AI-based personalized e-learning systems: Issues, challenges, and solutions

M Murtaza, Y Ahmed, JA Shamsi, F Sherwani… - IEEE …, 2022‏ - ieeexplore.ieee.org
A personalized e-learning system is effective in imparting enhanced learning to its users. As
compared to a conventional e-learning system, which provides similar contents to each …

Text-based question difficulty prediction: A systematic review of automatic approaches

S AlKhuzaey, F Grasso, TR Payne… - International Journal of …, 2024‏ - Springer
Designing and constructing pedagogical tests that contain items (ie questions) which
measure various types of skills for different levels of students equitably is a challenging task …

Disentangling cognitive diagnosis with limited exercise labels

X Chen, L Wu, F Liu, L Chen, K Zhang… - Advances in …, 2023‏ - proceedings.neurips.cc
Cognitive diagnosis is an important task in intelligence education, which aims at measuring
students' proficiency in specific knowledge concepts. Given a fully labeled exercise-concept …

Modeling context-aware features for cognitive diagnosis in student learning

Y Zhou, Q Liu, J Wu, F Wang, Z Huang… - Proceedings of the 27th …, 2021‏ - dl.acm.org
The contexts and cultures have a direct impact on student learning by affecting student's
implicit cognitive states, such as the preference and the proficiency on specific knowledge …

Knowledge-sensed cognitive diagnosis for intelligent education platforms

H Ma, M Li, L Wu, H Zhang, Y Cao, X Zhang… - Proceedings of the 31st …, 2022‏ - dl.acm.org
Cognitive diagnosis is a fundamental issue of intelligent education platforms, whose goal is
to reveal the mastery of students on knowledge concepts. Recently, certain efforts have …

Deep cognitive diagnosis model for predicting students' performance

L Gao, Z Zhao, C Li, J Zhao, Q Zeng - Future Generation Computer Systems, 2022‏ - Elsevier
Cognitive model is playing very important role in predicting students' performance and
recommending learning resources. Thus, it has received a great deal of attention from …

A survey on recent approaches to question difficulty estimation from text

L Benedetto, P Cremonesi, A Caines, P Buttery… - ACM Computing …, 2023‏ - dl.acm.org
Question Difficulty Estimation from Text (QDET) is the application of Natural Language
Processing techniques to the estimation of a value, either numerical or categorical, which …

Multi-factors aware dual-attentional knowledge tracing

M Zhang, X Zhu, C Zhang, Y Ji, F Pan… - Proceedings of the 30th …, 2021‏ - dl.acm.org
With the increasing demands of personalized learning, knowledge tracing has become
important which traces students' knowledge states based on their historical practices. Factor …

Generating better items for cognitive assessments using large language models

A Laverghetta Jr, J Licato - Proceedings of the 18th workshop on …, 2023‏ - aclanthology.org
Writing high-quality test questions (items) is critical to building educational measures but has
traditionally also been a time-consuming process. One promising avenue for alleviating this …

A deep cross-modal neural cognitive diagnosis framework for modeling student performance

L Song, M He, X Shang, C Yang, J Liu, M Yu… - Expert Systems with …, 2023‏ - Elsevier
In intelligent education systems, one fundamental task is to predict student performance on
new exercises and estimate the knowledge proficiency of students on knowledge concepts …