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Enhanced Student Engagement through Teamwork, Gamification, and Diversity & Inclusion Best Practices in an Electromagnetics Course
IEEE Frontiers in Education Conference (FIE) ; 2021.
Article in English | Web of Science | ID: covidwho-1978387
ABSTRACT
In this Innovative Practice Full Paper we present an approach where we coupled several proven pedagogical practices to enhance student engagement during the time of remote/hybrid instruction due to the COVID-19 pandemic. One of these approaches was team-based learning throughout the entire semester which aided in student motivation. A second practice implemented was game-based learning to drive student engagement and excitement. This game-based learning approach used a semester-long scoring system which allowed students to compete for bonus points both on an individual and team basis. This enabled students to practice their teaming skills. Lastly, there was a major focus on diversity & inclusion in addition to teamwork in the course. Students were arranged into teams in an optimized manner by the CATME software. The optimization constraints were chosen using best practices for diversity in race & ethnicity, gender, skill levels, and leadership philosophy, while also considering students with similar schedules for availability purposes. The course also contained instructional modules on effective teamwork as well as contributions in the field of electrical engineering by underrepresented minorities. This paper details the innovative coupling of these practices and how they fit into the course's overall plan. Classroom activity and student perceptions associated with these practices were assessed via structured classroom observation using the COPUS protocol and collection of survey/focus group data, respectively. Assessment results are discussed, along with challenges encountered in this electromagnetics course in the hybrid/remote learning environment.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Prognostic study Language: English Journal: IEEE Frontiers in Education Conference (FIE) Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Prognostic study Language: English Journal: IEEE Frontiers in Education Conference (FIE) Year: 2021 Document Type: Article