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Authors: Azer Nouira ; Lilia Cheniti-Belcadhi and Rafik Braham

Affiliation: PRINCE Research Lab ISITCom, H- Sousse and Sousse University, Tunisia

Keyword(s): Learning Analytics, Learning Analytics Models, Assessment Analytics, Ontology.

Related Ontology Subjects/Areas/Topics: Internet Technology ; Protocols and Standards ; Web Information Systems and Technologies

Abstract: Today, there is a growing interest in data and analytics in the learning environment resulting in a highly qualified research concerning models, methods, tools, technologies and analytics. This research area is referred to as learning analytics. Metadata becomes an important item in an e-learning system, many learning analytics models are currently developed. They use metadata to tag learning materials, learning resources and learning activities. In this paper, we firstly give a detailed injection of the existing learning analytics models in the literature. We particularly observed that there is a lack of models dedicated to conceive and analyze the assessment data. That is why our objective in this paper is to propose an assessment analytics model inspired by the Experience API data model. Hence, an assessment analytics ontology model is developed supporting the analytics of assessment data by tracking the assessment activities, assessment result and assessment context of the learner.

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Paper citation in several formats:
Nouira, A.; Cheniti-Belcadhi, L. and Braham, R. (2017). An Ontological Model for Assessment Analytics. In Proceedings of the 13th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-246-2; ISSN 2184-3252, SciTePress, pages 243-251. DOI: 10.5220/0006284302430251

@conference{webist17,
author={Azer Nouira. and Lilia Cheniti{-}Belcadhi. and Rafik Braham.},
title={An Ontological Model for Assessment Analytics},
booktitle={Proceedings of the 13th International Conference on Web Information Systems and Technologies - WEBIST},
year={2017},
pages={243-251},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006284302430251},
isbn={978-989-758-246-2},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Web Information Systems and Technologies - WEBIST
TI - An Ontological Model for Assessment Analytics
SN - 978-989-758-246-2
IS - 2184-3252
AU - Nouira, A.
AU - Cheniti-Belcadhi, L.
AU - Braham, R.
PY - 2017
SP - 243
EP - 251
DO - 10.5220/0006284302430251
PB - SciTePress