New Pub: Connecting the dots – A literature review on learning analytics indicators from a learning design perspective

New Pub: Connecting the dots – A literature review on learning analytics indicators from a learning design perspective

Empirical Study, Higher Education, Journal, Learning Analytics, Learning Design, Lifelong Learning, Literature review, Open access, Publication, Self-Regulation, Special Issue, Target group
[caption id="attachment_4329" align="alignright" width="450"] Occurrences of the most commonly used learning analytic indicators over the past 10 years[/caption] 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 systematic literature review. 161 learning analytics (LA) articles were examined to identify indicators that were based on learning design events and their associated metrics. Through this research, we address two objectives. First, to achieve a better alignment between learning design and learning analytics by proposing a reference framework, where we present possible connections between learning analytics and learning design. Second, to present how…
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Presentation about detecting off-task behavior during learning at the GEBF 2022

Presentation about detecting off-task behavior during learning at the GEBF 2022

Conference, Event, Higher Education, Learning Analytics, Research topic, Self-Regulation
On 09.03.2022, Daniel Biedermann gave a presentation on the topic of recognizing off-task behavior as part of the GEBF conference. The talk was part of the symposium on "Self-Regulation in Learning in Digital Environments: From Problems to Solutions". The talk presented the endeavor of using process data within a learning environment to detect and predict off-task behavior. Special attention was given to the challenges that arise when detecting off-task behavior. The same observed activity may be considered off-task in one case, but relevant to learning in another. Making this distinction requires a precise grasp of the context in which the observed behavior takes place. Aspects such as what phase of learning was someone in when another web page was accessed? Had the learning material already been processed? Or was the…
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