Educational reforms and their impact on student performance: A review in African Countries

IS Adeniyi, NM Al Hamad, OE Adewusi… - World Journal of …, 2024 - wjarr.com
This comprehensive review delves into the educational reforms implemented across various
African countries and assesses their impact on student performance. With a focus on the …

Comparison of machine and deep learning algorithms using Google Earth Engine and Python for land classifications

A Nigar, Y Li, MY Jat Baloch, AF Alrefaei… - Frontiers in …, 2024 - frontiersin.org
Classifying land use and land cover (LULC) is essential for various environmental
monitoring and geospatial analysis applications. This research focuses on land …

Integrated constructive robotics in education (ICRE) model: a paradigmatic framework for transformative learning in educational ecosystem

A Alam, A Mohanty - Cogent Education, 2024 - Taylor & Francis
The researchers developed an Integrated Constructive Robotics in Education (ICRE) model
that represents a pioneering framework designed to revolutionize educational landscapes …

Energy Flow Analysis in Oilseed Sunflower Farms and Modeling with Artificial Neural Networks as Compared to Adaptive Neuro-Fuzzy Inference Systems (Case Study …

HL Nezhad, VR Sharabiani, J Tarighi, M Tahmasebi… - Energies, 2024 - mdpi.com
The evaluation of energy input and output processes in agricultural systems is a crucial
method for assessing sustainability levels within these systems. In this research, the …

Hybrid Approach to Predicting Learning Success Based on Digital Educational History for Timely Identification of At-Risk Students

TA Kustitskaya, RV Esin, YV Vainshtein… - Education Sciences, 2024 - mdpi.com
Student retention is a significant challenge for higher education institutions (HEIs). The fact
that a considerable number of dropouts from universities are primarily due to academic …

Predicting performance of students by optimizing tree components of random forest using genetic algorithm

M Chen, Z Liu - Heliyon, 2024 - cell.com
Prediction of student academic performance is still a problem because of the limitations of
the existing methods specifically low generalizability and lack of interpretability. This study …

An Efficient Deep Learning Approach for Prediction of Student Performance Using Neural Network

K Abid, N Aslam, M Fuzail, MS Maqbool… - VFAST Transactions on …, 2023 - vfast.org
In recent years, schools have shown interest in utilizing data mining to improve the quality of
education. To enhance academic performance, accurately predicting how students will …

[PDF][PDF] Exploring Predictive Models for Students' Performance in Exams: A Comparative Analysis of Regression Algorithms

FH Rizk, A Saleh, A Elgaml, A Elsakaan… - Full Length …, 2024 - researchgate.net
Student-centered analysis of academic performance is also the most important aspect in
improving education by being able to determine what measures work best, individualized …

A Framework to Identify Non-Achievers in eLearning Business Informatics Lab Courses

V Zakopoulos, I Georgakopoulos… - Journal of …, 2024 - ojs.bonviewpress.com
Abstract Learning Management Systems store valuable data in their repositories. Analyzing
such data could contribute to identifying non-achievers in eLearning courses. This study …

Flipped Classroom Trends: A Bibliometric Analysis

A Chitambram, NAH Sazalli - International Journal of Academic …, 2024 - ijarped.com
Analysing the flipped classroom framework is a crucial framework for informing teachers and
students about the evolving teaching and learning method. The connection for flipped …