activity
20232026
most citedPractical and Ethical Challenges of Large Language Models in Education: A Systematic Scoping Review

877 citations · 887 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CY2026

The Easy Trap: Why LLMs Underestimate Misconception-Driven Difficulty

Amanda La Hadi, Muhammad Johan Alibasa, Guanliang Chen +1

Large language models (LLMs) are increasingly used for estimating item difficulty in educational assessment. However, it remains unclear whether such estimates reflect how learners…

cs.HC2026

Dataset of GenAI-Assisted Information Problem Solving in Education

Xinyu Li, Kaixun Yang, Jiameng Wei +3

Information Problem Solving (IPS) is a critical competency for academic and professional success in education, work, and life. The advent of Generative Artificial Intelligence (Gen…

cs.CY2025

SCALEFeedback: A Large-Scale Dataset of Synthetic Computer Science Assignments for LLM-generated Educational Feedback Research

Keyang Qian, Kaixun Yang, Wei Dai +8

Using Large Language Models (LLMs) to give educational feedback to students for their assignments has attracted much attention in the AI in Education (AIED) field. Yet, there is cu…

cs.CY2025

Dean of LLM Tutors: A Framework for Automated Quality Review of AI-generated Feedback

Keyang Qian, Yixin Cheng, Rui Guan +8

Large language model (LLM) tutors are increasingly used to generate educational feedback, but existing research has focused mainly on feedback generation rather than feedback evalu…

cs.HC2024★ 2 cited

Ink and Algorithm: Exploring Temporal Dynamics in Human-AI Collaborative Writing

Kaixun Yang, Yixin Cheng, Linxuan Zhao +4

The advent of Generative Artificial Intelligence (GAI) has revolutionized the field of writing, marking a shift towards human-AI collaborative writing in education. However, the dy…

cs.HC2024★ 1 cited

Evidence-centered Assessment for Writing with Generative AI

Yixin Cheng, Kayley Lyons, Guanliang Chen +2

We propose a learning analytics-based methodology for assessing the collaborative writing of humans and generative artificial intelligence. Framed by the evidence-centered design,…

cs.CL2024★ 2 cited

Unveiling the Tapestry of Automated Essay Scoring: A Comprehensive Investigation of Accuracy, Fairness, and Generalizability

Kaixun Yang, Mladen Raković, Yuyang Li +3

Automatic Essay Scoring (AES) is a well-established educational pursuit that employs machine learning to evaluate student-authored essays. While much effort has been made in this a…

cs.CL2023★ 4 cited

Towards Automatic Boundary Detection for Human-AI Collaborative Hybrid Essay in Education

Zijie Zeng, Lele Sha, Yuheng Li +3

The recent large language models (LLMs), e.g., ChatGPT, have been able to generate human-like and fluent responses when provided with specific instructions. While admitting the con…

cs.CL2023

Robust Educational Dialogue Act Classifiers with Low-Resource and Imbalanced Datasets

Jionghao Lin, Wei Tan, Ngoc Dang Nguyen +6

Dialogue acts (DAs) can represent conversational actions of tutors or students that take place during tutoring dialogues. Automating the identification of DAs in tutoring dialogues…

cs.CL2023★ 1 cited

Does Informativeness Matter? Active Learning for Educational Dialogue Act Classification

Wei Tan, Jionghao Lin, David Lang +4

Dialogue Acts (DAs) can be used to explain what expert tutors do and what students know during the tutoring process. Most empirical studies adopt the random sampling method to obta…

cs.CL2023★ 877 cited

Practical and Ethical Challenges of Large Language Models in Education: A Systematic Scoping Review

Lixiang Yan, Lele Sha, Linxuan Zhao +6

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. W…