A Systematic Literature Review of Student’ Performance Prediction Using Machine Learning Techniques

Published in

Education sciences(2021)

External Links:

TL;DR

The review results indicated that various Machine Learning techniques are used to understand and overcome the underlying challenges; predicting students at risk and students drop out prediction and improving the students’ performance.

Abstract

Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding the student learning environment by exploring and utilizing educational data using machine learning and data mining techniques. Modern academic institutions operate in a highly competitive and complex environment. Analyzing performance, providing high-quality education, strategies for evaluating the students’ performance, and future actions are among the prevailing challenges universities face. Student intervention plans must be implemented in these universities to overcome problems experienced by the students during their studies. In this systematic review, the relevant EDM literature related to identifying student dropouts and students at risk from 2009 to 2021 is reviewed. The review results indicated that various Machine Learning (ML) techniques are used to understand and overcome the underlying challenges; predicting students at risk and students drop out prediction. Moreover, most studies use two types of datasets: data from student colleges/university databases and online learning platforms. ML methods were confirmed to play essential roles in predicting students at risk and dropout rates, thus improving the students’ performance.

Authors

Balqis Albreiki

1 papers

Nazar Zaki

1 papers

Hany Alashwal

1 papers

References89 items

Significance of Non-Academic Parameters for Predicting Student Performance Using Ensemble Learning Techniques

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Predicting Student Performance Using Data Mining and Learning Analytics Techniques: A Systematic Literature Review

Mining Educational Data to Analyze Students’ Performance: A Case Study of Mawuli School, Ho

Predicting at-risk university students in a virtual learning environment via a machine learning algorithm

A Systematic Literature Review of Student’ Performance Prediction Using Machine Learning Techniques

Published in

Education sciences(2021)

External Links:

Generate Graph DownloadPDF

TL;DR

Abstract

Authors

Balqis Albreiki

1 papers

Nazar Zaki

1 papers

Hany Alashwal

1 papers

References89 items

Significance of Non-Academic Parameters for Predicting Student Performance Using Ensemble Learning Techniques

Deep learning for AI

Predicting Student Performance Using Data Mining and Learning Analytics Techniques: A Systematic Literature Review

Mining Educational Data to Analyze Students’ Performance: A Case Study of Mawuli School, Ho

Predicting at-risk university students in a virtual learning environment via a machine learning algorithm

Analysis of Students’ Academic Performance by Using Machine Learning Tools

Student’s Academic Performance Prediction in Academic using Data Mining Techniques

Measuring and Enhancing the Performance of Undergraduate Student Using Machine Learning Tools

Analysis and Prediction of Student Academic Performance Using Machine Learning

A Novel Metaheuristic Approach to Optimization of Neuro-Fuzzy System for Students' Performance Prediction

Predicting academic success in higher education: literature review and best practices

Crowd Counting with respect to Age and Gender by using Faster R-CNN based Detection

The potential for student performance prediction in small cohorts with minimal available attributes

Dropout Prediction in MOOCs: Using Deep Learning for Personalized Intervention

Application of Machine Learning in Predicting Performance for Computer Engineering Students: A Case Study

A Systematic Review of Deep Learning Approaches to Educational Data Mining

Remedial Actions Recommendation via multi-Label Classification: A Course Learning Improvement Method

Temporal specificity-based text classification for information retrieval

Modelling student online behaviour in a virtual learning environment

Student and school performance across countries: A machine learning approach

Dynamic Knowledge Modeling with Heterogeneous Activities for Adaptive Textbooks

Predicting academic performance: a systematic literature review

Supporting academic decision making at higher educational institutions using machine learning-based algorithms

Using machine learning to predict student difficulties from learning session data

Machine Learning Based Student Grade Prediction: A Case Study

Analysis of Students' Performance by Using Different Data Mining Classifiers

Analyzing students’ performance using multi-criteria classification

Deep Model for Dropout Prediction in MOOCs

Student Performance Prediction via Online Learning Behavior Analytics

A Machine Learning Approach for Tracking and Predicting Student Performance in Degree Programs

MOOC Dropout Prediction: Lessons Learned from Making Pipelines Interpretable

Predicting Student Performance using Advanced Learning Analytics

Student performance prediction using Support Vector Machine and K-Nearest Neighbor

Data mining for modeling students' performance: A tutoring action plan to prevent academic dropout

Models for early prediction of at-risk students in a course using standards-based grading

Course Learning Outcome Performance Improvement: A Remedial Action Classification Based Approach

Machine learning application in MOOCs: Dropout prediction

PREDICTING ACADEMIC PERFORMANCE FROM BEHAVIOURAL AND LEARNING DATA

Predicting Student Dropout in Higher Education

Temporal predication of dropouts in MOOCs: Reaching the low hanging fruit through stacking generalization

Early dropout prediction using data mining: a case study with high school students

Temporal Models for Predicting Student Dropout in Massive Open Online Courses

Estimating student dropout in distance higher education using semi-supervised techniques

A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes

Exploring Machine Learning Methods to Automatically Identify Students in Need of Assistance

OU Analyse: analysing at-risk students at The Open University

Prediction of Student Dropout in E-Learning Program Through the Use of Machine Learning Method

Identifying At-Risk Students in Massive Open Online Courses

Early Prediction of Student Dropout and Performance in MOOCs using Higher Granularity Temporal Information

Early Prediction of Students Performance using Machine Learning Techniques

Predicting MOOC Dropout over Weeks Using Machine Learning Methods

Developing early warning systems to predict students' online learning performance

Predicting Dropout Student: An Application of Data Mining Methods in an Online Education Program

Predicting Performance in an Introductory Programming Course by Logging and Analyzing Student Programming Behavior

Scaffolding students' learning using test my code

Using artificial neural networks to predict first-year traditional students second year retention rates

Predicting student failure at school using genetic programming and different data mining approaches with high dimensional and imbalanced data

Mining Educational Data to Reduce Dropout Rates of Engineering Students

Use of machine learning techniques for educational proposes: a decision support system for forecasting students’ grades

Mining Educational Data to Analyze Students' Performance

Are Student Evaluations of Teaching Effectiveness Valid for Measuring Student Learning Outcomes in Business Related Classes? A Neural Network and Bayesian Analyses

Handbook of Educational Data Mining

A combinational incremental ensemble of classifiers as a technique for predicting students' performance in distance education

Drop Out Feature of Student Data for Academic Performance Using Decision Tree Techniques

Dropout prediction in e-learning courses through the combination of machine learning techniques

Enhancing prediction of student success: Automated machine learning approach

Student Performance Analyser Using Supervised Learning Algorithms. 2021

Mining for Predicting Student Success based on Interaction with the Virtual Learning Environment using Artificial Neural Network

Comparing Different Resampling Methods in Predicting Students’ Performance Using Machine Learning Techniques

Predicting secondary school students

A Study of Feature Selection Algorithms for Predicting Students Academic Performance

Exploring the high potential factors that affect students

Predicting Students Final GPA Using Decision Trees: A Case Study

The Prediction of Students' Academic Performance Using Classification Data Mining Techniques

High-School Dropout Prediction Using Machine Learning: A Danish Large-scale Study

Data Mining: A prediction for Student's Performance Using Classification Method

How to write a systematic literature review: A guide for medical students

Linear models of student skills for static data

DATA MINING APPROACH FOR PREDICTING STUDENT PERFORMANCE

A Dynamical System Model of Microgenetic Changes in Performance, Efficacy, Strategy Use and Value during Vocabulary Learning

Recommender system for predicting student performance

Early Prediction of Student Success: Mining Students Enrolment Data

Educational data mining: a case study for predicting dropout-prone students

Early and dynamic student achievement prediction in e-learning courses using neural networks

Specialised Tools for Automating Data Mining for Hospital Management

Procedures for Performing Systematic Reviews

USERʼS GUIDE TO THE ORTHOPAEDIC LITERATURE

Communications of the Association for Information Systems Communications of the Association for Information Systems

World Wide Web Companion, International World Wide Web Conferences Steering Committee

Field of Study

Computer Science

Journal Information

Name

Education Sciences

Venue Information

Name

Education sciences

Type

journal

URL

http://nevelestudomany.elte.hu/

Alternate Names

Educ Sci
Education Sciences
Educ sci