An Intelligent Collaborative E-learning Strategy

G. A. Ebrahim
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引用次数: 5

Abstract

Evaluating learners in terms of collaboration capabilities in a collaborative e-learning session can be quantified based on several parameters. These parameters include learner's contribution in the collaborative e-learning session. They also include learner's collaboration history in collaborative e-learning sessions and the collaboration capabilities of the group in which he participates. These parameters can be used as inputs to a model that generates a set of recommendations for the next step that should be taken towards the e-learning objectives. These recommendations can be used to enroll the learner in an e-learning session that best fits his collaboration capabilities. In this paper, a fuzzy inference system is introduced to estimate learner's collaboration in terms of a proposed metric called collaboration-index. This index can be utilized to guide the e-learning system for advising the learner to the best choice of the next collaborative e-learning session. Simulation study has been carried out to evaluate the performance of the proposed strategy. Simulation results show that the proposed strategy provides a positive impact on collaborative e-learning environments.
智能协同电子学习策略
根据协作电子学习会话中的协作能力来评估学习者,可以基于几个参数进行量化。这些参数包括学习者在协作电子学习会话中的贡献。它们还包括学习者在协作电子学习会议中的协作历史,以及他所参与的小组的协作能力。这些参数可以用作模型的输入,该模型为下一步应采取的电子学习目标生成一组建议。这些建议可用于为学习者注册最适合其协作能力的电子学习会话。本文提出了一种模糊推理系统,用一种称为协作指标的度量来估计学习者的协作。该指标可用于指导电子学习系统,为学习者提供下一个协同电子学习会话的最佳选择。并进行了仿真研究,以评估所提出策略的性能。仿真结果表明,该策略对协同电子学习环境具有积极的影响。
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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