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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
Wong, Billy Tak-ming; Li, Kam Cheong; Cheung, Simon K. S. – Journal of Computing in Higher Education, 2023
This paper presents an analysis of learning analytics practices which aimed to achieve personalised learning. It addresses the need for a systematic analysis of the increasing amount of practices of learning analytics which are targeted at personalised learning. The paper summarises and highlights the characteristics and trends in relevant…
Descriptors: Learning Analytics, Individualized Instruction, Context Effect, Stakeholders
Muljana, Pauline Salim; Luo, Tian – Journal of Computing in Higher Education, 2021
Studies in learning analytics (LA) have garnered positive findings on learning improvement and advantages for informing course design. However, little is known about instructional designers' perception and their current state of LA-related adoption. This qualitative study explores the perception of instructional designers in higher education…
Descriptors: Learning Analytics, Instructional Design, Higher Education, Attitudes
Li, Xu; Ouyang, Fan; Chen, WenZhi – Journal of Computing in Higher Education, 2022
Group formation is a critical factor which influences collaborative processes and performances in computer-supported collaborative learning (CSCL). Automatic grouping has been widely used to generate groups with heterogeneous attributes and to maximize the diversity of students' characteristics within a group. But there are two dominant challenges…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Group Dynamics, Grouping (Instructional Purposes)
Klein, Carrie; Lester, Jaime; Rangwala, Huzefa; Johri, Aditya – Journal of Computing in Higher Education, 2019
Learning analytics (LA) tools promise to improve student learning and retention. However, adoption and use of LA tools in higher education is often uneven. In this case study, part of a larger exploratory research project, we interviewed and observed 32 faculty and advisors at a public research university to understand the technological incentives…
Descriptors: Learning Analytics, Barriers, Incentives, Adoption (Ideas)

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