协同学习空间中的社会空间学习分析

IF 2.9 Q1 EDUCATION & EDUCATIONAL RESEARCH Journal of Learning Analytics Pub Date : 2023-09-05 DOI:10.18608/jla.2023.7991
Lixiang Yan, Linxuan Zhao, D. Gašević, Xinyu Li, Roberto Martínez-Maldonado
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引用次数: 0

摘要

社会空间学习分析(SSLA)是学习分析研究中的一个新兴领域,旨在从个人的社会和空间数据轨迹中揭示有价值的教育见解。这些痕迹是通过物理学习空间中的传感技术自动捕捉到的,研究通常基于社会建构主义和文化人类学的理论基础。随着其日益增长的经验基础,非系统文献综述是及时的,以便为教育研究人员和从业者提供对新兴作品和SSLA带来的机会的详细总结。本文对2011年至2023年间发表的25篇关于SSLA的同行评审文章进行了系统综述。进行了描述性、网络性和专题性分析,以确定SSLA所带来的引文网络、基本组成部分、机遇和挑战。研究结果表明,SSLA提供了机会:(1)贡献不引人注目和不受监督的研究方法,(2)通过可视化支持教育工作者的课堂编排,(3)用连续可靠的证据支持学习者的反思,(4)发展关于社会和协作学习的新理论,以及(5)为教育利益相关者提供量化数据,以评估不同的学习空间。这些定义可以支持学习分析和教育技术学者和从业者更好地理解和利用SSLA来支持未来的教育研究和实践。
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Socio-spatial Learning Analytics in Co-located Collaborative Learning Spaces:
Socio-spatial learning analytics (SSLA) is an emerging area within learning analytics research that seeks to un-cover valuable educational insights from individuals’ social and spatial data traces. These traces are capturedautomatically through sensing technologies in physical learning spaces, and the research is commonly based onthe theoretical foundations of social constructivism and cultural anthropology. With its growing empirical basis, asystematic literature review is timely in order to provide educational researchers and practitioners with a detailedsummary of the emerging works and the opportunities enabled by SSLA. This paper presents a systematic review of25 peer-reviewed articles on SSLA published between 2011 and 2023. Descriptive, network, and thematic analyseswere conducted to identify the citation networks, essential components, opportunities, and challenges enabled bySSLA. The findings illustrated that SSLA provides the opportunity to (1) contribute unobtrusive and unsupervisedresearch methodologies, (2) support educators’ classroom orchestration through visualizations, (3) support learnerreflection with continuous and reliable evidence, (4) develop novel theories about social and collaborative learning,and (5) empower educational stakeholders with the quantitative data to evaluate different learning spaces. Thesefindings could support learning analytics and educational technology scholars and practitioners to better understandand utilize SSLA to support future educational research and practice.
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来源期刊
Journal of Learning Analytics
Journal of Learning Analytics Social Sciences-Education
CiteScore
7.40
自引率
5.10%
发文量
25
期刊最新文献
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