AHCI RESEARCH GROUP

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proceedings of conferences, workshops and books.

OUR RESEARCH

Scientific Publications

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2024

Arrigo, M.; Farella, M.; Fulantelli, G.; Schicchi, D.; Taibi, D.

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

In: L.T., De Paolis; P., Arpaia; M., Sacco (Ed.): Lect. Notes Comput. Sci., pp. 325–333, Springer Science and Business Media Deutschland GmbH, 2024, ISBN: 03029743 (ISSN); 978-303171706-2 (ISBN).

Abstract | Links | BibTeX | Tags: Activity-based, Adversarial machine learning, Analytic technique, Augmented Reality, Contrastive Learning, Federated learning, Generative AI, Interaction framework, Learning Activity, Learning analytic framework, Learning Analytics Framework, Learning experiences, Learning patterns, Mobile Learning, Teachers'

@inproceedings{arrigo_task-interaction_2024,

title = {A Task-Interaction Framework to Monitor Mobile Learning Activities Based on Artificial Intelligence and Augmented Reality},

author = {M. Arrigo and M. Farella and G. Fulantelli and D. Schicchi and D. Taibi},

editor = {De Paolis L.T. and Arpaia P. and Sacco M.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204618733&doi=10.1007%2f978-3-031-71707-9_26&partnerID=40&md5=8969f18ab0f10dcddf37e54265d10518},

doi = {10.1007/978-3-031-71707-9_26},

isbn = {03029743 (ISSN); 978-303171706-2 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Lect. Notes Comput. Sci.},

volume = {15027 LNCS},

pages = {325–333},

publisher = {Springer Science and Business Media Deutschland GmbH},

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. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.},

keywords = {Activity-based, Adversarial machine learning, Analytic technique, Augmented Reality, Contrastive Learning, Federated learning, Generative AI, Interaction framework, Learning Activity, Learning analytic framework, Learning Analytics Framework, Learning experiences, Learning patterns, Mobile Learning, Teachers'},

pubstate = {published},

tppubtype = {inproceedings}

}