Data Driven Approach to Analyze Competency Teaching in an Undergraduate Biology Program: A Case Study
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Abstract
Recent calls to reform undergraduate biology education, including Vision and Change in Undergraduate Biology Education, have led biology departments to examine their curriculum to determine the extent to which it aligns with Vision and Change content and competency recommendations. The recently released BioSkills Guide translates the broad Vision and Change core competencies into more specific program-level learning objectives. Curriculum mapping is the process of surveying courses within a program to determine where content and skills are taught, then analyzing the data to determine how well the curriculum that is actually taught aligns with the planned curriculum. The [INSTITUTION] Biology Department used a new curriculum mapping tool, the BioSkills Curriculum Survey, to examine the extent to which Vision and Change core competencies and BioSkills learning objectives were taught in our courses. Instructors completed the survey for every course they taught in the last two years, enabling us to gather data on competency and learning objective coverage and assessment across our curriculum. We answered questions about where in the curriculum competencies and learning objectives were taught, how different instructors teaching the same course taught learning objectives, the extent to which different learning objectives were assessed, and how teaching learning objectives differed in different tracks and different course levels. For a subset of courses, students also completed a modified survey to determine how students’ perceptions of skills coverage matched instructor’s perceptions. One main finding was that we taught Science and Society learning objectives less than others and, when taught, we did not often assess them. We also found that students’ perceptions of competency teaching did not align well with instructors’ perceptions. The data were used to make informed decisions about ongoing curriculum revisions. This paper illustrates the questions that can be answered using this mapping tool for competencies and we offer recommendations about how a department can take a data-driven approach to curriculum reform.
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References
Allen, M.J. (2004). Assessing Academic Programs in Higher Education. Bolton, MA: Anker Publishing Company, Inc. Retrieved from http://www.ankerpub.com
American Association for the Advancement of Science. (2011). Undergraduate Biology Education: A Call to Action, Final Report, Washington DC. Retrieved from: http://www.visionandchange.org/.
Behr, D., Meitinger, K., Braun, M., and Kaczmirek, L. (2017). Web probing - implementing probing techniques from cognitive interviewing in web surveys with the goal to assess the validity of survey questions (Version 1.0). (GESIS Survey Guidelines). Mannheim: GESIS - Leibniz-Institut für Sozialwissenschaften. https://doi.org/10.15465/gesis- sg_en_023
Black, P., and Wiliam, D. (1998). Inside the black box: Raising standards through classroom assessment. Phi Delta Kappan, 80: 139-148.
[CITATION]
Brancaccio-Taras, L., Pape-Lindstrom, P., Peteroy-Kelly, M., Aguirre, K., Awong-Taylor, J., Balser, T., … Zhao, J. (2016). The PULSE Vision and Change rubrics, version 1.0: A valid and equitable tool to measure transformation of life sciences departments at all institution types. Cell Biology Education—Life Sciences Education, 15(4), ar60. https://doi.org/10.1187/cbe.15-12-0260
Brownell, S.E., Freeman, S., Wenderoth, M.P., and Crowe, A.J. (2014). BioCore guide: A tool for interpreting the core concepts of Vision and Change for biology majors. Cell Biology Education—Life Sciences Education, 13: 200-211. https://doi.org/10.1187/cbe.13-12-0233
Cary, T. and Branchaw, J. (2017). Conceptual elements: A detailed framework to support and assess student learning of biology core concepts. Cell Biology Education—Life Sciences Education, 16:ar24, 1–10 https://doi.org/10.1187/cbe.16-10-0300
Cheesman, K., French, D., Cheesman, I., Swails, N., and Thomas, J. (2007). Is there any common curriculum for undergraduate biology majors in the 21st century? BioScience, 57: 516-522.
Clemmons, A.W., Donovan, D.A., Theobald, E.J., and Crowe, A.J. (in review) Using the Intended-Enacted-Experienced curriculum model to map the Vision and Change core competencies in undergraduate biology programs and courses. Cell Biology Education—Life Sciences Education
Clemmons, A.W., Timbrook, J., Herron, J.C., and Crowe, A.J. (2020). BioSkills Guide: Development and national validation of a tool for interpreting the Vision and Change core competencies. Cell Biology Education—Life Sciences Education. 19:ar53, 1–19. https://doi.org/10.1187/cbe.19-11-0259
Coil, D., Wenderoth, M.P., Cunningham, M., and Dirks, C. (2010). Teaching the process of science: Faculty perceptions and an effective methodology. Cell Biology Education—Life Sciences Education 9: 524-535. https://doi.org/10.1187/cbe.10-01-0005
Couch, B.A., Wright, C.S., Freeman, S., Knight, J.L., Semsar, K., Smith, M.K., Summers, M.M., Zheng, Y., Crowe, A.J., and Brownell, S.E. (2019). GenBio-MAPS: A programmatic assessment to measure student understanding of Vision and Change core concepts across general biology programs. Cell Biology Education—Life Sciences Education, 18:ar1, 1-14. https://doi.org/10.1187/cbe.18-07-0117
Diaz Eaton, C., Highlander, H.C., Dahlquist, K.D., Ledder, G., LaMar, M.D., and Schugart, R.C. (2019). A “Rule-of-Five” framework for models and modeling to unify mathematicians and biologists and improve student learning. PRIMUS. 29: 799-829. https://doi.org/10.1080/10511970.2018.1489318
Dirks, C. and Cunningham, M. (2006). Enhancing diversity is science: Is teaching science process skills the answer? Cell Biology Education—Life Sciences Education. 5: 218-226. https://doi.org/10.1187/cbe.05-10-0121
Gouvea, J. and Passmore, C. (2017). ‘Models of’ versus ‘models for’: Toward an agent-based conception of modeling in the science classroom. Science and Education. 26: 49-63.
Grosslight, L., Unger, C., Jay, E., and Smith, C. (1991). Understanding models and their use in science: Conceptions of middle and high school students and experts. Journal of Research in Science Teaching. 28: 799-822.
Joyner, H.S. (2016). Curriculum mapping: A method to assess and refine undergraduate degree programs. Journal of Food Science Education. 15: 83-100. https://doi.org/10.1111/1541-4329.12086
Killpack, T.L., Fulmer, S.M., Roden, J.A., Dolce, J.L., and Skow, C.D. (2020). Increased scaffolding and inquiry in an introductory biology lab enhance experimental design skills and sense of scientific ability. Journal of Microbiology and Biology Education. 21: 1-10. https://journals.asm.org/doi/10.1128/jmbe.v21i2.2143
Lam, B-H and Tsui, K-W. (2013). Examining the alignment of subject learning outcomes and course curricula through curriculum mapping. Australian Journal of Teacher Education. 38: 97-119.
Lawlor, J. (2020). PNWColors: Color Palettes Inspired by Nature in the US Pacific Northwest. R package version 0.1.0. Retreived from: https://github.com/jakelawlor/PNWColors
Manthey, S. and Brewe, E. (2013). Toward university modeling instruction-Biology: Adapting curricular frameworks from physics to biology. Cell Biology Education—Life Sciences Education. 12: 206-214. https://doi.org/10.1187/cbe.12-08-0136
National Research Council. (2012). A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas. Committee on a Conceptual Framework for New K-12 Science Education Standards. Board on Science Education, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press. https://doi.org/10.17226/13165.
National Research Council. (2013). Next Generation Science Standards: For States, By States. Washington, DC: The National Academies Press. https://doi.org/10.17226/18290.
Quillin, K. and Thomas, S. (2015). Drawing-to-learn: A framework for using drawings to promote model-based reasoning in biology. Cell Biology Education—Life Sciences Education. 14: 1-16. https://doi.org/10.1187/cbe.14-08-0128
R Core Team. (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. Retrieved from https://www.r-project.org/
Ram, K. and Wickham, H. (2018). wesanderson: A Wes Anderson Palette Generator. R package version 0.3.6. https://cran.r-project.org/package=wesanderson
Rawle, F., Bowen, T., Murck, B., and Hong, R.J. (2017). Curriculum mapping across the disciplines: Differences, approaches, and strategies. Collected Essays on Teaching and Learning. https://doi.org/10.22329/celt.v10i0.4765
Svoboda, J. and Passmore, C. (2013). The strategies of modeling in biology education. Science and Education. 22: 119-142.
Wickham, H. (2016). tidyverse: Easily install and load the “Tidyverse”. R Package Version 1.2.1. Retrieved from https://cran.r-project.org/package=tidyverse
Wilke, C.O. (2020). cowplot: Streamlined Plot Theme and Plot Annotations for 'ggplot2'. R package version 1.1.0. Retrieved from https://CRAN.R-project.org/package=cowplot
Wilson, K.J., Long, T.M., Momsen, J.L., and Bray Speth, E. (2019). Evidence based teaching guide: Modeling in classroom. Cell Biology Education—Life Sciences Education. Retrieved from https://lse.ascb.org/evidence-based-teaching-guides/modeling-in-the-classroom/
Zukswert, J.M., Barker, M.K., and McDonnell, L. (2019). Identifying troublesome jargon in biology: Discrepancies between student performance and perceived understanding. Cell Biology Education—Life Sciences Education. 18:ar6, 1-12. https://doi.org/10.1187/cbe.17-07-0118