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Stephanie J. Blackmon; Robert L. Moore – Journal of Computing in Higher Education, 2024
As learning analytics use grows across U.S. colleges and universities, so does the need to discuss the plans, purposes, and paths for the data collected via learning analytics. More specifically, students, faculty, and others who are impacted by learning analytics use should have more information about their campus' learning analytics practices…
Descriptors: Learning Analytics, Networks, Models, Ethics
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Liyanachchi Mahesha Harshani De Silva; María Jesús Rodríguez-Triana; Irene-Angelica Chounta; Gerti Pishtari – Journal of Computing in Higher Education, 2025
With technological advances, institutional stakeholders are considering evidence-based developments such as Curriculum Analytics (CA) to reflect on curriculum and its impact on student learning, dropouts, program quality, and overall educational effectiveness. However, little is known about the CA state of the art in Higher Education Institutions…
Descriptors: Learning Analytics, Curriculum Evaluation, Higher Education, Stakeholders
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Ji Hyun Yu – Journal of Computing in Higher Education, 2025
This study investigates the role of learning analytics in enhancing the learning experience within Massive Open Online Courses (MOOCs) through a two-phase design-based research approach, focusing on a Social Work MOOC. Initial engagement analysis revealed strong interactions with course content, especially with introductory elements and reflection…
Descriptors: Learning Analytics, Instructional Design, MOOCs, Social Work
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Paul Prinsloo; Mohammad Khalil; Sharon Slade – Journal of Computing in Higher Education, 2024
Central to the institutionalization of learning analytics is the need to understand and improve student learning. Frameworks guiding the implementation of learning analytics flow from and perpetuate specific understandings of learning. Crucially, they also provide insights into how learning analytics acknowledges and positions itself as entangled…
Descriptors: Learning Analytics, Data, Ecology, Models
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Mohammad Khalil; Sharon Slade; Paul Prinsloo – Journal of Computing in Higher Education, 2024
This article maps considerations of inclusiveness and support for students with disabilities by reviewing articles within the field of learning analytics. The study involved a PRISMA-informed systematic review of two popular digital libraries, namely Clarivate's Web of Science, and Elsevier's Scopus for peer-reviewed journal articles and…
Descriptors: Learning Analytics, Journal Articles, Conference Papers, Inclusion
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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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Yuqin Yang; Yewen Chen; Xueqi Feng; Daner Sun; Shiyan Pang – Journal of Computing in Higher Education, 2024
Helping students gradually develop collective knowledge is critical but generally faces great challenges. Employing a quasi-experimental design, this study investigated the impacts and mechanisms of analytics-supported reflective assessment on the collective knowledge advancement of undergraduates. The experimental group (n = 55) engaged in…
Descriptors: Undergraduate Students, Learning Processes, Learning Analytics, Learner Engagement
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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