Examining the potential of machine learning for predicting academic achievement: A systematic review

QR Code

Examining the potential of machine learning for predicting academic achievement: A systematic review

Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. The capability to forecast student performance empowers universities to devise an intervention strategy either at the beginning of a...

Full description

Bibliographic Details
Main Authors:	Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi
Format:	Article
Language:	English
Published:	American Scientific Publishing Group (ASPG) 2023
Subjects:	QA75 Electronic computers. Computer science
Online Access:	https://umpir.ump.edu.my/id/eprint/38938/

Similar Items

Transforming education with deep learning: A systematic review on predicting student performance and critical challenges
by: Nazir, M., et al.
Published: (2025)

Students’ Performance Prediction in Higher Education Using Multi-Agent Framework-Based Distributed Data Mining Approach: A Review
by: Nazir, M., et al.
Published: (2023)

A review on disaster prediction using machine learning
by: Farghaly, Alaa Taiseer, et al.
Published: (2024)

Systematic review of using machine learning in imputing missing values
by: Alabadla, Mustafa, et al.
Published: (2022)

Comparative analysis of machine learning models to predict common vulnerabilities and exposure
by: Shaesta Khan, Sheh Rahman, et al.
Published: (2024)

Systematic Literature Review on Visual Analytics of Predictive Maintenance in the Manufacturing Industry
by: Cheng, Xiang, et al.
Published: (2022)

Predicting Parkinson’s Disease Using Machine Learning Model
by: Sanjay Aswath, K.S.M, et al.
Published: (2024)

Breast Cancer Prediction Model Using Machine Learning
by: Muhammad Amin, Bakri, et al.
Published: (2021)

Risk Status Prediction and Modelling Of Students’ Academic Achievement - A Fuzzy Logic Approach
by: Raheem, Ajiboye Adeleke, et al.
Published: (2013)

Development of an intelligent prediction tool for rice yield based on machine learning techniques
by: Md. Sap, Mohd. Noor, et al.
Published: (2006)

Stock Market Value Prediction Based On Machine Learning Approach
by: Chew, Min Wei
Published: (2023)

Similarity-Based Weights For Cross-Domain Sentiment Classification Of Product Reviews
by: Gupta, Aditi
Published: (2023)

Prediction of Fetal Health Status Using Machine Learning
by: Naidile S, Saragodu, et al.
Published: (2024)

Machine Learning Applications in Offense Type and Incidence Prediction
by: Balaji, R., et al.
Published: (2024)

A Systematic Review of Personalized Learning: Comparison between E-Learning and Learning by Coursework Program in Oman
by: Tawafak, Ragad M., et al.
Published: (2019)

Early prediction of acute kidney injury using machine learning algorithms
by: Ismail, Amelia Ritahani, et al.
Published: (2018)

Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques
by: Lim, Shi Ru
Published: (2022)

A system to predict pharmaceutical student performance using machine learning
by: Nurul Nazihah, Sukor
Published: (2019)

The Crop Price Prediction Using Machine Learning: Preliminary Stage
by: Ramya, T.K., et al.
Published: (2024)

Machine learning techniques for software bug prediction: a systematic review
by: Saharudin, Syahana Nur’Ain, et al.
Published: (2020)

Psychosocial predictors of academic achievement of adolescents: practical reference on employment of SEM: examining variables that were predictive of adolescents’ academic achievement
by: Ismail, Khamsiah, et al.
Published: (2012)

Technical approach in text mining for stock market prediction: a systematic review
by: Islam, Mohammad Rabiul, et al.
Published: (2018)

Machine learning algorithms for early predicting dropout student online learning
by: Dewi, Meta Amalya, et al.
Published: (2023)

Diabetic Retinopathy Prediction Using Machine Learning
by: Ravikiran, Y., et al.
Published: (2024)

Big Data and Machine Learning-Based Iot Models for Sustainable Energy Prediction
by: Sravani, Parvathareddy, et al.
Published: (2024)

Application of machine learning algorithms to predict the thyroid disease risk: an experimental comparative study
by: Islam, Saima Sharleen, et al.
Published: (2022)

Breast cancer prediction: A comparative study using machine learning techniques
by: Islam, Md. Milon, et al.
Published: (2020)

Review : Machine and deep learning methods in Malaysia for COVID-19
by: Mohammed Adam Kunna, Azrag, et al.
Published: (2023)

Technology Acceptance Model in M-learning context: A systematic review
by: Al-Emran, Mostafa, et al.
Published: (2018)

Text-based emotion prediction system using machine learning approach
by: Ahmad Fakhri, Ab. Nasir, et al.
Published: (2020)

Predicting the stress level of students using supervised machine learning and artificial neural network (ANN)
by: Arya, Suraj, et al.
Published: (2024)

Predicting android app success before google play store launch using machine learning
by: Aleem, Muhammad, et al.
Published: (2024)

Predicting mental health disorder on twitter using machine learning techniques
by: Lim, Shi Ru, et al.
Published: (2023)

Edge assisted crime prediction and evaluation framework for machine learning algorithms
by: Adhikary, Apurba, et al.
Published: (2022)

Crop classification and yield prediction using robust machine learning models for agricultural sustainability
by: Badshah, Abid, et al.
Published: (2024)

Financial time series predicting using machine learning algorithms
by: Tiong, Leslie Ching Ow *
Published: (2013)

One-class support vector machines for protein-protein interactions prediction
by: Alashwal, H., et al.
Published: (2006)

A systematic literature review of an advisory system
by: Ain Nadhira, Mohd Taib, et al.
Published: (2024)

First Semester Examination 2020/2021 Academic Session
by: PPSKOM, Pusat Pengajian Sains Komputer
Published: (2021)

Predicting the success of suicide terrorist attacks using different machine learning algorithms
by: Hossain, Md Junayed, et al.
Published: (2022)