AI-Based Adaptive Learning - State of the Art

Ezzaim, Aymane; Dahbi, Aziz; Assad, Noureddine; Haidine, Abdelfatteh

doi:10.1007/978-3-031-26384-2_14

Cited by 3 publications

(1 citation statement)

References 36 publications

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“…This inspired the authors to look into techniques for awakening students' interest and boosting their motivation with the ultimate goal of enhancing their performance. Among the strategies explored, AI-based adaptive learning stood out as a potential answer [2]- [4]. Each student's unique demands are satisfied by this approach, which uses technology and individualized learning paths to adapt the learning process to fit their needs and preferences [5]- [7].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Implementing a Moodle Plug-in as an AI-based Adaptive Learning Solution on Learning Effectiveness: Case of Morocco

Ezzaim,

Dahbi,

Haidine

et al. 2024

Int. J. Interact. Mob. Technol.

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This article presents feedback on the implementation of an Artificial Intelligence-based adaptive learning Moodle plugin aimed at enhancing the engagement levels and academic performance of 102 Moroccan high school students. The primary objective of this study was to assess and compare the performance of students utilizing the adaptive learning system with those employing conventional learning methods. To guarantee the efficacy of this approach, a participant satisfaction survey and a comprehensive summative evaluation were conducted, revealing the positive impact of AI-based adaptive learning on the participants. The results of this study highlight the potential benefits of integrating AI-driven adaptive learning into high school computer science curricula, emphasizing how it may raise student engagement and academic performance. These results strengthen the determination to use this teaching methodology with students in future educational activities.

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Section: Introductionmentioning

confidence: 99%

The Impact of Implementing a Moodle Plug-in as an AI-based Adaptive Learning Solution on Learning Effectiveness: Case of Morocco

Ezzaim,

Dahbi,

Haidine

et al. 2024

Int. J. Interact. Mob. Technol.

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AI-based learning style detection in adaptive learning systems: a systematic literature review

Ezzaim,

Dahbi,

Aqqal

et al. 2024

J. Comput. Educ.

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AI-based adaptive instructional systems for maritime safety training: a systematic literature review

Karimi,

Smith,

Billard

et al. 2024

Discov Artif Intell

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Adaptive instructional systems (AISs) refer to educational interventions designed to accommodate individual learner differences. These systems employ various approaches, such as artificial intelligence (AI), machine learning (ML), and data analytics, to analyze student performance and personalize the learning experience. This article presents a review of the current state-of-the-art of AI methods used in the development of AISs for maritime safety training. The main objective of this systematic literature review is to determine the use of AI/ML techniques in AIS and how they can contribute to the development of AIS for maritime education and training (MET) applications in addressing small data problems. Answering the research questions of the review identifies the fundamental purposes of using AI/ML techniques in developing AIS for MET. Further, the review highlights several crucial research areas, including AI techniques for modelling student and instructor knowledge, as well as ML algorithms for predicting student performance in situations with limited datasets.

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AI-Based Adaptive Learning - State of the Art

Cited by 3 publications

References 36 publications

The Impact of Implementing a Moodle Plug-in as an AI-based Adaptive Learning Solution on Learning Effectiveness: Case of Morocco

The Impact of Implementing a Moodle Plug-in as an AI-based Adaptive Learning Solution on Learning Effectiveness: Case of Morocco

AI-based learning style detection in adaptive learning systems: a systematic literature review

AI-based adaptive instructional systems for maritime safety training: a systematic literature review

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