Research

Adaptive Learning Support through Knowledge Monitoring

We study adaptive learning support that considers not only what learners actually know but also how accurately they perceive their own understanding. By integrating open-ended learning reflections and assessment results using LLMs and heterogeneous graph neural networks, we estimate learners' perceived knowledge states and provide personalized feedback that addresses both knowledge gaps and metacognitive miscalibration such as overconfidence and underconfidence.

Early Prediction of At-Risk Students with Federated Learning

We study methods for predicting students at risk of academic difficulty by combining federated learning with differential features that capture relative differences among learners. The goal is to generate risk rankings that support early intervention while preserving privacy across educational institutions.

Collaborative Problem-Solving Skill Recognition

We study methods for automatically recognizing multiple collaborative problem-solving skills from classroom discussion data. By incorporating dialogue structure, such as speaker roles and turn-taking, the approach aims to support the analysis and assessment of collaborative learning.

Continuous Glucose Forecasting

We study deep learning models for accurate forecasting of future states from time-series data. GluTANN introduces a dedicated attention mechanism into a Transformer-based architecture to improve continuous glucose forecasting while reducing predictive uncertainty.

Time-Series Forecasting with Mamba

We study extensions of Mamba for modeling complex nonlinear dependencies in time-series data. By introducing a negative-feedback mechanism, the approach aims to better capture long-term dependencies and nonlinear temporal dynamics for accurate forecasting.

Research

Learning Analytics

Adaptive Learning Support through Knowledge Monitoring

Early Prediction of At-Risk Students with Federated Learning

Collaborative Problem-Solving Skill Recognition

Time Series Forecasting

Continuous Glucose Forecasting

Time-Series Forecasting with Mamba

Adaptive Learning Support through Knowledge Monitoring

Capture-Calibrate-Coach: A Graph-Based Framework for Knowledge Monitoring Estimation and Adaptive Feedback

Early Prediction of At-Risk Students with Federated Learning

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

Collaborative Problem-Solving Skill Recognition

DiaRoBERTa: A Multi-Party Dialogue Model for Multi-Skill Recognition in Classroom Collaborative Problem Solving Discussions

Continuous Glucose Forecasting

GluTANN: Transformer-Based Continuous Glucose Monitoring Model with ANN Attention

Time-Series Forecasting with Mamba

Enhancing Nonlinear Dependencies of Mamba via Negative Feedback for Time Series Forecasting