Authors :
Sara Benayache; Bouchrik Mourad
Volume/Issue :
Volume 9 - 2024, Issue 9 - September
Google Scholar :
https://tinyurl.com/4cc8hnb3
Scribd :
https://tinyurl.com/2c5nwjdf
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24SEP1667
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The study is based on a conceptual model to
examine the integration of artificial intelligence (AI)
technologies in education and their impact on student
engagement. This model structures the analysis around
several axes: AI technologies, including intelligent
tutoring systems (ITS), adaptive learning platforms, and
educational chatbots, play a key role in personalizing
learning paths, making pedagogical support more
accessible, and adapting content to students' specific
needs. Student engagement is thus assessed through the
personalization of pathways and the accessibility of
support, while taking into account individual moderating
factors such as learning styles, self-motivation, and prior
experience with AI technologies, which influence the
effectiveness of these tools. In addition, the study
examines contextual conditions, including the importance
of adequate technological infrastructure and teacher
training, which are essential for the successful integration
of AI technologies into pedagogical practices. This
conceptual model guides the study in evaluating the
assumptions made, providing an in-depth understanding
of the interactions between these variables and making
recommendations to optimize the use of AI technologies
in education.
Keywords :
Artificial Intelligence (AI)- Student Engagement- Personalization- Intelligent Tutoring Systems (ITS)- Adaptive Learning Platforms- Educational Chatbots- Teacher Training.
References :
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The study is based on a conceptual model to
examine the integration of artificial intelligence (AI)
technologies in education and their impact on student
engagement. This model structures the analysis around
several axes: AI technologies, including intelligent
tutoring systems (ITS), adaptive learning platforms, and
educational chatbots, play a key role in personalizing
learning paths, making pedagogical support more
accessible, and adapting content to students' specific
needs. Student engagement is thus assessed through the
personalization of pathways and the accessibility of
support, while taking into account individual moderating
factors such as learning styles, self-motivation, and prior
experience with AI technologies, which influence the
effectiveness of these tools. In addition, the study
examines contextual conditions, including the importance
of adequate technological infrastructure and teacher
training, which are essential for the successful integration
of AI technologies into pedagogical practices. This
conceptual model guides the study in evaluating the
assumptions made, providing an in-depth understanding
of the interactions between these variables and making
recommendations to optimize the use of AI technologies
in education.
Keywords :
Artificial Intelligence (AI)- Student Engagement- Personalization- Intelligent Tutoring Systems (ITS)- Adaptive Learning Platforms- Educational Chatbots- Teacher Training.