Assessment and evaluation of different machine learning algorithms for predicting student performance

YA Alsariera, Y Baashar, G Alkawsi… - Computational …, 2022 - Wiley Online Library
Student performance is crucial to the success of tertiary institutions. Especially, academic
achievement is one of the metrics used in rating top‐quality universities. Despite the large …

Machine learning in biohydrogen production: a review

A Alagumalai, B Devarajan, H Song… - Biofuel Research …, 2023 - biofueljournal.com
Biohydrogen is emerging as a promising carbon-neutral and sustainable energy carrier with
high energy yield to replace conventional fossil fuels. However, biohydrogen commercial …

[HTML][HTML] Toward predicting student's academic performance using artificial neural networks (ANNs)

Y Baashar, G Alkawsi, A Mustafa, AA Alkahtani… - Applied Sciences, 2022 - mdpi.com
Student performance is related to complex and correlated factors. The implementation of a
new advancement of technologies in educational displacement has unlimited potentials …

[HTML][HTML] Analysis of machine learning strategies for prediction of passing undergraduate admission test

MAA Walid, SMM Ahmed, M Zeyad, SMS Galib… - International Journal of …, 2022 - Elsevier
This article primarily focuses on understanding the reasons behind the failure of
undergraduate admission seekers using different machine learning (ML) strategies. An …

The impact of AI on teaching and learning in higher education technology

SV Singh, KK Hiran - Journal of Higher Education Theory and …, 2022 - articlearchives.co
Thanks to AI, students may now study whenever and wherever they like. Personalized
feedback on assignments, quizzes, and other assessments can be generated using AI …

[HTML][HTML] Aisar: Artificial intelligence-based student assessment and recommendation system for e-learning in big data

W Bagunaid, N Chilamkurti, P Veeraraghavan - Sustainability, 2022 - mdpi.com
Educational systems have advanced with the use of electronic learning (e-learning), which
is a promising solution for long-distance learners. Students who engage in e-learning can …

Feasibility of breast cancer detection through a convolutional neural network in mammographs

FM Ahmed, BS MOHAMMED - Tamjeed Journal of Healthcare …, 2023 - tamjeedpub.com
In the Iraq female samples, the malignant neoplasm type with the highest mortality rate is
breast cancer. When the disease is detected early, the success rate is higher, resulting in …

[HTML][HTML] The implementation of the cognitive theory of multimedia learning in the design and evaluation of an AI educational video assistant utilizing large language …

R AlShaikh, N Al-Malki, M Almasre - Heliyon, 2024 - cell.com
Abstract The integration of Artificial Intelligence (AI) holds immense potential for
revolutionizing education; especially, in contexts where multimodal learning experiences …

[HTML][HTML] Analysis of the factors affecting student performance using a neuro-fuzzy approach

M Abou Naaj, R Mehdi, EA Mohamed, M Nachouki - Education Sciences, 2023 - mdpi.com
Predicting students' academic performance and the factors that significantly influence it can
improve students' completion and graduation rates, as well as reduce attrition rates. In this …

[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 …