Learning analytics for Medical Education
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This document provides an introduction to learning analytics. It defines analytics and learning analytics. It discusses case studies using learning analytics to analyze viewing times of course materials and social network analysis. It notes challenges of learning analytics including issues with data size, sharing, and compatibility as well as tools, people, and educational impact. It encourages the community to connect, collaborate, learn, appraise, share, and facilitate as the field continues to develop.
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Learning analytics for Medical Education
- 1. Learning Analytics: An Introduction Dr. Janet Corral Faculty, Educational Informatics University of Colorado School of Medicine
- 2. @edtechcorral #edinformatics #bigdataedu Janet Corral
- 3. Overview • Analytics • Learning Analytics • Case Studies • Challenges & Opportunities • Where do we go from here?
- 4. What are ‘Analytics’? 0101110001101 0101011010100 0101011010101 0010111010101 0101010111101 0101101010110 1010110101010 1010101001010 1010101010001 0101010101010 0010101010100 1011101010010 1010101010111 0101010100101 0111010101010 1010001110101 0101010111010 1000101010111
- 5. Big Data for Business 010111000110101010 110101000101011010 101001011101010101 010101111010101101 010110101011010101 010101010010101010 101010001010101010 101000101010101001 011101010010101010 101011101010101001 010111010101010101 00011101011010101
- 6. Big Data for Business
- 7. Big Data for Business 010111000110101010 110101000101011010 101001011101010101 010101111010101101 010110101011010101 010101010010101010 101010001010101010 101000101010101001 011101010010101010 101011101010101001 010111010101010101 00011101011010101
- 8. Big Data for Health Care Carrier Status Disease Risk Drug Response Research
- 9. What about medical education? LMS Exams ePortfolio Lecture Capture Admissions
- 10. DEFINITIONS
- 11. Learning Academic Analytics Analytics
- 12. What is “learning analytics”? Siemens, G., Gasevic, D., Haythornthwaite, C., Dawson, S., Sh um, S. B., Ferguson, R., . . . Baker, R. S. J. D. (2011)
- 13. CASE STUDIES - BASIC
- 14. LMS + Google Analytics = ? With gratitude to the Entrada Project: http://www.entrada-project.org/
- 15. Podcasting Hemopathology Anemia 60 60 Viewing Time (in mins) Viewing Time (in mins) 50 50 40 40 30 30 20 20 10 10 0 0 s1 s2 s3 s4 s5 s6 s7 s8 s9 s10 s11 s12 s13 s14 s1 s2 s3 s4 s5 s6 s7 s8 Students Students Hematopoesis Intro to Coagulation 70 70 60 60 Viewing Time (in mins) 50 Viewing Time (in mins) 50 40 40 30 30 20 20 10 10 0 0 s1 s2 s3 s4 s5 s6 s7 s8 s9 s10 s11 s1 s1 s2 s3 s4 s5 s6 s7 s8 s9 s10 s11 Students Students With gratitude to UC Denver META Unit: http://goo.gl/g90rs
- 16. What Does The Data Mean? • Clicks • Navigation • Assumptions • Interpretation • Confusion • Predictors and causes • Data + behavioural practices
- 18. CASE STUDIES - APPLIED
- 19. Social Network Analysis Advice-seeking network. Hawe P , Ghali L Health Educ. Res. 2007;23:62-69 © The Author 2007. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org
- 21. Holland: Shared Education Data Van der Linden, Lammers & Wijffelars. (2011). http://videolectures.net/edm2011_van_der_linden_educatio
- 22. NYU Educational Data Warehouse With gratitude to NYU Educational Data Warehouse: alex.support@med.nyu.edu
- 23. Points to Consider: • Visualization • Reporting • Timelines • Expectations • Policies
- 24. Open Learning Analytics Siemens, G., Gasevic, D., Haythornthwaite, C., Dawson, S., Sh um, S. B., Ferguson, R., . . . Baker, R. S. J. D. (2011)
- 25. Learning Analytics: Virtual Patients Corral, J. (2012). Learning with Virtual Patients.
- 26. The Gold Standard Path Corral, J. (2012). Learning with Virtual Patients.
- 27. Hmm… Successes Limitations Frequency by individual node Click = ? Pathways by individual user Insight into thinking processes Data we didn’t have before Insight into decision making Individual or collective use?
- 29. Challenges & Opportunities Data • Size • Security • Sharing • Cross-institutional • Compatibility • Policies • Algorithms • Transparency • Storage • Openness • Focus
- 30. Challenges & Opportunities Tools • Variety • Algorithms • Transparency • Openness • Focus • Scale
- 31. Challenges & Opportunities People • Multiple skill sets • Collaboration • Education • Ownership • Ethics • Privacy • Transparency
- 32. Challenges & Opportunities Educational Impact • Success • Ownership • Ethics • Privacy • Return on Investment • Multiple skill sets • Collaboration • Education
- 33. Where do we go from here? • Community • Collaborate • Learn • Appraise • Share • Facilitate
- 34. Connect, Participate, Share Janet Corral
Editor's Notes
- 1. Don’t confuse predictors and causes. 2. What about social learning processes?