An Automatic Group Formation Method to Promote Student Interaction in Distance Education Courses

M. Ullmann, D. Ferreira, C. Camilo-Junior
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引用次数: 3

Abstract

This article proposes an automatic group formation method applying the particle swarm optimization (PSO) algorithm to boost the quality of students' online interactions. The groups were heterogeneous regarding their levels of knowledge and their interests, and three different leadership roles were distributed among group members. A case study with 66 undergraduate students was performed. Discourse analysis was applied using two coding schemes to measure the critical thinking apparent in the students' online discussions and evaluate the socio-cognitive aspects of group interactions. The results provided evidence that groups of undergraduate students formed by the proposed method achieved better scores in most categories analyzed when compared to the randomly formed groups.
远程教育课程中促进学生互动的自动分组方法
本文提出了一种应用粒子群优化(PSO)算法的自动分组方法,以提高学生在线互动的质量。这些小组在知识水平和兴趣方面是异质的,并且在小组成员中分配了三种不同的领导角色。对66名大学生进行了个案研究。话语分析采用两种编码方案来衡量学生在线讨论中明显的批判性思维,并评估群体互动的社会认知方面。结果证明,与随机组成的群体相比,采用该方法组成的本科生群体在大多数类别分析中取得了更好的成绩。
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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