Ascertaining the More Knowledgeable Other among peers in collaborative e-learning environment

A. Safia, T. Mala
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引用次数: 7

Abstract

Collaborative E-Learning is an environment where in learners learn through interaction among peer group mates using computers. 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 sessions; collaboration history of a learner in collaborative e-learning sessions and the level of knowledge of the learner in the group in which he participates. In respect to this finding the More Knowledgeable Other (MKO) person refers to someone who has a better understanding and higher ability level than other learners, with respect to a particular task, process, or concept. He can make others learn effectively. By finding out the MKO it is possible to form effective and efficient group where in learner's learning capabilities in a group can be enhanced so that the peers in the group participate to maximum extent and there is an increase in knowledge level. In this paper, a fuzzy model is introduced to find out an MKO using an intelligent inference system to improve learner's learning capabilities in terms of a proposed metric called fuzzy associative matrix. This matrix can be utilized to guide the collaborative e-learning system for finding out the MKO as the best choice for very effective collaborative e-learning. Simulation study using NetLogo has been carried out to evaluate the performance of the proposed strategy. Simulation results show that the proposed strategy provides an optimal solution in ascertaining an MKO among peers in collaborative E-learning environments.
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协作式电子学习环境中同伴中更有知识的他者的确定
协作式电子学习是一种学习者通过使用计算机与同伴群体成员进行互动来学习的环境。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议中的贡献;学习者在协作式电子学习会话中的协作历史以及学习者在其参与的组中的知识水平。就这一发现而言,更有知识的人(MKO)是指在特定任务、过程或概念方面比其他学习者有更好的理解和更高的能力水平的人。他能使别人有效地学习。通过找出MKO,可以形成有效和高效的小组,从而提高学习者在小组中的学习能力,使小组中的同伴最大限度地参与,提高知识水平。在本文中,我们引入了一个模糊模型,利用一个智能推理系统来寻找MKO,并根据一个被称为模糊关联矩阵的度量来提高学习者的学习能力。利用该矩阵可以指导协同电子学习系统找出最优的MKO,从而实现高效的协同电子学习。利用NetLogo进行了仿真研究,以评估所提出策略的性能。仿真结果表明,该策略为协作电子学习环境中同伴间MKO的确定提供了最优解。
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