Self-Regulated Learning Environment at Scale
I believe an instructor should build a self-regulated learning environment where students can create their own academic goals and monitor their own progress towards those goals. Self-regulated learning is especially important these days due to the explosive enrollment growth of CS, as large class size makes it practically impossible for instructors to keep track of each student’s progress and offer appropriate assistance when needed.
Computer Science: An Interdisciplinary Approach
Princeton University, Link
It is the entry-level CS course which covers a broad range of CS topics including Java programming, basic data structures, number systems, computer architecture, combinational circuits, assembly programming, and theory of computing. It has been one of Princeton’s most popular courses - nearly 60% of students on campus take this course before they graduate.
I introduced multiple new course components to improve student engagement and and make the most efficient use of the instructional budget. First, I redesigned precepts, which are the only in-person class meetings of the course, into 2-staged class meetings named multi-themed labs and short precepts. This improved student engagement by enabling students to collaborate with their peers and personalize their learning to fulfill their individual needs. To ensure everyone kept up in their personalized learning, I also designed the fully-automated CompassX that provides personalized study guide to each student.
It covered the core content of the course. The lab material was delivered in a pre-written form through Ed Lessons. It consisted of reading passages followed by answering conceptual questions and/or completing programming exercises.
Delivering all the content through pre-written material enabled students to learn at their own pace and get personalized help from the preceptors as necessary. Students were also able to select between three sets of activities themed in arts, biology, and regular CS. These sets introduced the same CS concepts in the context of different themes, which reinforced students’ self-regulation by letting them find the most helpful learning material on their own based on their motivation and interest in CS.
Multi-themed labs used pair-programming practice to encourage collaboration in class.
Short precepts contained challenging exercises and used Peer Instruction practice to encourage peer discussions. Students polled their responses through an application called sli.do. The entire material is available on the course website.
CompassX offered personalized study guide for each student in a fully-automated manner. Using student answers to online quiz questions and their confidence indications on each of their answers, our embedded script created a prioritized list of things to study along with references to relevant resources.
Introduction to Computer Architecture & Computer Architecture Lab
University of California at San Diego, Summer 2017
To help students stay engaged throughout the lengthy 3-hour lectures, I adopted two evidence-based collaborative learning practices. I applied Jigsaw learning activities in the middle of the lecture while Peer Instruction was utilized at the beginning and end of the lecture. I crafted the Jigsaw learning material from scratch while I referred to pre-existing material for Peer Instruction.
According to the end-of-term evaluations, the vast majority were satisfied with my lecture design and 72% specifically pointed out that Jigsaw learning helped their learning. I also published an experience report of my Jigsaw learning practice on ITiCSE 2018. You can find sample material of Jigsaw learning activities on the same paper.