Big Five Personality Traits and Academic Learning in Wiki-Mediated Collaborative Activities

IF 3.3 Q1 EDUCATION & EDUCATIONAL RESEARCH

International Journal of Distance Education Technologies Pub Date : 2018-07-01 DOI:10.4018/IJDET.2018070105

Panagiota Altanopoulou, Nikolaos Tselios

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引用次数: 5

Abstract

The influence of students' non-cognitive characteristics on their learning performance constitutes a significant but rather unexplored topic. The goal of the research presented in this article, is to examine the relation between the students' personality characteristics (as measured using the Big Five Personality Test) and their learning outcome in the context of four framed wiki-based learning activities. 368 university students participated in the studies. Meta-analysis of results indicates that learning gain was significant negatively correlated with one of the five basic personality dimensions, namely Extraversion. Also, agreeableness was significant positively correlated with learning gain. Moreover, conscientiousness and emotionally stability were significant positively correlated with logged wiki edits that students made in this activity. It is argued, and discussed, that results from such studies can lead to useful conclusions regarding the design of appropriate activities and the creation of more effective collaborative teams in the context of wiki-based web activities.

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维基媒介协作活动中的五大人格特征与学术学习

学生的非认知特征对学习成绩的影响是一个重要但尚未被探索的话题。本文提出的研究目的是在四个框架的基于维基的学习活动的背景下，检验学生的人格特征(使用大五人格测试测量)与他们的学习成果之间的关系。368名大学生参与了研究。元分析结果表明，学习收益与外向性这五个基本人格维度之一呈显著负相关。此外，亲和性与学习收益显著正相关。此外，严谨性和情绪稳定性与学生在该活动中所做的维基编辑记录显著正相关。这是争论和讨论，从这些研究的结果可以得出有用的结论，关于设计适当的活动和创建更有效的协作团队在基于维基的网络活动的背景下。

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

International Journal of Distance Education Technologies EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

9.10

自引率

0.00%

发文量

期刊介绍： Discussions of computational methods, algorithms, implemented prototype systems, and applications of open and distance learning are the focuses of this publication. Practical experiences and surveys of using distance learning systems are also welcome. Distance education technologies published in IJDET will be divided into three categories, communication technologies, intelligent technologies.