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Multi-level computer aided learner assessment in massive open online courses

Lynda Haddadi Farida Bouarab Dahmani Nathalie Guin 1
1 TWEAK - Traces, Web, Education, Adaptation, Knowledge
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Assessment is at the heart of massive open online courses (MOOC) challenges. It is also a core component for any effective learning. In this paper, we provide a general survey of the various forms of assessment in MOOCs. Then, we propose gradual automated learners assessment based on ontology driven for auto-evaluation learning approach (ODALA) approach. Our proposition focuses on an assessment pyramid with four levels: Closed-ended questions, Half-open questions, Open-ended questions and problem solving (PS). This pyramid is the backbone of the learning process since it needs a gradual progression with an adequate methodology. Various computer aided or completely automated assessment activities are proposed. The transition from a level to another is a conditional one since there are minimal threshold of disciplinary knowledge acquisition. An evaluation prototype was tested with the Algorithmic discipline and was developed to access the feasibility of our proposition.
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Submitted on : Tuesday, November 27, 2018 - 10:10:48 PM
Last modification on : Tuesday, June 1, 2021 - 2:08:10 PM



Lynda Haddadi, Farida Bouarab Dahmani, Nathalie Guin. Multi-level computer aided learner assessment in massive open online courses. International Journal of Knowledge and Learning, Inderscience, 2018, 12 (4), ⟨10.1504/IJKL.2018.095958⟩. ⟨hal-01937121⟩



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