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Predictive Analytical Framework based on Formal Method to Enhance Mobile and Pervasive Learning Experience

Topics: Application of Mobile Information Systems; Application, Research project and Internet Technology; Application, Research project and Service Based IS; Applications, Research Projects and Web Intelligence; Context, Adaptability and Web Intelligence; Usability and Ergonomics; User-Centric Systems; Web Interface and Adaptability according to context and/or profile; Web Tools and Languages

Authors: Manel BenSassi ; Mona Laroussi and Henda BenGhezala

Affiliation: Riadi Laboratory, National School of Computer Science, Manouba University and Tunisia

Keyword(s): Learning Experience Design, Mobile Learning Scenario, Reliability, Predictive Analytics, Formal Method.

Related Ontology Subjects/Areas/Topics: Usability and Ergonomics ; Web Information Systems and Technologies ; Web Interfaces and Applications

Abstract: In this paper, we present a predictive analytical framework for mobile and ubiquitous learning environment based on three main dimensions: learner, contextualized activity and space. The main objective of this proposal is to assist pedagogical designer in developing engaging and effective courses by focusing on the learner’s experience and his learning environment. To do that, a solid structure is essential to organize correlations between different activities and to assess their reliability with the learner’s context. The strengths of our proposal lie in the fact that, in a formal manner through friendly graphical interfaces, it allows pedagogical designers:(1) to specify, model, simulate, analyse and verify different types of context-aware and adaptive learning activities and their related contexts, (2) to assess the reliability of the indoor and outdoor learning spaces within pervasive environment through factual cases and to experiment various learning scenarios, (3) To simulate and to verify interactions and co-adaptability rules between learner, contextualized activity and space. (More)

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Paper citation in several formats:
BenSassi, M.; Laroussi, M. and BenGhezala, H. (2018). Predictive Analytical Framework based on Formal Method to Enhance Mobile and Pervasive Learning Experience. In Proceedings of the 14th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-324-7; ISSN 2184-3252, SciTePress, pages 231-238. DOI: 10.5220/0006935802310238

@conference{webist18,
author={Manel BenSassi. and Mona Laroussi. and Henda BenGhezala.},
title={Predictive Analytical Framework based on Formal Method to Enhance Mobile and Pervasive Learning Experience},
booktitle={Proceedings of the 14th International Conference on Web Information Systems and Technologies - WEBIST},
year={2018},
pages={231-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006935802310238},
isbn={978-989-758-324-7},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Web Information Systems and Technologies - WEBIST
TI - Predictive Analytical Framework based on Formal Method to Enhance Mobile and Pervasive Learning Experience
SN - 978-989-758-324-7
IS - 2184-3252
AU - BenSassi, M.
AU - Laroussi, M.
AU - BenGhezala, H.
PY - 2018
SP - 231
EP - 238
DO - 10.5220/0006935802310238
PB - SciTePress