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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) DIROSAT: Journal of Education, Social Sciences & Humanities
Mohamed, Khaldi
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Humanities Computer Science & IT Engineering Social Sciences Other

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Model for motivating learners with personalized learning objects in a hypermedia adaptive learning system Ikram, Chelliq; Lamya, Anoir; Mohamed, Erradi; Mohamed, Khaldi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1282-1293

Abstract

A number of weaknesses were demonstrated in the E-learning platforms during the Covid-19 pandemic despite the efforts invested. This has negatively influenced learners' motivation and consequently their performance. With the proliferation of technology and the revolution of information and communication technologies (ICT), learning objects have become new epitomes widely used, accessible, and implemented with educational resources and technological support. The integration of learning objects into E-learning has enhanced educational progress, but during critical periods, it is crucial to ensure pedagogical continuity and learner motivation. Based on this observation, we will propose architecture of a personalized learning object model in the context of an adaptive hypermedia learning system (AHS). The objective of our model is to increase the motivation factor which is a determining element in the success of E-learning, our model aims to improve the performance of the learners in order to avoid the abounding of learning and to promote the attendance of the learners. This will be useful later for any design or development of learning objects in hypermedia learning systems that are adaptive to the needs of the learners and in line with their preferences and profiles throughout the learning process offered by the system. 
KH Integration of AI Applications in High School Physics, Kolb’s Convergent Style Kemouss, Hassane; Abdannour, Omar; Mohamed, Khaldi
DIROSAT: Journal of Education, Social Sciences & Humanities Vol. 2 No. 3 (2024): Innovation in Education and Social Sciences Research
Publisher : Perkumpulan Dosen Fakultas Agama Islam Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58355/dirosat.v2i3.80

Abstract

This study explores the integration of artificial intelligence (AI) applications in physics teaching at the secondary level. An interactive approach based on Kolb's learning model; The authors evaluated the convergent style of the kolb cycle with the use of simulations and AI-based data analysis systems to improve students' understanding of abstract physics concepts. The results show that these AI tools allow a more intuitive visualization of phenomena and facilitate the interpretation of experimental data. Students who used these resources demonstrated better performance and greater engagement with the subject. This research highlights the potential of AI to enrich physics learning in high school and opens the way to new innovative educational approaches.
Co-Authors Abdannour, Omar Ikram, Chelliq Kemouss, Hassane Lamya, Anoir Mohamed, Erradi