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Learning Analytics - Door data gestuurd leren
The document discusses learning analytics in the context of technology-enhanced education, emphasizing the collection and analysis of data generated by learners to improve educational outcomes. It covers various metrics used for measuring student engagement, the potential of dashboards, and the importance of self-reflection. Ethical considerations and the impact of data-driven learning are also highlighted.
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Learning Analytics - Door data gestuurd leren
- 1. Learning Analytics Door datagestuurd leren Joris Klerkx Research Expert, PhD. http://hci.cs.kuleuven.be @jkofmsk Erik Duval Professor http://hci.cs.kuleuven.be @erikd Studienamiddag - Learning analytics - HU Brussel - 22 mei 2014 1
- 2. Our team: Human-Computer Interaction ! technologyenhanced learning music research (personal) health 2
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- 6. we are teachingstudents to solve problems we don't know using technologies we don't know 6
- 7. we are shouldbe teaching students to solve problems we don't know using technologies we don't know 7
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- 14. Ex cathedra -exams http://www.flickr.com/photos/wolflawlibrary/2417195782/ 14
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- 16. exams Judge a manby his questions/actions rather than by his answers…Voltaire 16
- 17. Continuous monitoring exams before -during - after 17
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- 19. Collecting traces thatlearners leave behind and using those traces to improve learning http://erikduval.wordpress.com/2012/01/30/learning-analytics-and-educational-data-mining/ Learning analytics 19
- 20. What to measure? Dependson the user 20
- 21. Analytics for Students accessto learning resources posts in discussion fora logins to learning management systems posts of assignments replies to posts votes in lecture response systems time on page in electronic textbook location of device used to access course (and thus proximity to other users) software lines produced contributions to shared documents or wikis etc. Who? ! ! What? ! ! When? 21
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- 24. email, twitter, facebook,web reading, physical movement, location, proximity, food intake, sleeping, drinking, emotion tracking, weather info, attention, brainwaves, … As learning moves online, traces also include… Relevant? 24
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- 27. awareness (self) reflection sense making impact data questions answers behaviorchange or new meaning 27
- 28. How can dataon relevant actions be captured? Inspiration 28
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- 34. Web Analytics -trackers34
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- 38. What else dopeople track? 38
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- 40. Making sense ofthe data Raise awareness & Reflection 40
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- 46. Anscombe’”⁹s quartet ! uX =9.0 uY = 7.5 sigma X = 3.317 sigma Y = 2.03 Y = 3 + 0.5X http://en.wikipedia.org/wiki/Anscombe's_quartet 46
- 47. Educational Data mining DataVisualisation Visual Dashboards <> 47
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- 52. Khaled Bachour, Frederic Kaplan, Pierre Dillenbourg, "An Interac:ve Table for Suppor:ng Par:cipa:on Balance in Face-‐to-‐Face Collabora:ve Learning," IEEE Transac:ons on Learning Technologies, vol. 3, no. 3, pp. 203-‐213, July-‐September, 2010 52
- 53. http://gigaom.com/2013/06/19/new-augmented-reality-glasses-let-teachers-know-when-their-students-are-falling-behind/ T. Zarraonandia, I.Aedo, P. Dıaz, and A. Montero. An augmented lecture feedback system to support learner and teacher communication. British Journal o Technology, 44(4):616–628, 2013. 53
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- 72. J. Santos, S.Charleer, G. Parra, J. Klerkx, E. Duval, and K.Verbert. Evaluating the use of open badges in an open learning environment. In D. Hernandez-Leo,T. Ley, R. Klamma, and A. Harrer, editors, Scaling up Learning for Sustained Impact, volume 8095 of Lecture Notes in Computer Science, pages 314–327. Springer Berlin Heidelberg, 2013.72
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- 85. what can wemeasure & how is it relevant? what is relevant & how can we measure it? 85
- 86. Thank you foryour attention! joris.klerkx@cs.kuleuven.be @jkofmsk 86