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Darvishi, Ali; Khosravi, Hassan; Rahimi, Afshin; Sadiq, Shazia; Gasevic, Dragan – IEEE Transactions on Learning Technologies, 2023
Engaging students in creating learning resources has demonstrated pedagogical benefits. However, to effectively utilize a repository of student-generated content (SGC), a selection process is needed to separate high- from low-quality resources as some of the resources created by students can be ineffective, inappropriate, or incorrect. A common…
Descriptors: Student Developed Materials, Educational Assessment, Peer Evaluation, Evaluation Methods
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Alzahrani, Asma Shannan; Tsai, Yi-Shan; Iqbal, Sehrish; Marcos, Pedro Manuel Moreno; Scheffel, Maren; Drachsler, Hendrik; Kloos, Carlos Delgado; Aljohani, Naif; Gasevic, Dragan – Education and Information Technologies, 2023
Potential benefits of learning analytics (LA) for improving students' performance, predicting students' success, and enhancing teaching and learning practice have increasingly been recognized in higher education. However, the adoption of LA in higher education institutions (HEIs) to date remains sporadic and predominantly small in scale due to…
Descriptors: Learning Analytics, Higher Education, Adoption (Ideas), Epistemology
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Saint, John; Whitelock-Wainwright, Alexander; Gasevic, Dragan; Pardo, Abelardo – IEEE Transactions on Learning Technologies, 2020
The recent focus on learning analytics (LA) to analyze temporal dimensions of learning holds the promise of providing insights into latent constructs, such as learning strategy, self-regulated learning (SRL), and metacognition. These methods seek to provide an enriched view of learner behaviors beyond the scope of commonly used correlational or…
Descriptors: Undergraduate Students, Engineering Education, Learning Analytics, Learning Strategies
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Alzahrani, Asma Shannan; Tsai, Yi-Shan; Aljohani, Naif; Whitelock-wainwright, Emma; Gasevic, Dragan – Educational Technology Research and Development, 2023
Learning analytics (LA) has gained increasing attention for its potential to improve different educational aspects (e.g., students' performance and teaching practice). The existing literature identified some factors that are associated with the adoption of LA in higher education, such as stakeholder engagement and transparency in data use. The…
Descriptors: Teacher Attitudes, Trust (Psychology), Learning Analytics, Higher Education
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Tsai, Yi-Shan; Whitelock-Wainwright, Alexander; Gasevic, Dragan – Journal of Learning Analytics, 2021
The adoption of learning analytics (LA) in complex educational systems is woven into sociocultural and technical challenges that have induced distrust in data and difficulties in scaling LA. This paper presents a study that investigated areas of distrust and threats to trustworthy LA through a series of consultations with teaching staff and…
Descriptors: Learning Analytics, Program Implementation, Trust (Psychology), Higher Education
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Matcha, Wannisa; Uzir, Nora'ayu Ahmad; Gasevic, Dragan; Pardo, Abelardo – IEEE Transactions on Learning Technologies, 2020
This paper presents a systematic literature review of learning analytics dashboards (LADs) research that reports empirical findings to assess the impact on learning and teaching. Several previous literature reviews identified self-regulated learning as a primary focus of LADs. However, there has been much less understanding how learning analytics…
Descriptors: Learning Analytics, Computer Interfaces, Educational Research, Learning Strategies
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Gasevic, Dragan; Tsai, Yi-Shan; Dawson, Shane; Pardo, Abelardo – International Journal of Information and Learning Technology, 2019
Purpose: The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach to advancing our understanding of the learning process. This promise motivated the emergence of the field of learning analytics and supported the education sector in moving toward…
Descriptors: Learning Analytics, Adoption (Ideas), Technology Integration, Foreign Countries
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Khosravi, Hassan; Shabaninejad, Shiva; Bakharia, Aneesha; Sadiq, Shazia; Indulska, Marta; Gasevic, Dragan – Journal of Learning Analytics, 2021
Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…
Descriptors: Learning Analytics, Visual Aids, Artificial Intelligence, Information Retrieval
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Matcha, Wannisa; Gasevic, Dragan; Uzir, Nora'ayu Ahmad; Jovanovic, Jelena; Pardo, Abelardo; Lim, Lisa; Maldonado-Mahauad, Jorge; Gentili, Sheridan; Perez-Sanagustin, Mar; Tsai, Yi-Shan – Journal of Learning Analytics, 2020
Generalizability of the value of methods based on learning analytics remains one of the big challenges in the field of learning analytics. One approach to testing generalizability of a method is to apply it consistently in different learning contexts. This study extends a previously published work by examining the generalizability of a learning…
Descriptors: Learning Analytics, Learning Strategies, Instructional Design, Delivery Systems