The application of AI technologies in STEM education: a systematic review from 2011 to 2021

W Xu, F Ouyang - International Journal of STEM Education, 2022 - Springer
Background The application of artificial intelligence (AI) in STEM education (AI-STEM), as an
emerging field, is confronted with a challenge of integrating diverse AI techniques and …

A systematic review on machine learning models for online learning and examination systems

S Kaddoura, DE Popescu, JD Hemanth - PeerJ Computer Science, 2022 - peerj.com
Examinations or assessments play a vital role in every student's life; they determine their
future and career paths. The COVID pandemic has left adverse impacts in all areas …

Theories and models of emotions, attitudes, and self-efficacy in the context of programming education

L Malmi, J Sheard, P Kinnunen, Simon… - Proceedings of the 2020 …, 2020 - dl.acm.org
Research into the relationship between learning computing and students' attitudes, beliefs,
and emotions often builds on theoretical frameworks from the social sciences in order to …

[PDF][PDF] Application of machine learning methods to predict student performance: a systematic literature review

AA Enughwure, ME Ogbise - Int. Res. J. Eng. Technol, 2020 - academia.edu
In recent times, the need for the application of machine learning in the educational frontier
has become crucial. Most educational administrators and researchers are using various …

Early gestational diabetes mellitus diagnosis using classification algorithms: an ensemble approach

OOS Abe, OO Obe, OK Boyinbode… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
In the next twenty years, Type 2 diabetes may affect over 50% of GDM patients, and infants
and adults can acquire the disease. It is critical to consider both the mother's and the …

[PDF][PDF] Prediction of erythemato squamous-disease using ensemble learning framework

EC Igodan, OO Obe, AFB Thompson… - Prediction of …, 2022 - researchgate.net
The erythemto-squamous (skin) disease is characterized by redundant and noisy features.
One of the biggest challenges in the artificial intelligence field has been finding relevant …

[PDF][PDF] Predicting the Effect of Mobile Phone on Student Academic Performance Using Machine Learning

S Yau, AA Ishola, AI Adamu - Int. J. Sci. Res. in Computer Science …, 2024 - researchgate.net
The study aimed to predict the effect of mobile phones on students' academic performance
using Machine Learning, focusing on the Faculty of Science at the Federal University Birnin …

Analítica de enseñanza y aprendizaje en cursos de programación

JCF Quinteros, JAJ Builes, JWB Bedoya - Campus Virtuales, 2022 - uajournals.com
La enseñanza de la programación requiere del desarrollo de habilidades cognitivas de alto
orden, lo que exige un gran esfuerzo por parte de estudiantes y profesores. Las altas tasas …

[PDF][PDF] A deep neural network for the identification of lead molecules in antibiotics discovery

MI Oladunjoye, OO Obe… - … Artificial Intelligence in …, 2022 - academia.edu
In this study, we develop a deep neural network (DNN) model, multi-layer perceptron (MLP)
to classify the molecules into “active” and “inactive” compounds using a ligand-based virtual …

[PDF][PDF] The Impact of Coating Ingredients on the Aging Resistance of Topcoat Paints by Model Trees

TT Wong, SH Hung - Advances in Technology Innovation, 2020 - distantreader.org
Topcoat paint is mainly composed of resin and pigment and hence its quality highly
depends on the type and proportion of these two ingredients. This study aims at testing the …