30 citations · 58 across the 12 of their papers we have counts for
12 papers
Do Personalized Skills Help Coding Agents? An Empirical Study of Developer Interaction Traces
Shuyan Huang, Kai Du, Andrew Lan
As human developers increasingly collaborate with large language model (LLM)-powered coding agents, adapting to individual developer preferences, potentially via agent skills, may…
Who Am I? History-Aware Profiles for Student Simulation in Tutoring Dialogues
Zhangqi Duan, Shuyan Huang, Alexander Scarlatos +3
A key part of developing large language model (LLM)-powered, automated tutoring tools is student simulation, i.e., using LLMs to role-play as students, which can facilitate tutor m…
Interpretable Difficulty-Aware Knowledge Tracing in Tutor-Student Dialogues
Shuyan Huang, Alexander Scarlatos, Jaewook Lee +1
Recent advances in large language models (LLMs) have led to the development of AI-powered tutoring systems that provide interactive support via dialogue. To enable these tutoring s…
Towards Robust Knowledge Tracing Models via k-Sparse Attention
Shuyan Huang, Zitao Liu, Xiangyu Zhao +2
Knowledge tracing (KT) is the problem of predicting students' future performance based on their historical interaction sequences. With the advanced capability of capturing contextu…
Improving Low-Resource Knowledge Tracing Tasks by Supervised Pre-training and Importance Mechanism Fine-tuning
Hengyuan Zhang, Zitao Liu, Shuyan Huang +3
Knowledge tracing (KT) aims to estimate student's knowledge mastery based on their historical interactions. Recently, the deep learning based KT (DLKT) approaches have achieved imp…
Improving Interpretability of Deep Sequential Knowledge Tracing Models with Question-centric Cognitive Representations
Jiahao Chen, Zitao Liu, Shuyan Huang +2
Knowledge tracing (KT) is a crucial technique to predict students' future performance by observing their historical learning processes. Due to the powerful representation ability o…
simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracing
Zitao Liu, Qiongqiong Liu, Jiahao Chen +2
Knowledge tracing (KT) is the problem of predicting students' future performance based on their historical interactions with intelligent tutoring systems. Recently, many works pres…
Enhancing Deep Knowledge Tracing with Auxiliary Tasks
Zitao Liu, Qiongqiong Liu, Jiahao Chen +4
Knowledge tracing (KT) is the problem of predicting students' future performance based on their historical interactions with intelligent tutoring systems. Recent studies have appli…
A Design of A Simple Yet Effective Exercise Recommendation System in K-12 Online Learning
Shuyan Huang, Qiongqiong Liu, Jiahao Chen +3
We propose a simple but effective method to recommend exercises with high quality and diversity for students. Our method is made up of three key components: (1) candidate generatio…
SC-Ques: A Sentence Completion Question Dataset for English as a Second Language Learners
Qiongqiong Liu, Yaying Huang, Zitao Liu +6
Sentence completion (SC) questions present a sentence with one or more blanks that need to be filled in, three to five possible words or phrases as options. SC questions are widely…
DialogID: A Dialogic Instruction Dataset for Improving Teaching Effectiveness in Online Environments
Jiahao Chen, Shuyan Huang, Zitao Liu +1
Online dialogic instructions are a set of pedagogical instructions used in real-world online educational contexts to motivate students, help understand learning materials, and buil…
pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models
Zitao Liu, Qiongqiong Liu, Jiahao Chen +3
Knowledge tracing (KT) is the task of using students' historical learning interaction data to model their knowledge mastery over time so as to make predictions on their future inte…