activity
20212024
most citedA Multi-Level Trace Clustering Analysis Scheme for Measuring Students' Self-Regulated Learning Behavior in a Master-Based Online Learning Environment

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

physics.ed-ph2024

Comparing student performance on a multi-attempt asynchronous assessment to a single-attempt synchronous assessment in introductory level physics

Emily Frederick, Zhongzhou Chen

The current paper examines the possibility of replacing conventional synchronous single-attempt exam with more flexible and accessible multi-attempt asynchronous assessments in int…

physics.ed-ph2024

Achieving Human Level Partial Credit Grading of Written Responses to Physics Conceptual Question using GPT-3.5 with Only Prompt Engineering

Zhongzhou Chen, Tong Wan

Large language modules (LLMs) have great potential for auto-grading student written responses to physics problems due to their capacity to process and generate natural language. In…

physics.ed-ph2023

Reforming Physics Exams Using Openly Accessible Large Isomorphic Problem Banks created with the assistance of Generative AI: an Explorative Study

Zhongzhou Chen, Emily Frederick, Colleen Cui +4

This paper explores using large isomorphic problem banks to overcome many challenges of traditional exams in large STEM classes, especially the threat of content sharing websites a…

physics.ed-ph20211 cited

A Multi-Level Trace Clustering Analysis Scheme for Measuring Students' Self-Regulated Learning Behavior in a Master-Based Online Learning Environment

Tom Zhang, Michelle Taub, Zhongzhou Chen

The study introduces a new analysis scheme to analyze trace data and visualize students' self-regulated learning strategies in a mastery-based online learning modules platform. The…