most citedSingle-Agent vs. Multi-Agent LLM Strategies for Automated Student Reflection Assessment

7 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

cs.HC2026

Designing a Meta-Reflective Dashboard for Instructor Insight into Student-AI Interactions

Boxuan Ma, Baofeng Ren, Huiyong Li +4

Generative AI tools are increasingly used for coursework help, shifting much of students' help-seeking and reasoning into student-AI chats that are largely invisible to instructors…

cs.HC2026

Design Implications for Student and Educator Needs in AI-Supported Programming Learning Tools

Boxuan Ma, Yinjie Xie, Huiyong Li +4

AI-powered coding assistants can support students in programming courses by providing on-demand explanations and debugging help. However, existing research often focuses on individ…

cs.HC2026

Three Years with Classroom AI in Introductory Programming: Shifts in Student Awareness, Interaction, and Performance

Boxuan Ma, Huiyong Li, Gen Li +4

Generative AI (GenAI) tools such as ChatGPT now provide novice programmers with instant, personalized support and are reshaping computing education. While a growing body of work ex…

cs.LG2025

Ranking-Based At-Risk Student Prediction Using Federated Learning and Differential Features

Shunsuke Yoneda, Valdemar Švábenský, Gen Li +2

Digital textbooks are widely used in various educational contexts, such as university courses and online lectures. Such textbooks yield learning log data that have been used in num…

cs.LG20257 cited

Single-Agent vs. Multi-Agent LLM Strategies for Automated Student Reflection Assessment

Gen Li, Li Chen, Cheng Tang +4

We explore the use of Large Language Models (LLMs) for automated assessment of open-text student reflections and prediction of academic performance. Traditional methods for evaluat…