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Mahmoud, Mai; Dafoulas, Georgios; Abd ElAziz, Rasha; Saleeb, Noha – International Journal of Information and Learning Technology, 2021
Purpose: The objective of this paper is to present a comprehensive review of the literature on learning analytics (LA) stakeholders' expectations to reveal the status of ongoing research in this area and to highlight gaps in research. Design/methodology/approach: Conducting a literature review is a well-known method to establish knowledge and…
Descriptors: Learning Analytics, Stakeholders, Expectation, Higher Education
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Emmanuel Amos; Harry Barton Essel; George Kwame Fobiri; Akwasi Adomako Boakye; Yaw Boateng Ampadu – SAGE Open, 2025
The increasing number of students in higher education has led to the formation of large class teaching and learning environments, which is a threat to quality education. The Department of Fashion Design and Textiles Studies of Kumasi Technical University is one such department that is facing this challenge. Computer-based technology has…
Descriptors: Foreign Countries, College Students, Design, Computer Uses in Education
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Tsai, Yi-Shan; Perrotta, Carlo; Gaševic, Dragan – Assessment & Evaluation in Higher Education, 2020
The emergence of personalised data technologies such as learning analytics is framed as a solution to manage the needs of higher education student populations that are growing ever more diverse and larger in size. However, the current approach to learning analytics presents tensions between increasing student agency in making learning-related…
Descriptors: Student Empowerment, Equal Education, Learning Analytics, Accountability
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Van Wart, Sarah; Lanouette, Kathryn; Parikh, Tapan S. – Journal of the Learning Sciences, 2020
Data increasingly mediates how we understand the world. As such, there is growing interest in designing initiatives to help young people learn about data--not only the techno-mathematical skills necessary to work with data, but also the dispositions needed to participate in data-centric ways of knowing and doing. In this article, we argue that as…
Descriptors: Data, Social Problems, Data Collection, Data Use