A Human-Centered Review of Algorithms in Decision-Making in Higher Education
The use of algorithms for decision-making in higher education is steadily growing, promising
cost-savings to institutions and personalized service for students but also raising ethical …
cost-savings to institutions and personalized service for students but also raising ethical …
[HTML][HTML] Educational data mining techniques for student performance prediction: method review and comparison analysis
Y Zhang, Y Yun, R An, J Cui, H Dai… - Frontiers in psychology, 2021 - frontiersin.org
Student performance prediction (SPP) aims to evaluate the grade that a student will reach
before enrolling in a course or taking an exam. This prediction problem is a kernel task …
before enrolling in a course or taking an exam. This prediction problem is a kernel task …
Predicting and understanding student learning performance using multi-source sparse attention convolutional neural networks
Predicting and understanding student learning performance has been a long-standing task
in learning science, which can benefit personalized teaching and learning. This study shows …
in learning science, which can benefit personalized teaching and learning. This study shows …
Using ensemble learning algorithms to predict student failure and enabling customized educational paths
One of the challenges in e‐learning is the customization of the learning environment to
avoid learners' failures. This paper proposes a Stacked Generalization for Failure Prediction …
avoid learners' failures. This paper proposes a Stacked Generalization for Failure Prediction …
Language model-guided student performance prediction with multimodal auxiliary information
Abstract Student Performance Prediction (SPP) has received a lot of attention due to its
educational implications, such as personalized instruction. Among numerous attempts in …
educational implications, such as personalized instruction. Among numerous attempts in …
Acmf: An attention collaborative extended matrix factorization based model for mooc course service via a heterogeneous view
The spouting development of Massive Open Online Courses (MOOC) has enabled any
learner to obtain abundant resource anytime and anywhere, offered a large-scale and open …
learner to obtain abundant resource anytime and anywhere, offered a large-scale and open …
Identifying non-math students from brain mris with an ensemble classifier based on subspace-enhanced contrastive learning
In current research processes, mathematical learning has significantly impacted the brain's
plasticity and cognitive functions. While biochemical changes in brain have been …
plasticity and cognitive functions. While biochemical changes in brain have been …
[Retracted] Analysis on the Particularity of Higher Education Subject Development under the Background of Artificial Intelligence
Y Wang - International Transactions on Electrical Energy …, 2022 - Wiley Online Library
Subject development plays a crucial role in higher education (HE), improving student
academic performance. The HE continuously requires conceptual and empirical …
academic performance. The HE continuously requires conceptual and empirical …
Contrastive deep knowledge tracing
H Dai, Y Yun, Y Zhang, W Zhang, X Shang - International Conference on …, 2022 - Springer
Abstract Knowledge tracing (KT) aims to predict student performance on the next question
according to historical records. Recently deep learning-based models for KT task …
according to historical records. Recently deep learning-based models for KT task …
Self-paced graph memory network for student GPA prediction and abnormal student detection
Student learning performance prediction (SLPP) is a crucial step in high school education.
However, traditional methods fail to consider abnormal students. In this study, we organized …
However, traditional methods fail to consider abnormal students. In this study, we organized …