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Exploring Biomedical Engineering Students' Self-Raised Motivations for Engaging in Instructional Design
Author(s) -
Jacqueline Handley,
Aileen Huang-Saad,
Cassandra Woodcock
Publication year - 2020
Publication title -
2018 asee annual conference and exposition proceedings
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--30484
Subject(s) - active learning (machine learning) , engineering education , psychology , incubator , pedagogy , mathematics education , medical education , computer science , engineering , medicine , engineering management , microbiology and biotechnology , artificial intelligence , biology
Current research in the field of engineering education endorses a transition toward active learning pedagogies in the classroom to support greater student learning. In several cases, however, a gap exists between the interdisciplinary research supporting the effectiveness of active learning environments in engineering and actual instructional practice. Today, the engineering instruction is often a shared responsibility between faculty, graduate students and senior undergraduates serving in student teaching roles. Thus, there is a need to better support adopting active learning and to better understand the potential barriers that may inhibit instructors from adopting these new pedagogies. To begin to address these needs, we launched a research-based instructional incubator for biomedical engineering (BME) students, upper level undergraduates, graduate students, postdoctoral fellows and faculty. Given the participants’ selfselection into the Incubator and more systemic barriers in the field, we were interested in understanding what motivates students to engage in a course around active learning and educational design in engineering. Further, we sought to better understand the pre-conceptions these students may have about learning, as one potential barrier to translating research to practice. We hypothesized that students may enter the course with a broad interest in improving education given their own experiences, but limited understanding of learning as it relates to evidence-based active learning practices. Using data from a long-form, open-ended survey, we qualitatively analyzed student responses to better understand their motivations for taking the course and their conceptions of learning. We present results on BME students’ self-raised motivations for engaging in educational design and how students conceive learning from the analytical lens of current learning theories.

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