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A review of data mining in personalized education: Current trends and future prospects
Personalized education, tailored to individual student needs, leverages educational
technology and artificial intelligence (AI) in the digital age to enhance learning effectiveness …
technology and artificial intelligence (AI) in the digital age to enhance learning effectiveness …
DGEKT: a dual graph ensemble learning method for knowledge tracing
Knowledge tracing aims to trace students' evolving knowledge states by predicting their
future performance on concept-related exercises. Recently, some graph-based models have …
future performance on concept-related exercises. Recently, some graph-based models have …
Fine-grained interaction modeling with multi-relational transformer for knowledge tracing
Knowledge tracing, the goal of which is predicting students' future performance given their
past question response sequences to trace their knowledge states, is pivotal for computer …
past question response sequences to trace their knowledge states, is pivotal for computer …
Deep knowledge tracing incorporating a hypernetwork with independent student and item networks
E Tsutsumi, Y Guo, R Kinoshita… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Knowledge tracing (KT), the task of tracking the knowledge state of a student over time, has
been assessed actively by artificial intelligence researchers. Recent reports have described …
been assessed actively by artificial intelligence researchers. Recent reports have described …
A unified adaptive testing system enabled by hierarchical structure search
Adaptive Testing System (ATS) is a promising testing mode, extensively utilized in
standardized tests like the GRE. It offers personalized ability assessment by dynamically …
standardized tests like the GRE. It offers personalized ability assessment by dynamically …
Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images
In the last years, the weakly supervised paradigm of multiple instance learning (MIL) has
become very popular in many different areas. A paradigmatic example is computational …
become very popular in many different areas. A paradigmatic example is computational …
Deepqr: Neural-based quality ratings for learnersourced multiple-choice questions
Automated question quality rating (AQQR) aims to evaluate question quality through
computational means, thereby addressing emerging challenges in online learnersourced …
computational means, thereby addressing emerging challenges in online learnersourced …
Eduagent: Generative student agents in learning
S Xu, X Zhang, L Qin - arxiv preprint arxiv:2404.07963, 2024 - arxiv.org
Student simulation in online education is important to address dynamic learning behaviors
of students with diverse backgrounds. Existing simulation models based on deep learning …
of students with diverse backgrounds. Existing simulation models based on deep learning …
Simultaneous missing value imputation and structure learning with groups
Learning structures between groups of variables from data with missing values is an
important task in the real world, yet difficult to solve. One typical scenario is discovering the …
important task in the real world, yet difficult to solve. One typical scenario is discovering the …
Assessing the performance of online students--new data, new approaches, improved accuracy
We consider the problem of assessing the changing performance levels of individual
students as they go through online courses. This student performance (SP) modeling …
students as they go through online courses. This student performance (SP) modeling …