Application of learning analytics to case studies

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Poh-Sun Goh

1st draft on 19 October 2017 @ 0709am

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Blog posts
(diﬀerent content on each Post,

and

diﬀerent learning pathways

on each Post)
Analytics
(daily, extended session,

Individual

And

Cohort)
Modify Content
(create more, edit less, curate)
Instagram
(visual index of blog posts)
Application of Learning Analytics to Case Studies
Poh-Sun Goh

1st draft on 19 October 2017 @ 0709am

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Destaque

Keynote delivered by George Siemens (@gsiemens), Dragan Gasevic (@dgasevic), and Ryan Baker (@BakerEDMLab) at the 8th International Educational Data Mining Conference (EDM 2015) in Madrid, Spain on June 27, 2015 Educational data mining and learning analytics have to date largely focused on specific research questions that provide insight into granular interactions. These insights have bee abstracted to include the development of predictive models, intelligent tutors, and adaptive learning. While there are several domains where holistic or systems models have provided additional explanatory power, work around learning has not created holistic models with the level of concreteness or richness required. The need for both granular and integrated high-level view of learning is further influenced by distributed, life long, multi-spaced learning that today defines education. Drawing on social and knowledge graph theory, we propose the development of a Personal Learning Graph (PLeG) - an open and learner-owned profile that addresses cognitive, affective, and related elements that reflect what a learner knows, is able to do, and processes through which she learns best. This talk will introduce PLeG, detail required technical infrastructure, and articulate how it would interact with established learning software.

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