The "flat peer learning" agent-based model.

IF 2 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS
Journal of Computational Social Science Pub Date : 2022-01-01 Epub Date: 2021-05-30 DOI:10.1007/s42001-021-00120-0
Philippe Collard
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引用次数: 2

Abstract

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.

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Abstract Image

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基于代理的“平面对等学习”模型。
本文讨论同伴学习,特别是排斥现象;它建议建模一组学习者,其中每个人都有自己的行为,表达他遵循课程的方式。重点是个人动机,以避免某些人处于不利地位,同时优化社区一级的行为;在这种情况下,该方法基于这样一种信念,即诱导学习动力学可以通过基于智能体的建模及其进入同伴学习模拟领域的贡献来澄清。扁平化学习意味着每个学习者具有相同的初始技能水平,并且有相同的机会独立学习和在同伴的帮助下学习。为了解决这个问题,本文提出了受维果茨基的社会和学习理论启发的基于智能体的平面同伴学习计算模型。这篇论文表明,即使严格的公平可以得到保证,教育工作者仍然面临着必须在优化群体的学习过程或防止某些人被排斥之间做出选择的困境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Computational Social Science
Journal of Computational Social Science SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
6.20
自引率
6.20%
发文量
30
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