Learning Analytics Support for Just-in-time Teaching

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Presentation of my PhD thesis status in the annuel meeting of the GAST research group of UC3M

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Learning Analytics Support for Just-in-time Teaching

  1. 1. Learning Analytics support for Just-in-time Teaching Israel Gutiérrez Jornadas GAST - 8 de julio de 2013
  2. 2. Just-in-time Teaching
  3. 3. Awareness
  4. 4. Learning Analytics
  5. 5. Lab sessions photo: berkeleylab at flickr
  6. 6. Research Questions
  7. 7. Research Questions “What are the problems that emerge in highly interactive face-to-face sessions?”
  8. 8. Research Questions “Could a just-in-time teaching system be used to overcome the previous problems, facilitating the teacher management of the session driving it to the intended learning objectives and improving the efficiency of the students allowing them to focus on the assignment?” “What are the problems that emerge in highly interactive face-to-face sessions?”
  9. 9. Methodology Design-based research
  10. 10. Methodology Design-based research • Based on theory but pragmatic
  11. 11. Methodology Design-based research • Based on theory but pragmatic • Real-world setting
  12. 12. Methodology Design-based research • Based on theory but pragmatic • Real-world setting • Iterative process
  13. 13. Methodology Design-based research • Based on theory but pragmatic • Real-world setting • Iterative process • Mixed methods
  14. 14. Methodology Design-based research • Based on theory but pragmatic • Real-world setting • Iterative process • Mixed methods • Research agenda updated with findings
  15. 15. Problems in lab session Literature Experiments Experts
  16. 16. Literature Lantern (Alavi & Dillenbourg, 2009) PLITAZ (Dong & Hwang, 2012) Problem Source Stakeholder Demand an answer Alavi09 Students Wait longer Alavi09 Students Fails to notice requests Alavi09 Teachers Heavy workload Dong12 Teachers Isolation Dong12 Students Limited awareness Dong12 Teachers Simultaneous requests Dong12 Teachers
  17. 17. AMM11 (Gutiérrez Rojas, Crespo García, & Delgado Kloos, 11) AS11 (Gutiérrez Rojas & Crespo García, 12) AMM12 (Gutiérrez Rojas, Crespo García, & Delgado Kloos, 12) Problem Source Stakeholder Methodology increases workload AMM11 Teachers Huge number of requests AS11 Teachers Attention to personalized feedback AS11 Students Ask without thinking AS11 Students Shorten explanation if overwhelmed AS11 Teachers Perceive not enough teachers AS11 Students Attention order unfairness AS11 Teachers Devote time monitoring the teacher AS11 Students Not aware of time AS11 Teachers Not like writing questions AMM12 Students Not relevant not current info AMM12 Teachers Interface not straight-forward AMM12 Teachers Experiments
  18. 18. OUNL UC3M Experts KU Leuven RWTH Aachen Problem Source Stakeholder Not support for project-based learning EXP Teachers Not support for exchange questions EXP Students Not support for exchange progress EXP Students Not collecting evidences for summative EXP Teachers
  19. 19. Requirements Requirement Stakeholder Provide time management mechanisms Teachers Provide info about students progression Teachers Provide info about students requests Teachers Straightforward UI Teachers Responsive UI Teachers Store and process students records Teachers Support different teaching methods Teachers Provide info to students for self-awareness Students As much personalized feedback as possible Students Enable students to focus on the assignment Students Share and rate questions and answers Students Share progression Students
  20. 20. in-Class Live Analytics for Assessment and Orchestration http://www.class-on.org
  21. 21. Student UI
  22. 22. Student UI
  23. 23. Teacher UI
  24. 24. Teacher UI
  25. 25. Analytics
  26. 26. Video
  27. 27. Authentic experiments AMM12 AS12 AMM13 Date March-May 2012 November 2012 February-May 2013 Duration 18 sessions 6 sessions 10 sessions* Teachers 4 3 1 Students 70 121 30 Group settings Dyads Dyads Dyads
  28. 28. Results Teachers interviews Students surveys Collected traces
  29. 29. Results Teachers interviews Students surveys Collected traces
  30. 30. Results Teachers interviews Students surveys Collected traces Requirements
  31. 31. Lessons Learned
  32. 32. Lessons Learned
  33. 33. Lessons Learned
  34. 34. Lessons Learned
  35. 35. Lessons Learned
  36. 36. Contributions
  37. 37. Contributions
  38. 38. Contributions
  39. 39. Contributions
  40. 40. Related Publications Gutiérrez Rojas, I., Crespo García, R. M., & Delgado Kloos, C. (2012). Enhancing orchestration of lab sessions by means of awareness mechanisms. EC-TEL 2012: 21st century learning for 21st century skills: 7th European Conference of Technology Enhanced Learning, 18-21 September 2012, Saarbrücken (Germany) (Vol. 7563, pp. 113–125). Gutiérrez Rojas, I., & Crespo García, R. M. (2012). Towards efficient provision of feedback in lab sessions. International Conference on Advanced Learning Technologies (ICALT) (Vol. 1). Rome. Gutiérrez Rojas, I., Crespo García, R. M., & Delgado Kloos, C. (2011). Orchestration and feedback in lab sessions: improvements in quick feedback provision. Towards Ubiquitous Learning. 6th European Conference ofTechnology Enhanced Learning, EC-TEL 2011 Palermo, Italy, September 20-23, 2011 Proceedings. LNCS, 6964. doi:10.1007/978-3-642-23985-4
  41. 41. Future Work
  42. 42. Future Work
  43. 43. http://www.moocrank.com
  44. 44. Thank you very much!

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