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Mangaroska, Katerina; Vesin, Boban; Kostakos, Vassilis; Brusilovsky, Peter; Giannakos, Michail N. – IEEE Transactions on Learning Technologies, 2021
With the wide expansion of distributed learning environments the way we learn became more diverse than ever. This poses an opportunity to incorporate different data sources of learning traces that can offer broader insights into learner behavior and the intricacies of the learning process. We argue that combining analytics across different…
Descriptors: Learning Analytics, Electronic Learning, Educational Technology, Instructional Design
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Martinez-Maldonado, Roberto; Echeverria, Vanessa; Mangaroska, Katerina; Shibani, Antonette; Fernandez-Nieto, Gloria; Schulte, Jurgen; Buckingham Shum, Simon – International Journal of Artificial Intelligence in Education, 2022
Teachers' spatial behaviours in the classroom can strongly influence students' engagement, motivation and other behaviours that shape their learning. However, classroom teaching behaviour is ephemeral, and has largely remained opaque to computational analysis. Inspired by the notion of Spatial Pedagogy, this paper presents a system called 'Moodoo'…
Descriptors: Learning Analytics, Teaching Methods, Teacher Behavior, Spatial Ability
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Fernandez-Nieto, Gloria Milena; Echeverria, Vanessa; Shum, Simon Buckingham; Mangaroska, Katerina; Kitto, Kirsty; Palominos, Evelyn; Axisa, Carmen; Martinez-Maldonado, Roberto – IEEE Transactions on Learning Technologies, 2021
There is growing interest in creating learning analytics feedback interfaces that support students directly. While dashboards and other visualizations are proliferating, the evidence is that many fail to provide meaningful insights that help students reflect productively. The contribution of this article is qualitative and quantitative evidence…
Descriptors: Student Attitudes, Story Telling, Accountability, Formative Evaluation