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Showing 1 to 15 of 51 results Save | Export
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Atezaz Ahmad; Jan Schneider; Dai Griffiths; Daniel Biedermann; Daniel Schiffner; Wolfgang Greller; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: During the past decade, the increasingly heterogeneous field of learning analytics has been critiqued for an over-emphasis on data-driven approaches at the expense of paying attention to learning designs. Method and objective: In response to this critique, we investigated the role of learning design in learning analytics through a…
Descriptors: Instructional Design, Learning Analytics, Data Use, Literature Reviews
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Timothy Gallagher; Bert Slof; Marieke van der Schaaf; Michaela Arztmann; Sofia Garcia Fracaro; Liesbeth Kester – Journal of Computer Assisted Learning, 2024
Background: Learning analytics dashboards are increasingly being used to communicate feedback to learners. However, little is known about learner preferences for dashboard designs and how they differ depending on the self-regulated learning (SRL) phases the dashboards are presented (i.e., forethought, performance, and self-reflection phases) and…
Descriptors: Learning Analytics, Experiential Learning, Individualized Instruction, Computer System Design
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Yingbin Zhang; Yafei Ye; Luc Paquette; Yibo Wang; Xiaoyong Hu – Journal of Computer Assisted Learning, 2024
Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…
Descriptors: Learning Analytics, Learning Processes, Test Reliability, Psychometrics
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Wollny, Sebastian; Di Mitri, Daniele; Jivet, Ioana; Muñoz-Merino, Pedro; Scheffel, Maren; Schneider, Jan; Tsai, Yi-Shan; Whitelock-Wainwright, Alexander; Gaševic, Dragan; Drachsler, Hendrik – Journal of Computer Assisted Learning, 2023
Background: Learning Analytics (LA) is an emerging field concerned with measuring, collecting, and analysing data about learners and their contexts to gain insights into learning processes. As the technology of Learning Analytics is evolving, many systems are being implemented. In this context, it is essential to understand stakeholders'…
Descriptors: Foreign Countries, College Students, Learning Analytics, Expectation
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Stoyanov, Slavi; Kirschner, Paul A. – Journal of Computer Assisted Learning, 2023
Background: Learning analytics (LA) collects, analyses, and reports data from the learning environment, to provide evidence of the effects of a particular learning design. Learning design (LD) outlines the conceptual framework for a meaningful interpretation of Learning analytics data. Objectives: The study aims to identify the most relevant…
Descriptors: Learning Analytics, Instructional Design, Data Interpretation, Literature Reviews
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Paraskevi Topali; Ruth Cobos; Unai Agirre-Uribarren; Alejandra Martínez-Monés; Sara Villagrá-Sobrino – Journal of Computer Assisted Learning, 2024
Background: Personalised and timely feedback in massive open online courses (MOOCs) is hindered due to the large scale and diverse needs of learners. Learning analytics (LA) can support scalable interventions, however they often lack pedagogical and contextual grounding. Previous research claimed that a human-centred approach in the design of LA…
Descriptors: Learning Analytics, MOOCs, Feedback (Response), Intervention
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Yuqin Yang; Xueqi Feng; Gaoxia Zhu; Kui Xie – Journal of Computer Assisted Learning, 2024
Background: Undergraduates' collective epistemic agency is critical for their productive collaborative inquiry and knowledge building (KB). However, fostering undergraduates' collective epistemic agency is challenging. Studies have demonstrated the potential of computer-supported collaborative inquiry approaches, such as KB--the focus of this…
Descriptors: Undergraduate Students, Cooperative Learning, Epistemology, Inquiry
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Saleh Alhazbi; Afnan Al-ali; Aliya Tabassum; Abdulla Al-Ali; Ahmed Al-Emadi; Tamer Khattab; Mahmood A. Hasan – Journal of Computer Assisted Learning, 2024
Background: Measuring students' self-regulation skills is essential to understand how they approach their learning tasks in order to identify areas where they might need additional support. Traditionally, self-report questionnaires and think aloud protocols have been used to measure self-regulated learning skills (SRL). However, these methods are…
Descriptors: Learning Analytics, Independent Study, Higher Education, College Students
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Fan, Yizhou; Tan, Yuanru; Rakovic, Mladen; Wang, Yeyu; Cai, Zhiqiang; Shaffer, David Williamson; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: Select and enact appropriate learning tactics that advance learning has been considered a critical set of skills to successfully complete highly flexible online courses, such as Massive open online courses (MOOCs). However, limited by analytic methods that have been used in the past, such as frequency distribution, sequence mining and…
Descriptors: MOOCs, Students, Learning Processes, Learning Strategies
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Topali, Paraskevi; Chounta, Irene-Angelica; Martínez-Monés, Alejandra; Dimitriadis, Yannis – Journal of Computer Assisted Learning, 2023
Background: Providing feedback in massive open online courses (MOOCs) is challenging due to the massiveness and heterogeneity of learners' population. Learning analytics (LA) solutions aim at scaling up feedback interventions and supporting instructors in this endeavour. Paper Objectives: This paper focuses on instructor-led feedback mediated by…
Descriptors: Teaching Methods, Learning Analytics, Feedback (Response), MOOCs
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Vanessa Echeverria; Gloria Fernandez Nieto; Linxuan Zhao; Evelyn Palominos; Namrata Srivastava; Dragan Gaševic; Viktoria Pammer-Schindler; Roberto Martinez-Maldonado – Journal of Computer Assisted Learning, 2025
Background: Dashboards play a prominent role in learning analytics (LA) research. In collaboration activities, dashboards can show traces of team participation. They are often evaluated based on students' perceived satisfaction and engagement with the dashboard. However, there is a notable methodological gap in understanding how these dashboards…
Descriptors: Learning Analytics, Educational Technology, Student Attitudes, Reflection
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Onur Karademir; Daniele Di Mitri; Jan Schneider; Ioana Jivet; Jörn Allmang; Sebastian Gombert; Marcus Kubsch; Knut Neumann; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: Teacher dashboards can help secondary school teachers manage online learning activities and inform instructional decisions by visualising information about class learning. However, when designing teacher dashboards, it is not trivial to choose which information to display, because not all of the vast amount of information retrieved…
Descriptors: Learning Analytics, Secondary School Teachers, Educational Technology, Design
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Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
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Timothy Gallagher; Bert Slof; Marieke van der Schaaf; Ryo Toyoda; Yusra Tehreem; Sofia Garcia Fracaro; Liesbeth Kester – Journal of Computer Assisted Learning, 2024
Background: The potential of learning analytics dashboards in virtual reality simulation-based training environments to influence occupational self-efficacy via self-reflection phase processes in the Chemical industry is still not fully understood. Learning analytics dashboards provide feedback on learner performance and offer points of comparison…
Descriptors: Learning Analytics, Self Efficacy, Reflection, Chemistry
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Ley, Tobias; Tammets, Kairit; Pishtari, Gerti; Chejara, Pankaj; Kasepalu, Reet; Khalil, Mohammad; Saar, Merike; Tuvi, Iiris; Väljataga, Terje; Wasson, Barbara – Journal of Computer Assisted Learning, 2023
Background: With increased use of artificial intelligence in the classroom, there is now a need to better understand the complementarity of intelligent learning technology and teachers to produce effective instruction. Objective: The paper reviews the current research on intelligent learning technology designed to make models of student learning…
Descriptors: Artificial Intelligence, Technology Uses in Education, Learning Analytics, Instructional Effectiveness
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