ArticleFrontiers in psychology2021
Educational Data Mining Techniques for Student Performance Prediction: Method Review and Comparison Analysis.
Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Policy aware fusion of educational and economic indicators for public health curriculum optimization.Frontiers in public health · 2026Article
- Twelve tips for using educational data mining and machine learning to predict performance in high-stakes health professions education exams.Journal of education and health promotion · 2026Review
- Personalized learning support system for special education: a real-time feedback mechanism based on deep reinforcement learning.Frontiers in psychology · 2025Article
- Article
- Knowledge concept recognition in the learning brain via fMRI classification.Frontiers in neuroscience · 2025Article
- Article
- SAPPNet: students' academic performance prediction during COVID-19 using neural network.Scientific reports · 2024Article
- Enhancing Lessons on the Internet of Things in Science, Technology, Engineering, and Medical Education with a Remote Lab.Sensors (Basel, Switzerland) · 2024Article
- Self-paced graph memory for learner GPA prediction and it's application in learner multiple evaluation.Scientific reports · 2023Article
- Does teacher's data literacy and digital teaching competence influence empowering students in the classroom? Evidence from China.Education and information technologies · 2023Article
- Do Written Responses to Open-Ended Questions on Fourth-Grade Online Formative Assessments in Mathematics Help Predict Scores on End-of-Year Standardized Tests?Journal of Intelligence · 2022Article
- Influence Analysis of Education Policy on Migrant Children's Education Integration Using Artificial Intelligence and Deep Learning.Frontiers in psychology · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 toward personalized education and has attracted increasing attention in the field of artificial intelligence and educational data mining (EDM). This paper provides a systematic review of the SPP study from the perspective of machine learning and data mining. This review partitions SPP into five stages, i.e., data collection, problem formalization, model, prediction, and application. To have an intuition on these involved methods, we conducted experiments on a data set from our institute and a public data set. Our educational dataset composed of 1,325 students, and 832 courses was collected from the information system, which represents a typical higher education in China. With the experimental results, discussions on current shortcomings and interesting future works are finally summarized from data collections to practices. This work provides developments and challenges in the study task of SPP and facilitates the progress of personalized education.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.