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Article Dans Une Revue Journal of Computational Social Science Année : 2021

The “flat peer learning” agent-based model

Résumé

This paper deals with peer learning and, in particular, with the phenomena of exclusion; it proposes to model a group of learners where everyone has his own behaviour that expresses his way of following a curriculum. The focus is on individual motivations that avoid disadvantage certain individuals while optimising behaviour at the community level; in this context, the approach is based on the belief that the induced learning dynamics can be clarified by the contribution of agent-based modelling and its entry into the field of peer learning simulation. Flat learning means here that every learner features the same initial skill level, along with the same opportunities to learn both independently and with the help of peers. To address this topic the paper proposes the Flat Peer Learning agent-based computational model inspired by the Vygotsky's social and learning theory. The paper shows that even if strict equity could be guaranteed, educators would still be faced with the dilemma of having to choose between optimising the learning process for the group or preventing exclusion for some.

Dates et versions

hal-03281003 , version 1 (07-07-2021)

Identifiants

Citer

Philippe Collard. The “flat peer learning” agent-based model. Journal of Computational Social Science, 2021, ⟨10.1007/s42001-021-00120-0⟩. ⟨hal-03281003⟩
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