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Learning analytics dashboards
The seminar on learning analytics dashboards discusses the integration of visual tools to enhance student awareness and self-reflection through data tracking and analysis. Key research questions focus on user actions, data capture methods, and the evaluation of dashboard applications' impact on behavior. The document highlights various research contributions and tools in the field, aiming to advance evidence-based education practices.
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Learning analytics dashboards
- 1. Learning analytics dashboards Seminar Opportunities and Challenges of Learning with Technologies: Evidence-based Education Brussels, 12 November 2014 Katrien Verbert HCI research group – KU Leuven @katrien_v
- 2. Human-Computer Interaction Awareness sense-making Erik Duval Joris Klerkx Katrien Verbert Computer Graphics Phil Dutré Language Intelligence Information Retrieval Sien Moens “Flexible Interaction between people and information” http://hci.cs.kuleuven.be/
- 3. Sabermetrics objective evidence measure in-game activity
- 5. Learning analytics “Collectingtraces that learners leave behind and using those traces to improve learning.” Duval, E., Verbert, K. (2012). Learning analytics. E-Learning and Education, 1(8).
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- 12. Student Activity Meter(SAM) Govaerts, S., Verbert, K., Duval, E., Pardo, A. (2012, May). The student activity meter for awareness and self-reflection. In CHI'12 Extended Abstracts on Human Factors in Computing Systems (pp. 869-884). ACM.
- 14. ariadne.cs.kuleuven.be/LARAe/ LARAe ARTEL2014 . Graz, Austria
- 16. ! Derick Leony,Pedro J. Munoz-Merino, Carlos Delgado Kloos, Katrien Verbert. Evaluating Affectvis, a learning dashboard for emotions in projects. Submitted to Computers Education, Nov. 2014.
- 17. Research questions •RQ1: What are relevant user actions? • RQ2: How can data on relevant actions be captured? • RQ3: How is awareness self-reflection enabled for different kinds of users through appropriate devices? • RQ4: How can learning analytics dashboard applications be evaluated? How can the impact of these visualizations on user behavior be measured?
- 20. RQ2: How candata on relevant actions be captured?
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- 28. RQ3: How isawareness self-reflection enabled for different kinds of users through appropriate devices?
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- 31. Bachour, K., Kaplan,F., Dillenbourg, P. (2010). An interactive table for supporting participation balance in face-to-face collaborative learning. Learning Technologies, IEEE Transactions on, 3(3), 203-213.
- 32. 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 of Educational Technology, 44(4):616–628, 2013.
- 34. RQ4: How canlearning analytics dashboard applications be evaluated?
- 35. Verbert, K., Duval,E., Klerkx, J., Govaerts, S., Santos, J. L. (2013). Learning analytics dashboard applications. American Behavioral Scientist
- 36. demographics tool deployed tracking tools data tracked #cgiar 19 teachers SAM LMS resource use, communication, time spent #lak11 12 participants SAM LMS resource use, communication, time spent #uc3m 11 teachers SAM Virtual machine resource use, programming errors, debugging, time spent; artefacts produced #thesis11 13 students Step-Up! Twitter, Tinyarm, blogs resource use, artefacts produced #thesis11- sup 5 teachers Step-Up! Twitter, Tinyarm, blogs resource use, artefacts produced #peno3 10 students Step-Up! Toggl Time spent, resource and application use #chikul 30 students Step-Up! Toggl, twitter, blogs twitter, blogs, time spent, resource use
- 37. Verbert, K., Govaerts,S., Duval, E., Santos, J. L., Van Assche, F., Parra, G., Klerkx, J. (2013). Learning dashboards: an overview and future research opportunities. Personal and Ubiquitous Computing, 1-16.
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- 39. Thank you! Questions? [email protected] twitter: @katrien_v