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Data Visualization and Learning Analytics with xAPI

With the Experience API we are able to collect more granular, high-resolution data from our learning tools and platforms. But once we have that data, how do we present it in ways that easily communicate the right insights to our stakeholders?

In this presentation from the xAPI Cohort's Spring 2018 session, you'll find a brief historical survey of data visualizations, three keys to designing good data visualizations, and case studies of xAPI specific data visualizations and the insights they provided to organizations.

Data Visualization and Learning Analytics with xAPI

  1. 1. DataVisualization and Learning Analytics with xAPI March 29, 2018 — #xAPI Margaret Roth // @margaret_h_r
  2. 2. We’ve been visualizing data for hundreds of years. 2 background data viz case studies q&a takeaways The Tree of the Two Advents, 1202
  3. 3. Geometry, 1587 We visualize data so that we can see patterns in information. 3 background data viz case studies q&a takeaways
  4. 4. But what makes good data visualization good? Diagrams, 1854 4 background data viz case studies q&a takeaways
  5. 5. ØLet the user ask questions. ØConsider how users will ask questions. ØMake intuitive options for interaction that allows for fluid exploration of the data. 1. Interactive 5 background data viz case studies q&a takeaways
  6. 6. Diagrams, 1854The World Above Us, 2014 6 background data viz case studies q&a takeaways
  7. 7. Diagrams, 1854Yet Analytics xAPI LRS Timeline 7 background data viz case studies q&a takeaways
  8. 8. ØHelp the user see relationships between different variables. ØConsider the visual space and all the dimensions that you can reveal information. ØThink about color, size, shape, thickness, opacity, and motion. 2. Multi-Dimensional 8 background data viz case studies q&a takeaways
  9. 9. Diagrams, 1854 Buzzy Drinks, 2013 9 background data viz case studies q&a takeaways
  10. 10. Diagrams, 1854 Yet Analytics xAPI LRS Statement Frequency 10 background data viz case studies q&a takeaways
  11. 11. Diagrams, 1854 Yet Analytics xAPI LRS Statements Over Time 11 background data viz case studies q&a takeaways
  12. 12. ØUse visualization types that match your data. ØGood visualization conveys information in a much smaller footprint than the same data presented in tabular formats. ØGraph types imply relationships, choose ones that work with your data, not against it. 3.Visually Efficient 12 background data viz case studies q&a takeaways
  13. 13. Weather Radials, 2014 13 background data viz case studies q&a takeaways
  14. 14. Learning Economic Social Index, 2016 14 background data viz case studies q&a takeaways
  15. 15. Yet Analytics xAPI LRS Outliers Graph 15 background data viz case studies q&a takeaways
  16. 16. Public Nursing School Measuring the Effectiveness of Instructional Content with Granular Learner Behavior 16 background data viz case studies q&a takeaways
  17. 17. Problem ØDeveloping the expertise of students in diverse patient environment ØFocused on in-person experiential learning for students ØWanted to incorporate online interactive simulations and provide mobile learning solutions ØWanted more granular data 17 background data viz case studies q&a takeaways
  18. 18. ØDevelop interactive eLearning modules using Lectora ØUse xAPI to collect granular data about student response behavior and send statements to theYet LRS ØAnalyze and manipulate data inYet LRS ØExport unified data to current BI workflow to correlate and apply results Solution 18 background data viz case studies q&a takeaways
  19. 19. ØDevelop interactive eLearning modules using Lectora ØUse xAPI to collect granular data about student response behavior and send statements to theYet LRS ØAnalyze and manipulate data inYet LRS ØExport unified data to current BI workflow to correlate and apply results Solution 19 background data viz case studies q&a takeaways
  20. 20. ØMost students correctly identify findings ØSome students ask more questions than they need to and flag things that are not relevant ØIdentification of significant findings does not translate to correct decision making in branching scenarios ØMost students reject poor choices but many get distracted by reasonable choices Learning Analytics Source: https://www.slideshare.net/slideshow/embed_code/key/cImyNV4uIAS2d1 20 background data viz case studies q&a takeaways
  21. 21. Source: https://www.slideshare.net/slideshow/embed_code/key/cImyNV4uIAS2d1 21 background data viz case studies q&a takeaways
  22. 22. ØInteractive eLearning modules enhance instruction and improve learning analytics ØCreates feedback loop for instructors so they can identify necessary interventions and personalize learning ØEasy to collect learning analytics provide foundation for long-term data-driven instructional improvements Outcomes “With xAPI it’s now possible to gain insights into our students’ clinical reasoning skills.Yet Analytics worked closely with us and made it possible to harness this new technology. ” – Andrew Corbett, PhD Source: https://www.slideshare.net/slideshow/embed_code/key/cImyNV4uIAS2d1 22 background data viz case studies q&a takeaways
  23. 23. Reimagining Performance Assessment in Personalized Learning & Development 23 background data viz case studies q&a takeaways
  24. 24. Problem ØHad selected the best learning tools and platforms ØUsed a modular approach and combined the components that best suited their needs ØDesigned a program and curriculum to support self-paced, self-directed, blended learning 24 background data viz case studies q&a takeaways
  25. 25. ØEasy to understand for students, actionable for teachers and other stakeholders ØSeamless, single-sign-on, multi-permission access structure ØSecure data processing and storage ØModular ecosystem approach for future compatibility Solution 25 background data viz case studies q&a takeaways
  26. 26. Teacher – ProfessionalStudent – 9Years Old 26 background data viz case studies q&a takeaways
  27. 27. Teacher – ProfessionalStudent – 9Years Old 27 background xAPI case studies Q&A takeaways
  28. 28. Teacher – ProfessionalStudent – 9Years Old 28 background xAPI case studies Q&A takeaways
  29. 29. Teacher – ProfessionalStudent – 9Years Old 29 background xAPI case studies Q&A takeaways
  30. 30. Teacher – ProfessionalStudent – 9Years Old 30 background data viz case studies q&a takeaways
  31. 31. Outcomes ØReal-time insight into student progress ØIndividual learner dashboards that empower students and facilitate communication with other stakeholders ØRole-specific dashboards making it easy for teachers, parents, and administrators to see learner masteries across tools at a glance 31 background data viz case studies q&a takeaways
  32. 32. Measuring Skill Development through a Multi- Source Learning Experience Interface 32 background data viz case studies q&a takeaways
  33. 33. Problem ØLearning content lives in an overwhelming number of locations ØDifficult for learners to get the content needed when it’s needed ØInstructional designers lack visibility into how resources are used or if they are valuable 33 background data viz case studies q&a takeaways
  34. 34. ØContent from different platforms and hosting systems is searchable in a single user interface ØIndividual learners can track their progress across content and playlists ØContent creators and cohort leaders are able to see engagement trends and informal learning progress Solution 34 background xAPI case studies Q&A takeaways
  35. 35. Curated Playlists Created by InstructorsUnified Search Portal for Learners 35 background xAPI case studies Q&A takeaways
  36. 36. Content Browse by Source andTopicLearning Network by Provider 36 background data viz case studies q&a takeaways
  37. 37. Competency MappingThrough Data ModelLearner Profile with Skill Development 37 background data viz case studies q&a takeaways
  38. 38. Competency MappingThrough Data ModelLearner Profile with Skill Development 38 background data viz case studies q&a takeaways
  39. 39. Competency MappingThrough Data ModelLearner Profile with Skill Development 39 background data viz case studies q&a takeaways
  40. 40. Outcomes ØProvides multiple pathways into content for learners and improves content searchability ØContent curation is streamlined through playlist creation and community validation ØProgress data from informal learning is automatically collected and stored in a learner’s profile ØEnables a unified learner experience 40 background data viz case studies q&a takeaways
  41. 41. What to do next? Work with your own data visually! The Tree of the Two Advents, 1202 41 background data viz case studies q&a takeaways
  42. 42. Start with Yet Adapter: The fastest, easiest, free-est way to get xAPI data. Click to transform data to xAPI.Select and upload a .csv file from your computer. 42 background data viz case studies q&a takeaways
  43. 43. Start with Yet Adapter: The fastest, easiest, free-est way to get xAPI data. Create new chips as needed. Manipulate columns from .csv file to configure xAPI statements. 43 background data viz case studies q&a takeaways
  44. 44. Start with Yet Adapter: The fastest, easiest, free-est way to get xAPI data. Send data to an LRS of your choice. 44 background data viz case studies q&a takeaways
  45. 45. Start with Yet Adapter: The fastest, easiest, free-est way to get xAPI data. If you send it to theYet LRS it will look something like this! 45 background data viz case studies q&a takeaways
  46. 46. Learner Dashboard Ø What does my activity tell me about the way I learn? Ø What’s a good fit for me? Ø What opportunities are available to me as I progress? Ø What are the competencies I need to demonstrate in order to achieve my goals? 46 background data viz case studies q&a takeaways
  47. 47. Instructor Dashboard Ø What does my class profile suggest about the appropriateness of the content and instructional strategy? Ø Can I identify learners based on trends in their learner pathway? Ø Can I identify who will require intervention or enhanced content? Ø Is the instructional design contributing to learning growth? 47 background data viz case studies q&a takeaways
  48. 48. Manager Dashboard Ø Which of my team members is best suited for which role? Ø If something goes wrong, who can I count on? Ø Can understanding my team’s experience better prepare me for challenges we will face together? Ø Can my team’s experiences be used to provide guidance to other teams? 48 background data viz case studies q&a takeaways
  49. 49. We come at this to solve a data problem. The Tree of the Two Advents, 1202 49 background data viz case studies q&a takeaways
  50. 50. Once we get the data in the same format, we can move on to the real challenge — solving our learner experience problem. The Tree of the Two Advents, 1202 50 background data viz case studies q&a takeaways
  51. 51. • Go explore an LRS for yourself — https://www.yetanalytics.com/demo • Get aYet xAPI LRS Sandbox — https://www.yetanalytics.com/free-sandbox-account • Start using theYet Adapter — https://www.yetanalytics.com/yetadapter • TheYet Adapter allows non-technical users an easy way to upload spreadsheet data and to transform it into xAPI data which can be sent to any Learning Record Store. • Have questions? Want these slides? Leave a card or email margaret@yetanalytics.com Thank you for sharing your time with me! 51 background data viz case studies q&a takeaways
  52. 52. Let us know how we can help! 52 background data viz case studies q&a takeaways
  53. 53. From learning analytics to data logistics, Yet Analytics helps transform learning experience into business intelligence. Tools and solutions used to improve learning and talent development. 53 background data viz case studies q&a takeaways

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