2 citations · 2 across the 4 of their papers we have counts for
4 papers
Generative Data Imputation for Sparse Learner Performance Data Using Generative Adversarial Imputation Networks
Liang Zhang, Jionghao Lin, John Sabatini +6
Learner performance data collected by Intelligent Tutoring Systems (ITSs), such as responses to questions, is essential for modeling and predicting learners' knowledge states. Howe…
Exploring the Potential of Large Language Models for Estimating the Reading Comprehension Question Difficulty
Yoshee Jain, John Hollander, Amber He +3
Reading comprehension is a key for individual success, yet the assessment of question difficulty remains challenging due to the extensive human annotation and large-scale testing r…
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…
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…