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Qiongqiong Liu

3 accepted papers

2023

Improving Interpretability of Deep Sequential Knowledge Tracing Models with Question-centric Cognitive Representations

AAAI 2023technical

Knowledge tracing (KT) is a crucial technique to predict students’ future performance by observing their historical learning processes. Due to the powerful representation ability of deep neural networks, remarkable progress has been made by using deep learning techniques to solve the KT problem. The…

Cited by 61SourcePDFScholar
2023

simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracing

ICLR 2023poster

Knowledge tracing (KT) is the problem of predicting students' future performance based on their historical interactions with intelligent tutoring systems. Recently, many works present lots of special methods for applying deep neural networks to KT from different perspectives like model architecture,…

2022

pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models

NeurIPS 2022accept

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 interaction performance. Recently, remarkable progress has been made of using various deep learning techniques to solve the…

Cited by 63SourcePDFScholar