2 citations · 4 across the 3 of their papers we have counts for
4 papers
Data Augmentation for Sparse Multidimensional Learning Performance Data Using Generative AI
Liang Zhang, Jionghao Lin, John Sabatini +6
Learning performance data describe correct and incorrect answers or problem-solving attempts in adaptive learning, such as in intelligent tutoring systems (ITSs). Learning performa…
Integrating Attentional Factors and Spacing in Logistic Knowledge Tracing Models to Explore the Impact of Training Sequences on Category Learning
Meng Cao, Philip I. Pavlik, Wei Chu +1
In category learning, a growing body of literature has increasingly focused on exploring the impacts of interleaving in contrast to blocking. The sequential attention hypothesis po…
Predicting Learning Performance with Large Language Models: A Study in Adult Literacy
Liang Zhang, Jionghao Lin, Conrad Borchers +4
Intelligent Tutoring Systems (ITSs) have significantly enhanced adult literacy training, a key factor for societal participation, employment opportunities, and lifelong learning. O…
3DG: A Framework for Using Generative AI for Handling Sparse Learner Performance Data From Intelligent Tutoring Systems
Liang Zhang, Jionghao Lin, Conrad Borchers +2
Learning performance data (e.g., quiz scores and attempts) is significant for understanding learner engagement and knowledge mastery level. However, the learning performance data c…