Seminars & Colloquia

Soohyun Liao

University of California San Diego

"How to Maintain Student Learning Quality When Class Size Grows"

Thursday January 31, 2019 09:30 AM
Location: 3211, EB2 NCSU Centennial Campus
(Visitor parking instructions)


Abstract: As a researcher in computing education, my interest boils down to one question – “how can computer science (CS) programs maintain equivalent or better learning quality when class size increases?” This question stems from the increase in demand for CS major in post-secondary institutions. To fulfill such demand, many CS classes have to either grow in size or split the class into multiple smaller sections. However, increasing class size adds to the burden of existing instructor and reduces the effectiveness of traditional classroom pedagogy. Also, offering multiple sections may not be a sustainable option because adding instructors can be costly. These effects deteriorate students’ learning experience and cause students to prematurely leave CS programs.


In this talk, I will present the two ways my PhD research approached this question, followed by future work. I will also discuss other projects I have in mind to improve CS community. The talk will end with a brief teaching demonstration on for-loop basics using two active learning strategies: Peer Instruction and Jigsaw learning.

Short Bio: I am a PhD candidate from University of California, San Diego. As a computer science education researcher, I believe evidence-based instructional practices are crucial to maximize students’ learning quality. It is importance is especially significant in computer science programs these days as offering effective learning environment has become more challenging due to the growth in enrollment. It is also concerning, because poor quality of education seems to place underrepresented students at higher risk of leaving computer science programs.

Thus, my PhD research focuses on how computer science programs can maintain equivalent or better learning quality as class size grows. I approached this question in two ways: strategically assigning existing instructional resources to at-risk students and adopting active learning practices to improve every student’s learning. So far, I have published conference papers at the International Computing Education Research (ICER) and Computer Science Education (SIGCSE, ITiCSE) and a journal at Transactions on Computing Education (TOCE).

My teaching method is also deeply grounded to the evidence I acquired from a broad range of computer science education research studies. I assisted multiple Peer Instruction classrooms and adopted Peer Instruction and Jigsaw learning to my own course. In addition, I mentored junior graduate teaching assistants in the department to help adopt different evidence-based instructional practices to their own lectures. My effort on promoting evidence-based instructional practices was recognized through the doctoral teaching award from the CSE department in 2017 and I received Summer Graduate Teaching Scholarship shortly after.

Host: Sarah Heckman, CSC

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