An overview and comparison of supervised data mining techniques for student exam performance prediction
Bibliographic Data
| ID | 21538429 |
|---|---|
| Authors | Nikola Tomasevic (0000-0002-6620-479X, University of Belgrade, corresponding author), Nikola Gvozdenovic (0000-0003-3362-0516, Institut Mihajlo Pupin), Sanja Vranes (0000-0002-7054-6928, Institut Mihajlo Pupin) |
| Year | 2020 |
| Volume | 143 |
| Pages | 103676 |
| Publication date | 2020-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Computers & Education (JOURNAL) |
| Journal identifiers | ISSN: 0360-1315 • E-ISSN: 1873-782X |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.compedu.2019.103676 |
| OpenAlex | W2970787375 |
| Language | EN |
| Citations received | 24 |
| References cited | 12 |
Artificial neural network · Data mining · Data science · Educational Data Mining · Exploit · Learning analytics · Machine learning · Computer Science · Engineering · Online Learning and Analytics · Artificial Intelligence
Predicting at-risk university students based on their e-book reading behaviours by using machine learning classifiers
Artificial intelligence in online higher education
The role of strategic online engagement and content curation in professional branding and career advancement on social media platforms
Low-Overhead Learning Analytics
Analysis of Student Evaluation from the Perspective of Competency for Enhancing the Competency Strategies of College Counselors
Digital Aesthetics in the Age of Machine Learning
Towards actionable recommendations for exam preparation using isomorphic problem banks and Explainable Machine Learning
Predicting university dropout using machine learning
Early Success Prediction for Online Learners
Predicting Student Performance Using Clickstream Data and Machine Learning
Evaluation method for the comprehensive quality of students based on multi-source data fusion
To what extent has machine learning achieved in predicting online at-risk students? Evidence from quantitative meta-analysis
A comparison of machine learning algorithms for predicting student performance in an online mathematics game
Predicting problem-solving success in an office simulation applying N-grams and a random forest to behavioral process data
Massive LMS log data analysis for the early prediction of course-agnostic student performance
Is college students’ trajectory associated with academic performance
Leveraging Large Language Models to Enhance Self‐Regulated Learning in Programming Education With Explainable AI
Understanding the focal points and sentiment of learners in Mooc reviews
Are family variables or personal characteristics more important? Based on the evidence among learners in developed and developing countries
A Framework for Detecting Factors Influencing Students’ Academic Performance
Enhancing the Detection of Social Desirability Bias Using Machine Learning
Technological professional development variables related to Teachers' Personal Information Management skills
E-learning enhancement through educational data mining with Covid-19 outbreak period in backdrop
We Have Big Data, But Do We Need Big Theory? Review-Based Remarks on an Emerging Problem in the Social Sciences
Understanding the massive open online course (Mooc) student experience
The current landscape of learning analytics in higher education
An Introduction to Kernel and Nearest-Neighbor Nonparametric Regression
Comparative analysis of the impact of traditional versus innovative learning environment on student attitudes and learning outcomes
The structure of phenotypic personality traits
Learning Analytics
The Big (Data) Bang
| Citations per year | 4 |
|---|---|
| Citation span | 2020 - 2026 (7) |
| Highly cited | No |