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Title: Virtual adaptation of introductory materials engineering: a partially asynchronous approach to engage a large class
With large enrollments (about 200-350) of primarily non-majors, engaging students in the required introductory materials science and engineering course at our university has been a longstanding challenge. In moving to the virtual format in the fall of 2020, we significantly adapted several aspects of the course, many of which have continued to the hybrid format in future semesters, with good results. The primary content was provided through asynchronous videos; this format allowed us to break content into digestible pieces. In particular, multiple mini-lectures and example videos were pre-recorded for each week, with a total viewing time per week somewhat less than the typical total class time. To provide real-time, structured interaction, one live virtual class session per week was held, centered on previously submitted student questions. Smaller teaching-assistant-led recitation sections also met live (virtually or in person), during which “clicker” questions were asked through TopHat. Assignments were also updated to take advantage of the virtual format. Multiple small assignments with lower stakes were due throughout the week: a reading/lecture quiz, a survey to submit questions, and a shortened homework assignment. Finally, we changed some content near the end of the course to allow students to connect the course to their own career aspirations, which we expect can aid in longterm retention. Specifically, students chose among several possible topics to cover in the final weeks, covered via typical pre-recorded lectures and reading, and also guest lectures. They wrote an abstract-length reflection on how they could use what they learned in this course later in their careers. Overall, students remained engaged with the course throughout the semester and provided favorable comments and evaluations of the course, including higher numerical evaluations of the course than in prior semesters.  more » « less
Award ID(s):
1943870
NSF-PAR ID:
10403112
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
2022 ASEE Annual Conference & Exposition
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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