网络分析揭示学生角色的社会认知话语

Maverick Andre Dionisio Ferreira, R. F. Mello, Vitomir Kovanovíc, André C. A. Nascimento, R. Lins, D. Gašević
{"title":"网络分析揭示学生角色的社会认知话语","authors":"Maverick Andre Dionisio Ferreira, R. F. Mello, Vitomir Kovanovíc, André C. A. Nascimento, R. Lins, D. Gašević","doi":"10.1145/3506860.3506978","DOIUrl":null,"url":null,"abstract":"Roles that learners assume during online discussions are an important aspect of educational experience. The roles can be assigned to learners and/or can spontaneously emerge through student-student interaction. While existing research proposed several approaches for analytics of emerging roles, there is limited research in analytic methods that can i) automatically detect emerging roles that can be interpreted in terms of higher-order constructs of collaboration; ii) analyse the extent to which students complied to scripted roles and how emerging roles compare to scripted ones; and iii) track progression of roles in social knowledge progression over time. To address these gaps in the literature, this paper propose a network-analytic approach that combines techniques of cluster analysis and epistemic network analysis. The method was validated in an empirical study discovered emerging roles that were found meaningful in terms of social and cognitive dimensions of the well-known model of communities of inquiry. The study also revealed similarities and differences between emerging and script roles played by learners and identified different progression trajectories in social knowledge construction between emerging and scripted roles. The proposed analytic approach and the study results have implications that can inform teaching practice and development techniques for collaboration analytics.","PeriodicalId":185465,"journal":{"name":"LAK22: 12th International Learning Analytics and Knowledge Conference","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"NASC: Network analytics to uncover socio-cognitive discourse of student roles\",\"authors\":\"Maverick Andre Dionisio Ferreira, R. F. Mello, Vitomir Kovanovíc, André C. A. Nascimento, R. Lins, D. Gašević\",\"doi\":\"10.1145/3506860.3506978\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Roles that learners assume during online discussions are an important aspect of educational experience. The roles can be assigned to learners and/or can spontaneously emerge through student-student interaction. While existing research proposed several approaches for analytics of emerging roles, there is limited research in analytic methods that can i) automatically detect emerging roles that can be interpreted in terms of higher-order constructs of collaboration; ii) analyse the extent to which students complied to scripted roles and how emerging roles compare to scripted ones; and iii) track progression of roles in social knowledge progression over time. To address these gaps in the literature, this paper propose a network-analytic approach that combines techniques of cluster analysis and epistemic network analysis. The method was validated in an empirical study discovered emerging roles that were found meaningful in terms of social and cognitive dimensions of the well-known model of communities of inquiry. The study also revealed similarities and differences between emerging and script roles played by learners and identified different progression trajectories in social knowledge construction between emerging and scripted roles. The proposed analytic approach and the study results have implications that can inform teaching practice and development techniques for collaboration analytics.\",\"PeriodicalId\":185465,\"journal\":{\"name\":\"LAK22: 12th International Learning Analytics and Knowledge Conference\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"LAK22: 12th International Learning Analytics and Knowledge Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3506860.3506978\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"LAK22: 12th International Learning Analytics and Knowledge Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3506860.3506978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

学习者在在线讨论中扮演的角色是教育体验的一个重要方面。角色可以分配给学习者,也可以通过学生与学生的互动自发地出现。虽然现有的研究提出了几种分析新兴角色的方法,但在分析方法方面的研究有限,这些分析方法可以i)自动检测可以根据协作的高阶结构解释的新兴角色;Ii)分析学生遵守既定角色的程度,以及新兴角色与既定角色的比较;iii)跟踪社会知识发展过程中角色的发展。为了解决文献中的这些空白,本文提出了一种结合聚类分析和认知网络分析技术的网络分析方法。该方法在一项实证研究中得到了验证,该研究发现,在众所周知的探究社区模型的社会和认知维度方面,新兴角色被发现是有意义的。研究还揭示了学习者所扮演的新兴角色与脚本角色之间的异同,并确定了新兴角色与脚本角色在社会知识建构方面的不同发展轨迹。所提出的分析方法和研究结果对协作分析的教学实践和开发技术具有启示意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
NASC: Network analytics to uncover socio-cognitive discourse of student roles
Roles that learners assume during online discussions are an important aspect of educational experience. The roles can be assigned to learners and/or can spontaneously emerge through student-student interaction. While existing research proposed several approaches for analytics of emerging roles, there is limited research in analytic methods that can i) automatically detect emerging roles that can be interpreted in terms of higher-order constructs of collaboration; ii) analyse the extent to which students complied to scripted roles and how emerging roles compare to scripted ones; and iii) track progression of roles in social knowledge progression over time. To address these gaps in the literature, this paper propose a network-analytic approach that combines techniques of cluster analysis and epistemic network analysis. The method was validated in an empirical study discovered emerging roles that were found meaningful in terms of social and cognitive dimensions of the well-known model of communities of inquiry. The study also revealed similarities and differences between emerging and script roles played by learners and identified different progression trajectories in social knowledge construction between emerging and scripted roles. The proposed analytic approach and the study results have implications that can inform teaching practice and development techniques for collaboration analytics.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信