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Tempelaar, Dirk; Rienties, Bart; Nguyen, Quan – Educational Technology & Society, 2021
Precision education requires two equally important conditions: accurate predictions of academic performance based on early observations of the learning process and the availability of relevant educational intervention options. The field of learning analytics (LA) has made important contributions to the realisation of the first condition,…
Descriptors: Learning Analytics, Individualized Instruction, Blended Learning, Electronic Learning
Nguyen, Quan; Rienties, Bart; Whitelock, Denise – Journal of Learning Analytics, 2020
The use of analytical methods from learning analytics (LA) research combined with visualizations of learning activities using learning design (LD) tools and frameworks has provided important insight into how instructors design for learning. Nonetheless, there are many subtle nuances in instructors' design decisions that might not easily be…
Descriptors: Instructional Design, Online Courses, Distance Education, Electronic Learning
Holmes, Wayne; Nguyen, Quan; Zhang, Jingjing; Mavrikis, Manolis; Rienties, Bart – Distance Education, 2019
There has been a growing interest in how teaching might be informed by "learning design" (LD), with a promising method for investigating LD being offered by the emerging field of "learning analytics" (LA). In this study, we used a novel LA for LD methodology to investigate the implementation of LD in an online distance learning…
Descriptors: Learning Analytics, Instructional Design, Electronic Learning, Distance Education
Nguyen, Quan; Rienties, Bart; Richardson, John T. E. – Assessment & Evaluation in Higher Education, 2020
Although the attainment gap between black and minority ethnic (BME) students and white students has persisted for decades, the potential causes of these disparities are highly debated. The emergence of learning analytics allows researchers to understand how students engage in learning activities based on their digital traces in a naturalistic…
Descriptors: Learning Analytics, Academic Achievement, Achievement Gap, Racial Differences
Tempelaar, Dirk; Rienties, Bart; Nguyen, Quan – International Association for Development of the Information Society, 2019
Learning analytic models are built upon traces students leave in technology-enhanced learning platforms as the digital footprints of their learning processes. Learning analytics uses these traces of learning engagement to predict performance and provide learning feedback to students and teachers when these predictions signal the risk of failing a…
Descriptors: Learner Engagement, Outcomes of Education, Learning Processes, Learning Analytics

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