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Ubiquitous learning situations : quality-aware description and modelling

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Abstract

In ubiquitous environments, the heterogeneous and dynamic nature of context sensors besides their characteristics have a great importance on undermining the quality of the detected context and the whole situation described by that context. A recent interest had been made to manage the quality of low-level context in the ubiquitous learning (u-learning) field; however, the quality of the u-learning situation has never been a main concern. Hence, a quality-aware description and a quality-aware ontological model of the u-learning situation are proposed. Experimentation results are given to show the implication of the quality of situation in the enhancement of situation identification. Quality-based situation identification provided 52% of high-quality identified situations compared to only 38% for the standard identification showing an enhancement of 14% in high-quality situation identification.

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  1. http://siafusimulator.org/

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  1. RIADI Research Laboratory, ENSI-Manouba University, Manouba, Tunisia

    Ines Bayoudh Saâdi, Raoudha Souabni & Henda Ben Ghezala

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  1. Ines Bayoudh Saâdi
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Correspondence to Ines Bayoudh Saâdi.

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Saâdi, I.B., Souabni, R. & Ghezala, H.B. Ubiquitous learning situations : quality-aware description and modelling. Multimed Tools Appl 80, 17583–17609 (2021). https://doi.org/10.1007/s11042-021-10546-3

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