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Value of Case-Based Learning within STEM Courses: Is It the Method or Is It the Student?
Ashley Rhodes1, Abigail Wilson1, Timothy Rozell2
1Division of Biology, Kansas State University, Manhattan, KS 66506.
Case-based learning in physiology courses may not benefit all students equally. Students with lower academic preparation experienced reduced learning gains compared to traditional lectures, suggesting cognitive load challenges.
Area of Science:
- STEM Education
- Cognitive Psychology
- Physiology Pedagogy
Background:
- Undergraduate attrition in Science, Technology, Engineering, and Mathematics (STEM) is a significant issue, often increasing in intermediate college years.
- A mismatch between pedagogical methods and students' cognitive abilities can contribute to attrition.
- Cognitive Load Theory provides a framework for understanding learning limitations.
Purpose of the Study:
- To investigate the impact of case-based learning versus traditional lectures on undergraduate learning gains in physiology.
- To examine how student characteristics, such as academic preparation and academic age, influence the effectiveness of case-based learning.
Main Methods:
- Comparison of learning gains between case-based learning and traditional lecture formats in an intermediate physiology course.
- Analysis of student characteristics, including ACT scores (academic preparation) and credit hours completed (academic age).
Main Results:
- Case-based learning did not universally yield greater learning gains than traditional lectures.
- Students with lower ACT scores or fewer completed credit hours showed diminished learning gains with case-based learning compared to lectures.
- Findings suggest extraneous cognitive load from case-based learning may impede less experienced students.
Conclusions:
- The effectiveness of case-based learning is contingent on student cognitive capacity and preparation.
- Pedagogical strategies must consider individual student differences to avoid overwhelming cognitive abilities.
- Further research is needed to optimize case-based learning for diverse undergraduate populations in STEM.
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