Modeling the Transition from a Phenotypic to Genotypic Conceptualization of Genetics in a University-Level Introductory Biology Context
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Identifying contingencies between constructs in a multi-faceted learning progression (LP) is a challenging task. Often, there is not enough evidence in the literature to support connections, and once identified, they are difficult to empirically test. Here, we use causal model search to evaluate how connections between ideas in a genetics LP change over time in the context of an introductory biology course. We identify primary and secondary hub ideas and connections between concepts before and after instruction to illustrate how students moved from a phenotypic grounding of genetics knowledge to a more genotypic grounding of their genetics knowledge after instruction. We discuss our results in light of conceptual change and illustrate the importance of understanding students’ idea structures within a domain.
KeywordsGenetics Learning progressions Causal model search Bayesian networks
We would like to thank the Center for Causal Discovery, supported by grant U54HG008540, for providing open access to its software TETRAD and for methodological assistance. We would like to thank Gretchen Haas for valuable feedback on this study.
- Briggs, D. C., Alonzo, A. C., Schwab, C., & Wilson, M. (2006). Diagnostic assessment with ordered multiple choice items. Educational Assessment, 11(1), 33–63.Google Scholar
- Castro-Faix, M., Rothman, J., Seryapov, R., & Duncan, R. G. (2016). Data driven refinements of a genetics learning progression: Mapping an understanding of classical genetics. Paper presented at the Annual Meeting of the National Association for Research in Science Teaching, Baltimore, MD.Google Scholar
- Choi, J J., Duncan, R. G., Castro-Faix, M., & Cavera, V. L. (2016a). Validity evidence for assessments of a genetics learning progression. Paper presented at the Annual Meeting of the American Educational Research Association, Washington, DC.Google Scholar
- Choi, J., Duncan, R G., Castro-Faix, M., Cavera V. (2016b). Using alternative instructional sequences to test a learning progression in genetics. Paper presented at the Annual Meeting of the National Association for Research in Science Teaching, Baltimore, MD.Google Scholar
- Corcoran, T. B., Mosher, F. A., & Rogat, A. D. (2009). Learning progressions in science: An evidence-based approach to reform. New York, NY: Columbia University, Teachers College, Center on Continuous Instructional Improvement.Google Scholar
- Duit, R. (2009). Bibliography–STCSE. Students’ and Teachers’ Conceptions and Science Education (http://www.ipn.uni-kiel.de/aktuell/stcse/download_stcse.html).Google Scholar
- Duncan, R. G., Castro-Faix, M., & Choi, J. (2016). Informing a learning progression in genetics: Which should be taught first, Mendelian inheritance or the central dogma of molecular biology? International Journal of Science and Mathematics Education, 14(3), 445–472.Google Scholar
- Elrod, S. (2007). Genetics Concept Inventory. http://bioliteracy.colorado.edu/Readings/papersSubmittedPDF/Elrod.pdf (accessed 20 July 2013).
- Glymour, C., Scheines, Spirtes, P. Ramsey, J. TETRAD [Computer software] (2016). Center for Causal Discovery. Retrieved from http://www.phil.cmu.edu/tetrad/current.html
- Guttman, L. (1950). The principal components of scale analysis. In S. A. Stouffer, L. Guttman, E. A. Suchman, P. F. Lazarsfeld, S. A. Star, & J. A. Clausen (Eds.), Measurement and prediction (pp. 312–361). New York: Wiley.Google Scholar
- Human Genetics Commission [HGC]. (2001). Public attitudes to human genetic information: People’s Panel quantitative study conducted for the Human Genetics Commission.Google Scholar
- Klymkowsky, M. W., Underwood, S. M., & Garvin-Doxas, R. K. (2010). Biological Concepts Instrument (BCI): A diagnostic tool for revealing student thinking. arXiv preprint arXiv:1012.4501.Google Scholar
- Manthey, S., Brewe, E., Traxler, A. L., Kramer, L. H., O'Brien, G., von Wettberg, E., & Lowenstein, M. (2014). A Multi-Measure Assessment of Course Type Efficacy between Traditional Lecture and Online Instruction General Biology I at a Large Public Hispanic-Serving University. http://www.academia.edu/download/34548053/Manthey2014_SABER.pdf.
- National Research Council [NRC]. (2011). 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. National Academies Press.Google Scholar
- Petty, E. M., Kardia, S. R., Mahalingham, R., Pfeffer, C. A., Saksewski, S. L., Brandt, M. G., … & Jayaratne, T. E. (2000a, October). Public understanding of genes and genetics: Implications for the utilization of genetic services and technology. In American Journal of Human Genetics (Vol. 67, No. 4, pp. 253–253). 5720 SOUTH WOODLAWN AVE, CHICAGO, IL 60637–1603 USA: UNIV CHICAGO PRESS.Google Scholar
- Petty, E. M., Kardia, S. R., Mahalingham, R., Pfeffer, C. A., Saksewski, S. L., Brandt, M. G., Anderson, E. S., & Jayaratne, T. E. (2000b). Public understanding of genes and genetics: Implications for the utilization of genetic services and technology. American Journal of Human Genetics, 4, 253.Google Scholar
- Popper, K. (1957). In C. A. Mace (Ed.), Philosophy of science. British philosophy in the mid-century. London: George Allen and Unwin.Google Scholar
- Raftery, A. E. (1995). Bayesian model selection in social research. Sociological Methodology, 111–163.Google Scholar
- Ramsey, J. D. (2015). Scaling up Greedy Equivalence Search for Continuous Variables. arXiv preprint arXiv:1507.07749.Google Scholar
- Ramsey, J. D., Hanson, S. J., Hanson, C., Halchenko, Y. O., Poldrack, R. A., & Glymour, C. (2010). Six problems for causal inference from fMRI.neuroimage, 49(2), 1545–1558.Google Scholar
- Rogat, A., Anderson, C. A., Foster, J., Goldberg, F., Hicks, J., Kanter, D., … Wiser, M. (2011). Developing learning progressions in support of new science standards. A RAPID workshop series. Consortium for Policy Research in Education. Retrieved from http://eric.ed.gov/?id=ED536834.
- Romine, W. L., Schaffer, D. L., & Barrow, L. (2015). Development and application of a novel Rasch-based methodology for evaluating multi-tiered assessment instruments: Validation and utilization of an undergraduate diagnostic test of the water cycle. International Journal of Science Education, 37(16), 2740–2768.Google Scholar
- Roseman, J. E., Caldwell, A., Gogos, A., & Kurth, L. (2006). Mapping a coherent learning progression for the molecular basis of heredity. Paper presented at the annual meeting of the National Association for research in science teaching. San Francisco: CA.Google Scholar
- Songer, N. B., Kelcey, B., & Gotwals, A. W. (2009). How and when does complex reasoning occur? Empirically driven development of a learning progression focused on complex reasoning about biodiversity. Journal of Resarch in Science Teaching, 46(6), 610–631.Google Scholar
- Stewart, J., Cartier, J. L., & Passmore, C. M. (2005). Developing understanding through model-based inquiry. In M. S. Donovan & J. D. Branford (Eds.), How students learn (pp. 515-565). Washington DC: National Research Council.Google Scholar
- Todd, A. N. (2013). The molecular genetics learning progressions: Revisions and refinements based on empirical testing in three 10th grade classrooms. Doctoral dissertation, Wright State University, Dayton, OH.Google Scholar
- Todd, A. & Kenyon, L. (2016). Empirical refinements of a molecular genetics learning progression: The molecular constructs. Journal of Research in Science Teaching, 53(9), 1385-1418.Google Scholar
- Todd, A. & Romine W. (2016). Validation of the Learning Progression-based Assessment of Modern Genetics (LPA-MG) in a college context. International Journal of Science Education, 38(10), 1673–1698.Google Scholar
- Todd, A., & Romine, W. (2017). Empirical validation of a modern genetics progression web for college biology students. International Journal of Science Education. doi: 10.1080/09500693.2017.1296207.
- Todd, A., Romine, W., & Cook Whitt, K. (2017). Development and validation of the Learning Progression-based Assessment of Modern Genetics (LPA-MG) in a high school context. Science Education, 101(1), 32–65.Google Scholar