O slideshow foi denunciado.
Utilizamos seu perfil e dados de atividades no LinkedIn para personalizar e exibir anúncios mais relevantes. Altere suas preferências de anúncios quando desejar.

Learning analytics are more than a technology

The slides used in my ELearn 2015 keynote

Audiolivros relacionados

Gratuito durante 30 dias do Scribd

Ver tudo

Learning analytics are more than a technology

  1. 1. Learning analytics are more than a technology Dragan Gašević @dgasevic October 20, 2015 ELearn 2015, Kona, HI
  2. 2. Educational Landscape Today “Non-traditional” students Large classrooms Long time to complete degrees Long waiting lists
  3. 3. Learning at scale
  4. 4. Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 201319030.
  5. 5. Feedback loops between students and instructors are missing/weak!
  6. 6. LEARNING ANALYTICS
  7. 7. Learning environment Educators Learners Student Information Systems
  8. 8. Blogs Videos/slides Mobile Search Educators Learners Networks Student Information Systems Learning environment
  9. 9. Blogs Mobile Search Networks Educators Learners Student Information Systems Learning environment Videos/slides
  10. 10. Learning Analytics – What? Measurement, collection, analysis, and reporting of data about learners and their contexts
  11. 11. Learning Analytics – Why? Understanding and optimising learning and the environments in which learning occurs
  12. 12. CASE STUDIES
  13. 13. Student retention 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% Year 1 Year 2 Year 3 Year 4 Course Signals No Course Signals Arnold, K. E., & Pistilli, M. D. (2012, April). Course Signals at Purdue: Using learning analytics to increase student success. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (pp. 267-270).
  14. 14. Tanes, Z., Arnold, K. E., King, A. S., & Remnet, M. A. (2011). Using Signals for appropriate feedback: Perceptions and practices. Computers & Education, 57(4), 2414-2422. Can teaching be improved?
  15. 15. Wright, M. C., McKay, T., Hershock, C., Miller, K., & Tritz, J. (2014). Better Than Expected: Using Learning Analytics to Promote Student Success in Gateway Science. Change: The Magazine of Higher Learning, 46(1), 28-34.
  16. 16. INSTITUTIONAL ADOPTION: CURRENT STATE
  17. 17. Very few institution-wide examples of adoption
  18. 18. Sophistication model Siemens, G., Dawson, S., & Lynch, G. (2014). Improving the Quality and Productivity of the Higher Education Sector - Policy and Strategy for Systems-Level Deployment of Learning Analytics. Canberra, Australia: Office of Learning and Teaching, Australian Government. Retrieved from http://solaresearch.org/Policy_Strategy_Analytics.pdf
  19. 19. Sophistication model Siemens, G., Dawson, S., & Lynch, G. (2014). Improving the Quality and Productivity of the Higher Education Sector - Policy and Strategy for Systems-Level Deployment of Learning Analytics. Canberra, Australia: Office of Learning and Teaching, Australian Government. Retrieved from http://solaresearch.org/Policy_Strategy_Analytics.pdf
  20. 20. Interest in analytics is high, but many institutions had yet to make progress beyond basic reporting Bichsel, J. (2012). Analytics in higher education: Benefits, barriers, progress, and recommendations. EDUCAUSE Center for Applied Research.
  21. 21. What’s necessary to move forward?
  22. 22. DIRECTIONS
  23. 23. Data – Model – Transform Barton, D., & Court, D. (Oct 2012). Making Advanced Analytics Work for You. Harvard Business Review, 79-83, https://hbr.org/2012/10/making-advanced-analytics-work-for-you/ar/1
  24. 24. Data – Model – Transform Creative data sourcing Barton, D., & Court, D. (Oct 2012). Making Advanced Analytics Work for You. Harvard Business Review, 79-83, https://hbr.org/2012/10/making-advanced-analytics-work-for-you/ar/1
  25. 25. Social networks are everywhere Gašević, D., Zouaq, A., Jenzen, R. (2013). ‘Choose your Classmates, your GPA is at Stake!’ The Association of Cross- Class Social Ties and Academic Performance. American Behavioral Scientist, 57(10), 1459–1478.
  26. 26. Data – Model – Transform Creative data sourcing Necessary IT support Barton, D., & Court, D. (Oct 2012). Making Advanced Analytics Work for You. Harvard Business Review, 79-83, https://hbr.org/2012/10/making-advanced-analytics-work-for-you/ar/1
  27. 27. Awareness of limitations and challenging assumptions Kovanović, V., Gašević, D., Dawson, S., Joksimović, S., Baker, R. (in press). Does Time-on-task Estimation Matter? Implications on Validity of Learning Analytics Findings. Journal of Learning Analytics
  28. 28. Data – Model – Transform Question-driven, not data-driven Barton, D., & Court, D. (Oct 2012). Making Advanced Analytics Work for You. Harvard Business Review, 79-83, https://hbr.org/2012/10/making-advanced-analytics-work-for-you/ar/1
  29. 29. Learning analytics is about learning Gašević, D., Dawson, S., Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64-71.
  30. 30. Once size fits all does not work in learning analytics
  31. 31. Gašević, D., Dawson, S., Rogers, T., Gašević, D. (in press). Learning analytics should not promote one size fits all: The effects of course-specific technology use in predicting academic success. The Internet and Higher Education. Learning context Instructional conditions shape learning analytics results
  32. 32. Learner agency Kovanović, V., Gašević, D., Joksimović, S., Hatala, M., Adesope, S. (2015). Analytics of Communities of Inquiry: Effects of Learning Technology Use on Cognitive Presence in Asynchronous Online Discussions. The Internet and Higher Education, 27, 74–89. More time online does not always mean better learning
  33. 33. Data – Model – Transform Participatory design of analytics tools Barton, D., & Court, D. (Oct 2012). Making Advanced Analytics Work for You. Harvard Business Review, 79-83, https://hbr.org/2012/10/making-advanced-analytics-work-for-you/ar/1
  34. 34. Data – Model – Transform Participatory design of analytics tools Analytics tools for non-statistics experts Barton, D., & Court, D. (Oct 2012). Making Advanced Analytics Work for You. Harvard Business Review, 79-83, https://hbr.org/2012/10/making-advanced-analytics-work-for-you/ar/1
  35. 35. Visualizations can be harmful Corrin, L., & de Barba, P. (2014). Exploring students’ interpretation of feedback delivered through learning analytics dashboards. In Proceedings of the ascilite 2014 conference (pp. 629-633). ascilite.
  36. 36. Data – Model – Transform Participatory design of analytics tools Analytics tools for non-statistics experts Develop capabilities to exploit (big) data Barton, D., & Court, D. (Oct 2012). Making Advanced Analytics Work for You. Harvard Business Review, 79-83, https://hbr.org/2012/10/making-advanced-analytics-work-for-you/ar/1
  37. 37. Marr, B. (Oct 2015). Forget Data Scientists - Make Everyone Data Savvy, http://www.datasciencecentral.com/m/blogpost?id=6448529%3ABlogPost%3A337288
  38. 38. Are we ready to act on analytics?
  39. 39. What to do if we detect deficit models in our practice? Are we ready to act on analytics? Joksimović, S., Gašević, D., Loughin, T. M., Kovanović, V., Hatala, M. (2015). Learning at distance: Effects of interaction traces on academic achievement. Computers & Education, 87, 204–217
  40. 40. How do we deal with performance-oriented culture? Are we ready to act on analytics? Jovanović, J., Pardo, A., Gašević, D., Dawson, S., Mirriahi, N. (2015). Dynamic analytics of learning in flipped classrooms. Manuscript in preparation.
  41. 41. What’s our adoption reality?
  42. 42. CHALLENGES
  43. 43. Current state Benchmarking learning analytics status, policy and practices for Australian universities
  44. 44. Senior management perspective
  45. 45. Senior management perspective
  46. 46. Solution-driven approach Bought an analytics product. Analytics box ticked!
  47. 47. Lack of data-informed decision making culture Macfadyen, L., & Dawson, S. (2012). Numbers Are Not Enough. Why e-Learning Analytics Failed to Inform an Institutional Strategic Plan. Educational Technology & Society, 15(3), 149-163.
  48. 48. Researchers not focused on scalability
  49. 49. LA idealized systems model Colvin, C., Rogers, T., Wade, A., Dawson, S., Gasevic, D., Buckingham Shum, S., Nelson, K., Alexander, S., Lockyer, L., Kennedy, G., Corrin, L., Fisher, J. (2015). Student retention and learning analytics: A snapshot of Australian practices and a framework for advancement. Australian Goverement’s Office for Learning and Teaching.
  50. 50. FINAL REMARKS
  51. 51. Embracing complexity of educational systems
  52. 52. Capacity development Multidisciplinary teams in institutions critical
  53. 53. Ethical and privacy consideration Development of data privacy agency Prinsloo, P., & Slade, S. (2015). Student privacy self-management: implications for learning analytics. In Proceedings of the Fifth International Conference on Learning Analytics And Knowledge (pp. 83-92). ACM.
  54. 54. Sclater, N. (2014). Code of practice for learning analytics: A literature review of the ethical and legal issues. http://repository.jisc.ac.uk/5661/1/Learning_Analytics_A-_Literature_Review.pdf
  55. 55. Development of analytics culture Manyika, J. et al. (2011). Big Data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute, http://goo.gl/Lue3qs
  56. 56. Mahalo!

×