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学习社区中感恩信息的网络分析

Network analysis of gratitude messages in the learning community.

作者信息

Yoshida Masami

机构信息

The Faculty of Education, Chiba University, 1-33 Yayoi, Inage, Chiba, 263-8522 Japan.

出版信息

Int J Educ Technol High Educ. 2022;19(1):47. doi: 10.1186/s41239-022-00352-8. Epub 2022 Sep 7.

Abstract

In pedagogical practice, gratitude is recognised not as an emotion, but as an approach to learning. This study introduced gratitude messages into the academic online communication of university students and specifically examined the community in which students shared their messages with gratitude. This study examined the tendency of message connections and how gratitude messages prompted replies. To elucidate their connections, exponential random graph models (ERGMs) were used. A post-event questionnaire to evaluate gratitude experiences was also administered. Results revealed that 77.3% of the 172 connected messages from 123 students involved gratitude. When the post-event questionnaire results were examined using an ERGM, the score effects on increasing message connections were found not to be significant. The most prominent indication was a higher level of significant propensities to make mutual connections. The homophily of the message content was found to have a significant propensity to increase connections. The ERGM results and a review of messages revealed that students expressed gratitude for being both benefactors and beneficiaries of gratitude messages, which confirmed their prosocial behaviour.

摘要

在教学实践中,感恩并非被视为一种情感,而是一种学习方式。本研究将感恩信息引入大学生的学术在线交流中,并特别考察了学生分享感恩信息的群体。本研究考察了信息连接的倾向以及感恩信息如何促使他人回复。为了阐明它们之间的联系,使用了指数随机图模型(ERGM)。还进行了一项事后问卷调查,以评估感恩体验。结果显示,123名学生的172条相互关联的信息中,77.3%涉及感恩。当使用ERGM对事后问卷调查结果进行分析时,发现分数对增加信息连接的影响并不显著。最显著的迹象是相互连接的倾向水平更高。信息内容的同质性被发现有显著的增加连接的倾向。ERGM结果和对信息的审查表明,学生们对自己既是感恩信息的施惠者又是受益者表达了感激之情,这证实了他们的亲社会行为。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0aaa/9449265/95da5249b8ad/41239_2022_352_Fig1_HTML.jpg

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