  Google Scholar 

  • Palmer, D. (2005). A motivational view of constructivist‐informed teaching. International Journal of Science Education, 27, 1853–1881.

    Article  Google Scholar 

  • Papanastasiou, C., & Papanastasiou, E. C. (2002). The process of science achievement. Science Education International, 13, 12–24.

    Google Scholar 

  • Papanastasiou, C., & Papanastasiou, E. C. (2004). Major influences on attitudes toward science. Educational Research & Evaluation, 10, 239–257.

    Article  Google Scholar 

  • Piaget, J. (1954). The construction of reality in the child. New York: Basic Books.

    Book  Google Scholar 

  • Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). Motivated strategies for learning questionnaire. Ann Arbor, MI: National Center for Research to Improve Postsecondary Teaching and Learning.

    Google Scholar 

  • Romberg, T. A. (1998). Comments: NCTM’s curriculum and evaluation standards. Teachers College Record, 100(1), 8.

    Google Scholar 

  • Roth, W. (1994). Experimenting in a constructivist high school physics laboratory. Journal of Research in Science Teaching, 31, 197–223.

    Article  Google Scholar 

  • Russell, J., & Hollander, S. (1975). A biology attitude scale. American Biology Teacher, 37, 270–273.

    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 

  • Ryan, R. M., & Grolnick, W. S. (1986). Origins and pawns in the classroom: Self-report and projective assessments of individual differences in children’s perceptions. Journal of Personality and Social Psychology, 50, 550–558.

    Article  Google Scholar 

  • Schunk, D. H., & Zimmerman, B. J. (1997). Social origins of self-regulatory competence. Educational Psychologist, 32, 195–208.

    Article  Google Scholar 

  • Seymour, E. (1995). Revisiting the `problem iceberg’: Science, mathematics, and engineering students still chilled out. Journal of College Science Teaching, 24, 392–400.

    Google Scholar 

  • Seymour, E., & Hewitt, N. M. (2000). Talking about leaving: Why undergraduates leave the sciences. Boulder, CO: Westview Press.

    Google Scholar 

  • Shrigley, R. L. (1990). Attitude and behavior are correlates. Journal of Research in Science Teaching, 27, 97–113.

    Article  Google Scholar 

  • Talton, E. L., & Simpson, R. D. (1987). Relationships of attitude toward classroom environment with attitude toward and achievement in science among tenth grade biology students. Journal of Research in Science Teaching, 24, 507–525.

    Article  Google Scholar 

  • Taylor, P. C. S., Fraser, B. J., & & White, L. R. (1994, April). A classroom environment questionnaire for science educators interested in the constructivist reform of school science. Paper presented at the Annual Meeting of the National Association for Research in Science Teaching, Anaheim, CA.

  • Tuckman, B. W., & Sexton, T. L. (1991, April). Motivating student performance: The influence of grading criteria and assignment length limit. Paper presented at the Annual Meeting of the American Educational Research Association. Chicago, IL.

  • Von Glasersfeld, E. (1995). Radical constructivism: A way of knowing and learning (Studies in Mathematics Education Series: 6). Bristol, PA: Falmer Press.

    Book  Google Scholar 

  • Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Wainwright, C., Morrell, P. D., Flick, L., & Schepige, A. (2004). Observation of reform teaching in undergraduate level mathematics and science courses. School Science & Mathematics, 104, 322–335.

    Article  Google Scholar 

  • Walczyk, J. J., Ramsey, L. L., & Zha, P. (2007). Obstacles to instructional innovation according college science and mathematics faculty. Journal of Research in Science Teaching, 44, 85–106.

    Article  Google Scholar 

  • Weinburgh, M. (1995). Gender differences in student attitudes toward science: A meta-analysis of the literature from 1970–1991. Journal of Research in Science Teaching, 32, 387–398.

    Article  Google Scholar 

  • Yager, R., Kaya, O. N., & Dogan, A. (2007). College science teaching changing to mirror real science in Turkish higher education. Journal of College Science Teaching, 36(7), 50–54.

    Google Scholar 

  • Zusho, A., Pintrich, P. R., & Goppola, B. (2003). Skill and will: The role of motivation and cognition in the learning of college chemistry. International Journal of Science Education, 25, 1081–1094.

    Article  Google Scholar 

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  1. 217 Life Science Building, Department of Biological Sciences, Bowling Green State University, Bowling Green, OH, 43403, USA

    Matthew L. Partin

  2. 137 Life Science Building, Education/Division of Teaching & Learning, Bowling Green State University, Bowling Green, OH, 43403, USA

    Jodi J. Haney

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  1. Matthew L. Partin
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Partin, M.L., Haney, J.J. The CLEM model: Path analysis of the mediating effects of attitudes and motivational beliefs on the relationship between perceived learning environment and course performance in an undergraduate non-major biology course. Learning Environ Res 15, 103–123 (2012). https://doi.org/10.1007/s10984-012-9102-x

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