2024 ASEE Annual Conference & Exposition

Evaluating the Effectiveness of Peer-Led Learning for a Hardware Course

Presented at Frameworks and Comparative Analyses in ECE Education

In this paper, we describe the effectiveness of peer-led learning for a hardware course (computer organization) in the Computer Science and Engineering department at a large public university. The proposed peer-led learning in the format of online recitations extends in-class activities to after-lecture recitation hours, encourages students’ deep learning and understanding with extra challenging questions and peer-guided group discussions. In this paper we will describe the format, design, and improvement of the peer-led recitation sessions and how we choose peer leaders. The implementation of the peer-led online recitation sessions began in Fall 2021. Since then, students’ feedback has been monitored continuously to adjust recitations’ formats, frequency, discussion topics, etc. Surveys have been conducted and analyzed to evaluate the effectiveness of peer-led recitations and identify areas of improvement. Most students (more than 90%) expressed positive feedback in the end of semester survey. Based on the survey results conducted in the past several semesters, we conclude that peer-led online recitations help students’ study in concepts understanding, problem solving techniques, and assembly language programming. Moreover, we observe that course pass rate improved for students attending peer-led recitations.

Authors

Dr. Yan Zhang University of South Florida [biography]

Yan Zhang is an assistant professor of instruction in the Department of Computer Science and Engineering, University of South Florida. Dr. Zhang completed her Ph.D. in Computer Engineering at New Jersey Institute of Technology. Dr. Zhang’s research interests are Congestion control and energy optimization in data center networks, content delivery acceleration over wide area networks and energy efficient networking.
Dr. Jing Wang University of South Florida [biography]

Dr. Jing Wang is a Professor of Instruction in the Department of Computer Science and Engineering. She received her PhD in 2005 in Electrical Engineering and Computer Science from Vanderbilt University. Her research interests are computer animation, undergraduate computer science and engineering education, and broadening participation in computing. Throughout her career, Dr. Wang has been actively involved in the important mission of recruiting and mentoring women in computer science and engineering. She serves as the faculty advisor of Women in Computer Science and Engineering student organization since 2013.

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