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Chen Zhan; Srecko Joksimovic; Djazia Ladjal; Thierry Rakotoarivelo; Ruth Marshall; Abelardo Pardo – IEEE Transactions on Learning Technologies, 2024
Data are fundamental to Learning Analytics (LA) research and practice. However, the ethical use of data, particularly in terms of respecting learners' privacy rights, is a potential barrier that could hinder the widespread adoption of LA in the education industry. Despite the policies and guidelines of privacy protection being available worldwide,…
Descriptors: Privacy, Learning Analytics, Ethics, Data Use
Liu, Kai; Tatinati, Sivanagaraja; Khong, Andy W. H. – IEEE Transactions on Learning Technologies, 2020
Activity-centric data gather feedback on students' learning to enhance learning effectiveness. The heterogeneity and multigranularity of such data require existing data models to perform complex on-the-fly computation when responding to queries of specific granularity. This, in turn, results in latency. In addition, existing data models are…
Descriptors: Context Effect, Models, Learning Analytics, Data Use
Moonen-van Loon, Joyce M. W.; Govaerts, Marjan; Donkers, Jeroen; van Rosmalen, Peter – IEEE Transactions on Learning Technologies, 2022
Self-directed learning is generally considered a key competence in higher education. To enable self-directed learning, assessment practices increasingly embrace assessment for learning rather than the assessment of learning, shifting the focus from grades and scores to provision of rich, narrative, and personalized feedback. Students are expected…
Descriptors: Competency Based Education, Portfolios (Background Materials), Feedback (Response), Independent Study

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