An exploratory latent class analysis of student expectations towards learning analytics services

IF 6.4 1区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Alexander Whitelock-Wainwright , Yi-Shan Tsai , Hendrik Drachsler , Maren Scheffel , Dragan Gašević
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引用次数: 15

Abstract

For service implementations to be widely adopted, it is necessary for the expectations of the key stakeholders to be considered. Failure to do so may lead to services reflecting ideological gaps, which will inadvertently create dissatisfaction among its users. Learning analytics research has begun to recognise the importance of understanding the student perspective towards the services that could be potentially offered; however, student engagement remains low. Furthermore, there has been no attempt to explore whether students can be segmented into different groups based on their expectations towards learning analytics services. In doing so, it allows for a greater understanding of what is and is not expected from learning analytics services within a sample of students. The current exploratory work addresses this limitation by using the three-step approach to latent class analysis to understand whether student expectations of learning analytics services can clearly be segmented, using self-report data obtained from a sample of students at an Open University in the Netherlands. The findings show that student expectations regarding ethical and privacy elements of a learning analytics service are consistent across all groups; however, those expectations of service features are quite variable. These results are discussed in relation to previous work on student stakeholder perspectives, policy development, and the European General Data Protection Regulation (GDPR).

学生对学习分析服务期望的探索性潜类分析
为了使服务实现得到广泛采用,有必要考虑关键涉众的期望。如果做不到这一点,可能会导致服务反映出意识形态的差距,这将在不经意间引起用户的不满。学习分析研究已经开始认识到理解学生对可能提供的服务的看法的重要性;然而,学生的参与度仍然很低。此外,没有人试图探索是否可以根据学生对学习分析服务的期望将他们划分为不同的群体。在这样做的过程中,它允许更好地理解学生样本中学习分析服务的期望和不期望。目前的探索性工作通过使用三步潜类分析方法来解决这一限制,以了解学生对学习分析服务的期望是否可以清晰地分割,使用从荷兰开放大学的学生样本中获得的自我报告数据。调查结果表明,学生对学习分析服务的道德和隐私元素的期望在所有群体中都是一致的;然而,对服务特性的期望变化很大。这些结果与之前关于学生利益相关者观点、政策制定和欧洲通用数据保护条例(GDPR)的工作有关。
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来源期刊
Internet and Higher Education
Internet and Higher Education EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
19.30
自引率
4.70%
发文量
30
审稿时长
40 days
期刊介绍: The Internet and Higher Education is a quarterly peer-reviewed journal focused on contemporary issues and future trends in online learning, teaching, and administration within post-secondary education. It welcomes contributions from diverse academic disciplines worldwide and provides a platform for theory papers, research studies, critical essays, editorials, reviews, case studies, and social commentary.
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