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COLTT Learning at Scale

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In the last 5 years, there has been a rise in what we might call “large-scale digital learning experiments.” These take the form of centralized courses, vendor-created courseware, online homework systems, MOOCs, and free-range learning platforms. If we mine the research, successes, and failures coming out of these experiments, what can we discover about designing better digital learning experiences and technology for learning?

Published in: Education
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COLTT Learning at Scale

  1. 1. Learning at Scale Using Research To Improve Learning Practices and Technology for Teaching Maria H. Andersen, Ph.D. Faculty, Westminster College, Utah
  2. 2. Small Private In-person Courses (SPICs?)
  3. 3. Small Private Online Courses (SPOCS)
  4. 4. Massive Open Online Courses (MOOCs)
  5. 5. Massive Online Self-paced Courses (MOSCs?)
  6. 6. What have we learned?
  7. 7. Lessons from Learning at Scale
  8. 8. We need to improve findability.
  9. 9. The impact of findability on student motivation, self- efficacy, and perceptions of online course quality Authors: B. Simunich, D. Robins & V. Kelly Published: 2015 Study size: n=81, students had to complete 7 tasks, navigating either a well-constructed course (according to QM) or a “broken” course
  10. 10. 7.00x Introduction to Biology: The Secret of Life MITx on EdX Course Report - 2013 Spring Authors: D. Seaton, J. Reich, S. Nesterko, et al. Published: 2014 Study size: 38k signups, 3K certified (Seaton et al, 2014)
  11. 11. (Seaton et al, 2014) Introduction to Biology
  12. 12. 6.00x Introduction to Computer Science and Programming MITx on edX – 2012 Fall Authors: S. Features, P. Grimson, J. Guttag Published: 2014 Study size: 84.5k signups, 5.7K certified
  13. 13. (Features et al, 2014) Introduction to Computer Science and Programming
  14. 14. 14.73x The Challenges of Global Poverty MITx on edX – 2013 Spring Authors: P. Black, P. White Published: 2014 Study size: 40k signups, 4.6K certified
  15. 15. (Black & White, 2014) The Challenges of Global Poverty
  16. 16. Examining Engagement: Analysing Learner Subpopulations in MOOCs Authors: R. Ferguson, D. Clow Published: 2015 Study size: 34k signups, 7k full participants, 4 MOOCs
  17. 17. (Ferguson & Clow, 2015)
  18. 18. Students need to be coerced into more frequent engagement.
  19. 19. Raise your hand if you tell your students or children to be careful sharing on the Internet. Keep your hand raised if you think it’s easy to get students to participate in these without points. Raise your hand if you use discussion boards with your students.
  20. 20. Comments in MOOCs: who is doing the talking and does it help? Authors: B. Swinnerton, S. Hotchkiss & N.P. Morris Published: 2017 Study size: 25k active learners, 8k commenters, 5k students who completed a pre-course survey (roughly half commenters and half non-commenters)
  21. 21. 1-9-90 Rule 1% creators 9% commenters/sharers 90% lurkers
  22. 22. Predicting Student Retention in Massive Open Online Courses using Hidden Markov Models Authors: G. Balakrishnan Published: 2013 Study size: 30k enrolled students in “Software as a Service” MOOC
  23. 23. (Balakrishnan, 2013) Commenting in discussion boards
  24. 24. (Balakrishnan, 2013) Commenting in discussion boards
  25. 25. (Balakrishnan, 2013) Lurking in discussion boards
  26. 26. Comments in MOOCs: who is doing the talking and does it help? Authors: B. Swinnerton, S. Hotchkiss & N.P. Morris Published: 2017 Study size: 25k active learners, 8k commenters, 5k students who completed a pre-course survey (roughly half commenters and half non-commenters)
  27. 27. Improve participation in the learning community.
  28. 28. Examining Engagement: Analysing Learner Subpopulations in MOOCs Authors: R. Ferguson, D. Clow Published: 2015 Study size: 34k signups, 7k full participants, 4 MOOCs
  29. 29. (Ferguson & Clow, 2015)
  30. 30. Samplers Visit, but only briefly (commented in some courses) Strong Starters Complete the first week, but then dropout Returners Made it through 2 weeks, but then dropout Midway Dropouts Dropped out around assessment 3 or 4 Nearly There’s Made it through ¾ of the course, then dropped Late Completers Completed course, but submitted things late Keen Completers Completed course, mostly on time (>80%) (Ferguson & Clow, 2015)
  31. 31. (Graph generated from data in Ferguson & Clow, 2015)
  32. 32. Deconstructing Disengagement: Analyzing Learner Subpopulations in Massive Open Online Courses Authors: R. Kizilcec, C. Piech, E. Schneider Published: 2013 Study size: 94k active learners in 3 computer science MOOCs
  33. 33. Courses need a catch-up option.
  34. 34. Why don’t we offer slipped schedule courses?
  35. 35. This might mean the courses have to be offered on 12-week schedules.
  36. 36. Your click decides your fate : Inferring Information Processing and Attrition Behavior from MOOC Video Clickstream Interactions Authors: T. Sinha, P. Jermann, N. Li et al. Published: 2014 Study size: 66k enrolled, 36.5k interacted with videos, there were 48 video lectures (producing 10 Gb of JSON data) from “Functional Programming in Scala” run on Coursera
  37. 37. 10 GB of JSON video click data Play (Pl) Pause (Pa) SeekFw (Sf) SeekBw (Sb) ScrollFw (SSf) ScrollBw (SSb) RatechangeFast (Rf) RatechangeSlow (Rs) (Sinha et al., 2014)
  38. 38. PlPaSbPl Play (Pl) Pause (Pa) SeekBw (Sb) Play (Pl) Rewatch (Sinha et al., 2014)
  39. 39. RatechangeFast (Rf) Pause (Pa) Play (Pl) Pause (Pa) Fast watching RfPaPlPa (Sinha et al., 2014)
  40. 40. ScrollBw (SSb) SeekBw (Sb) Pause (Pa) Play (Pl) Clear concept SSbSbPaPl (Sinha et al., 2014)
  41. 41. (Sinha et al., 2014) Information Processing Index (IPI)
  42. 42. (Sinha et al., 2014) If students’ video rewatching behavior changes from low IPI to high IPI, they are 33% less likely to drop out.
  43. 43. Don’t aim for perfect. Let students get stuck a little more.
  44. 44. Linear Functions Polynomial Functions Exponential FunctionsQuadratic Functions
  45. 45. Linear Functions Polynomial Functions Exponential FunctionsQuadratic Functions
  46. 46. Linear Functions Polynomial Functions Exponential FunctionsQuadratic Functions Assessing the Reasonability of an Answer
  47. 47. Linear Functions Polynomial Functions Exponential FunctionsQuadratic Functions Creating a mathematical model for an application problem.
  48. 48. Linear Functions Polynomial Functions Exponential FunctionsQuadratic Functions
  49. 49. Interleaving through courses and programs.
  50. 50. Let’s see what you remember…
  51. 51. Improve findability.
  52. 52. Coerce students into more frequent engagement.
  53. 53. Improve participation in the learning community.
  54. 54. Courses need a catch-up option.
  55. 55. Videos: Let students get stuck a little more.
  56. 56. Learning is complex: Improve interleaving of concepts.
  57. 57. busynessgirl@gmail.com busynessgirl.com @busynessgirl maria@coursetune.com coursetune.com
  58. 58. busynessgirl@gmail.c om busynessgirl.com @busynessgirl

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