1. Towards fine-grained reading dashboards for online course revision
- Author
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Benoît Encelle, Madjid Sadallah, Yannick Prié, Azze-Eddine Maredj, Centre de recherche sur l'Information Scientifique et Technique (CERIST), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), Situated Interaction, Collaboration, Adaptation and Learning (SICAL), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Data User Knowledge (DUKe), Laboratoire des Sciences du Numérique de Nantes (LS2N), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), and Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
050101 languages & linguistics ,Computer science ,media_common.quotation_subject ,Dashboard (business) ,Learning analytics ,computer.software_genre ,Education ,[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] ,Online course ,Reading (process) ,ComputingMilieux_COMPUTERSANDEDUCATION ,Curriculum development ,0501 psychology and cognitive sciences ,[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC] ,Set (psychology) ,ComputingMilieux_MISCELLANEOUS ,media_common ,Multimedia ,4. Education ,05 social sciences ,Educational technology ,050301 education ,Course evaluation ,[INFO.EIAH]Computer Science [cs]/Technology for Human Learning ,0503 education ,computer - Abstract
Providing high-quality courses is of utmost importance to drive successful learning. This compels course authors to continuously review their contents to meet learners’ needs. However, it is challenging for them to detect the reading barriers that learners face with content, and to identify how their courses can be improved accordingly. In this paper, we propose a learning analytics approach for assisting course authors performing these tasks. Using logs of learners’ activity, a set of indicators related to course reading activity are computed and used to detect issues and to suggest content revisions. The results are presented to authors through CoReaDa, a learning dashboard empowered with assistive features. We instantiate our proposals using the logs of a major European e-learning platform, and validate them through a study. Study results show the effectiveness of our approach providing authors with more awareness and guidance in improving their courses, to better suit learners’ requirements.
- Published
- 2020