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A Multi-Institutional Study of Interdisciplinary Teaching and Learning in STEM

A Multi-Institutional Study of Interdisciplinary Teaching and Learning in STEM A Research-Based Framework. Jim Swartz, Grinnell College. Motivation for Project. The 21 st Century Learner : To investigate diverse ways of implementing and assessing interdisciplinary learning in the sciences.

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A Multi-Institutional Study of Interdisciplinary Teaching and Learning in STEM

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  1. A Multi-Institutional Study of Interdisciplinary Teaching and Learning in STEM A Research-Based Framework Jim Swartz, Grinnell College

  2. Motivation for Project • The 21st Century Learner: To investigate diverse ways of implementing and assessing interdisciplinary learning in the sciences. • To employ a multi-institutional faculty cohort to investigate interdisciplinary student learning. • To use an evidence-based approach (qualitative & quantitative). • To construct a framework for interdisciplinary understanding. • To build upon the work of others in this area of scholarly inquiry.

  3. Collaborative Inquiry of Interdisciplinary Learning • Interviews with faculty & students (self-report) • Online surveys(self-report) • Course instructors • Pre & post surveys of enrolled students • http://www.grinnell.edu/academic/psychology/faculty/dl/risc • Faculty team inquiry & analysis of student work in interdisciplinary courses (performance-based) RISC

  4. Funding provided by HHMI Acknowledgements Trish Ferrett (Carleton College) David Lopatto, Mark Levandoski, Vida Praitis (Grinnell College) Joanne Stewart, Graham Peaslee (Hope College) Jim Russo (Whitman College) Paul Jackson, Gary Muir, Kevin Crisp (St. Olaf College) Whitney Schlegel (Indiana University) Carleton’s Science Education Resource Center (SERC)

  5. RISC (Research on Integrated Science Curricula) Surveys Faculty survey: course goals and activities Studentpre- and post- surveys: nature of science, learning styles, confidence, and learning gains. EMPIRICAL & SCHOLARLY - Based on research literature, previous work of project team, and faculty/student interviews.

  6. Sample (of 50) Faculty Questions

  7. Sample (of 50) Student Questions

  8. What might we learn from RISC? Once survey validity is more established, we will query RISC data with more “profound” questions. EXAMPLE: What are the relationships between degree of independent learning (pedagogy), student attitudes about nature of science, and courses with a focus on complex ID problems or systems?

  9. Learning Goals:Items from Faculty survey common to “high” ID courses Students learn to ask "big questions" that implicate more than one discipline in a solution. Students learn about two (or more) disciplines so that new insights emerge from considering them together. Students learn to find similarities and differences between disciplines or fields of study. Students study problems with multiple causes that operate simultaneously and interactively.

  10. Pedagogies:Items from Faculty survey common to “high” ID courses Students engage in class discussion Students spend the entire course on one or a few problems Students work on problems that have no clear solution Students learn about two (or more) disciplines so that new insights emerge from considering them together Students have input on design of a project

  11. Results & Lessons from RISC Survey Language matters! Students’ reports on prominent learning gains align with faculty - and high learning gains reported by students. Faculty reports on learning goals and pedagogies are consistent with research literature on interdisciplinarity. High ID RISC items resonate with qualitative findings.

  12. Scholarly Inquiry by Faculty Cohort: Analysis of Student Work 10 faculty, 1-3 from each of 5 colleges (Carleton, Grinnell, Hope, St. Olaf, Whitman) Faculty and cohort inquiry into student learning in their own courses using qualitative methods of analyzing student work

  13. Interdisciplinary Courses: Qualitative Work • Two traditional disciplinary disciplines merged • Introductory biology and chemistry integrated course • Defined interdisciplinary area • Neuroscience (senior capstone & introductory course) • Bioinformatics (mid-level) • Problem-based drawing upon multiple disciplines • Health Sciences • Senior seminar on infectious diseases • Environmental Science • First-year seminar on renewable energy • Mid-level course on abrupt climate change • Senior research capstone for environmental science majors

  14. Integration Return, Revise, Reflect Engaging Complexity Interdisciplinary Understanding Building Understanding Engaging Disciplines Learning Communities Personal Connection Findings: Emergent Framework

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