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Lili Aunimo; Janne Kauttonen; Marko Vahtola; Salla Huttunen – Journal of Computing in Higher Education, 2025
Institutions of higher education possess large amounts of learning-related data in their student registers and learning management systems (LMS). This data can be mined to gain insights into study paths, study styles and possible bottlenecks on the study paths. In this study, we focused on creating a predictive model for study completion time…
Descriptors: Data Collection, Learning Management Systems, Study Habits, Time on Task
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Jeongwon Lee; Dongho Kim – Journal of Computing in Higher Education, 2025
Although learning analytics dashboards (LADs) are being recognized as tools that can enhance engagement--a crucial factor for the success of asynchronous online higher education--their impact may be limited without a solid theoretical basis for motivation. Furthermore, the processes through which students make decisions using dashboards and engage…
Descriptors: Self Determination, Learning Analytics, Educational Technology, Learner Engagement
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Jones, Kyle M. L.; VanScoy, Amy; Bright, Kawanna; Harding, Alison; Vedak, Sanika – Journal of Computing in Higher Education, 2022
Learning analytics tools are becoming commonplace in educational technologies, but extant student privacy issues remain largely unresolved. It is unknown whether faculty care about student privacy and see privacy as valuable for learning. The research herein addresses findings from a survey of over 500 full-time higher education instructors. In…
Descriptors: College Faculty, Teacher Attitudes, College Students, Privacy