How to Help a Pedagogical Team of a MOOC Identify the “Leader Learners”?
This paper proposes a method for the identification of the “Leader Learners” within Massive Open Online Courses (MOOCs) in order to improve the support process. The “Leader Learners” are those who will be mobilized to animate the forum. Their role is to help the other learners find the information t...
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| creator | Bouzayane, Sarra Saad, Inès |
| description | This paper proposes a method for the identification of the “Leader Learners” within Massive Open Online Courses (MOOCs) in order to improve the support process. The “Leader Learners” are those who will be mobilized to animate the forum. Their role is to help the other learners find the information they need during the MOOC so as not to drop it. This method is based on the Dominance-based Rough Set Approach (DRSA) to infer a preference model generating a set of decision rules. The DRSA relies on the expertise of the human decision makers, who are in our case the pedagogical team, to make a multicriteria decision based on their preferences. This decision concerns the classification of learners either in the decision class Cl1 of the “Non Leader Learners” or in the decision class Cl2 of the “Leader Learners”. Our method is validated on a French MOOC proposed by a Business School in France. |
| doi_str_mv | 10.1007/978-3-319-52624-9_11 |
| format | Book Chapter |
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| fulltext | fulltext |
| identifier | ISSN: 1865-1348 |
| ispartof | Group Decision and Negotiation. Theory, Empirical Evidence, and Application, 2017, Vol.274 (LNBIP, volume 274), p.140-151 |
| issn | 1865-1348 1865-1356 |
| language | eng |
| recordid | cdi_hal_primary_oai_HAL_hal_01796317v1 |
| source | Springer Books |
| subjects | Artificial Intelligence Computer Science DRSA Leader Learner Machine Learning Massive open online courses Pedagogical team Preference model |
| title | How to Help a Pedagogical Team of a MOOC Identify the “Leader Learners”? |
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