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Xiao Hu "Overview of the Space of Learning Analytics and Educational Data Mining"
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Xiao Hu "Overview of the Space of Learning Analytics and Educational Data Mining"






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Xiao Hu "Overview of the Space of Learning Analytics and Educational Data Mining" Presentation Transcript

  • 1. Overview of the Space of Learning Analytics and Educational Data Mining George Siemens (University Of Texas, Arlington And SoLAR) & Ryan Baker (Columbia University) Presented by Xiao Hu @ University of Hong Kong
  • 2. Scholarly Communication Venues Provided by SoLAR • LAK, JLA, LASI, LAMP • The mailing-lists • LA Google group: https://groups.google.com/forum/#!forum /learninganalytics • EDM-Discuss http://www.educationaldatamining.org/IE DMS/mailinglists
  • 3. Types of EDM Methods • Prediction • Structure Discovery • Relationship Mining • Distillation of Data for Human Judgment • Discovery with Models • Bring SoL and analytic geeks together
  • 4. What's Going on in Learning Analytics • Research methods are becoming finely turned • Growing impact on practice • Increased Computer Science presence
  • 5. What's Going on in EDM • Lots of classification and regression • Increased emphasis on latent knowledge estimation and knowledge structure discovery •figure out what students doing • Reduced emphasis on relationship mining (association rules)
  • 6. What's Going on in EDM (Con’d) • Constructs studied are broadening • Meta-cognition • Affect • Engagement • Motivation • Long-term participation (cross-years) • Increased number of studies with models analysis, particularly on more generalized models
  • 7. What's going on in EDM (Con’d) • Basic research • Automated intervention • Getting into "reporting“ •understand the meaning of the model, tell people what we found • Increased participation of industry
  • 8. Going Forward… • New tools, techniques and people (disciplines) • Data: openness, ethics and scope • Target of analytics activity • Connections to related fields and practitioners (collaborations, LAMP) • Challenges: creating strategic links to related communities
  • 9. Coming Up • A MOOC on EdX "Data, Analytics and Learning", Starting Oct. 20th, 2014 • LAK2015: in NY (deadline: Dec. 24th) • ICEDM2015 in Madrid (deadline: Dec. 24th)
  • 10. Q1: Friction between Computer Scientists and Learning Analytics ? • LAK vs EDM papers? •EDM don't use huge datasets • Around what is knowledge, fairness, equality • Will see more and more studies using CS methods, but the attributes of learning experience are also important
  • 11. Q2: Collaboration with Start- ups? • Certainly open to building connections to start-ups, as there is so much activity going on • But such connections are not yet explicit • Companies are scattered, connections are much appreciated!
  • 12. Q3: Research Ethics : Consent form, Privacy etc. ? • Do students have to give consent? • Not clear, no legal architecture in this area • Privacy: does it apply to MOOCs? • As a community, we need to educate the IRB about the nature of our research; • Improve the ways of anonymizing data; • Educate ourselves about how to manage data (for long-term access and re-use)
  • 13. Lightening Talks by Doctoral Student Attendees
  • 14. Questions for Clarifications? •Discussions will be after three presentations!