[HTML][HTML] Predictive Models for Educational Purposes: A Systematic Review

A Almalawi, B Soh, A Li, H Samra - Big Data and Cognitive Computing, 2024‏ - mdpi.com
This systematic literature review evaluates predictive models in education, focusing on their
role in forecasting student performance, identifying at-risk students, and personalising …

The influence of E-iearning, M-learning, and D-learning on the student performance: Moderating role of institutional support

MT Nuseir, AI Aljumah… - 2022 International Arab …, 2022‏ - ieeexplore.ieee.org
Student performance was affected due to the covid-19 pandemic; therefore, electronic (E),
mobile (M), and distance (D) learning are the significant solution for this issue and needs …

[HTML][HTML] XGBoost to enhance learner performance prediction

S Hakkal, AA Lahcen - Computers and Education: Artificial Intelligence, 2024‏ - Elsevier
The huge amount of data generated by an Intelligent Tutoring System becomes useful when
analyzed in an appropriate way to provide significant insights about learners, especially his …

[PDF][PDF] A systematic literature review on student performance predictions

H Nawang, M Makhtar, W Hamzah - International Journal of …, 2021‏ - researchgate.net
Prediction of student performance in educational institutions is a major topic of debate
among researchers in efforts to improve teaching and learning. Effective prediction …

[HTML][HTML] Artificial intelligence in higher education: A predictive model for academic performance

S Pacheco-Mendoza, C Guevara, A Mayorga-Albán… - Education …, 2023‏ - mdpi.com
This research work evaluates the use of artificial intelligence and its impact on student's
academic performance at the University of Guayaquil (UG). The objective was to design and …

Random Forest for rice yield map** and prediction using Sentinel-2 data with Google Earth Engine

K Choudhary, W Shi, Y Dong, R Paringer - Advances in Space Research, 2022‏ - Elsevier
Accurate information on crop yield prediction is essential for farmers, governments,
scientists, and agricultural agencies to make well-informed decisions. Majority of yield …

Pavement roughness prediction using explainable and supervised machine learning technique for long-term performance

K Sandamal, S Shashiprabha, N Muttil, U Rathnayake - Sustainability, 2023‏ - mdpi.com
Maintaining and rehabilitating pavement in a timely manner is essential for preserving or
improving its condition, with roughness being a critical factor. Accurate prediction of road …

[HTML][HTML] Real-time prediction of science student learning outcomes using machine learning classification of hemodynamics during virtual reality and online learning …

R Lamb, K Neumann, KA Linder - Computers and Education: Artificial …, 2022‏ - Elsevier
Current data sources used for the prediction of student outcomes average about 55%
accuracy and require a significant amount of input data and time for researchers and …

[HTML][HTML] Data mining-based decision support system for educational decision makers: Extracting rules to enhance academic efficiency

S Maniyan, R Ghousi, A Haeri - Computers and Education: Artificial …, 2024‏ - Elsevier
The exponential growth of data in the field of education has created a pressing demand for a
robust system capable of analyzing this vast amount of information, empowering decision …

Artificial intelligence in business education: Benefits and tools

C Surugiu, C Grădinaru, MR Surugiu - Amfiteatru Economic, 2024‏ - ceeol.com
Understanding the impact of artificial intelligence (AI) on education is vital for guiding
teachers in develo** educational tools. AI in education (AIEd) comes not only with …