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2024 | OriginalPaper | Chapter

A Task-Interaction Framework to Monitor Mobile Learning Activities Based on Artificial Intelligence and Augmented Reality

Authors : Marco Arrigo, Mariella Farella, Giovanni Fulantelli, Daniele Schicchi, Davide Taibi

Published in: Extended Reality

Publisher: Springer Nature Switzerland

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Abstract

The complexity behind the analysis of mobile learning activities has requested the development of specifically designed frameworks. When students are involved in mobile learning experiences, they interact with the context in which the activities occur, the content they have access to, with peers and their teachers. The wider adoption of generative artificial intelligence introduces new interactions that researchers have to look at when learning analytics techniques are applied to monitor learning patterns. The task interaction framework proposed in this paper explores how AI-based tools affect student-content and student-context interactions during mobile learning activities, thus focusing on the interplay of Learning Analytics and Artificial Intelligence advances in the educational domain. A use case scenario that explores the framework’s application in a real educational context is also presented. Finally, we describe the architectural design of an environment that leverages the task interaction framework to analyze enhanced mobile learning experiences in which structured content extracted from a Knowledge Graph is elaborated by a large language model to provide students with personalized content.

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Metadata
Title
A Task-Interaction Framework to Monitor Mobile Learning Activities Based on Artificial Intelligence and Augmented Reality
Authors
Marco Arrigo
Mariella Farella
Giovanni Fulantelli
Daniele Schicchi
Davide Taibi
Copyright Year
2024
DOI
https://doi.org/10.1007/978-3-031-71707-9_26

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