AI in Moroccan education: evaluating student acceptance using machine learning classification models

Khoual Mohamed, Elkaimbillah Zineb, Mcharfi Zineb, El Asri Bouchra

Abstract


Personalized learning is becoming a reality in education thanks to the rise of AI. This study investigates the possibilities of AI within the realm of education, focusing on the individualization of the learning experience. The research is based on the responses of 395 students from various faculties in Morocco. The questionnaire aimed to assess the students’ opinions of AI, their level of knowledge, their previous experiences, and their perception of the application of AI within educational settings. Employing classification techniques such as decision trees (DT), multilayer perceptron (MLP), and random forests (RF), our aim was to predict the receptivity of AI in education. The findings highlight significant differences in how Moroccan students perceive AI, identifying key factors such as familiarity with the technology, ethical concerns, and perception of its potential impact on the learning experience. Classification models showed varied performance in anticipating these attitudes. This study highlights the critical importance of understanding students’ perspectives on AI in education. These findings offer crucial insights for education policymakers as well as designers of educational technology solutions in Morocco. The findings can be used as a guide to adapt the incorporation of AI into the education sector with discernment, taking into account students’ perceptions and preferences.

Keywords


Artificial intelligence; Classification models; Educational sectors; Moroccan university; Personalized learning

Full Text:

PDF


DOI: http://doi.org/10.11591/ijeecs.v37.i1.pp452-462

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics