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An Adaptive Learning Partnership

An Adaptive Learning Partnership. Chuck Dziuban, UCF Patsy Moskal, UCF Connie Johnson, CTU Colm Howlin, Realizeit. The Problem. 4 th 3 rd 2 nd First. 77%. Chances of College Completion. Income Quartile. 34%. 17%. 9%. Compounding the Problem: Average College Debt. $39,400.

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An Adaptive Learning Partnership

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  1. An Adaptive Learning Partnership Chuck Dziuban, UCF Patsy Moskal, UCF Connie Johnson, CTU Colm Howlin, Realizeit

  2. The Problem 4th 3rd 2nd First 77% Chances of College Completion Income Quartile 34% 17% 9%

  3. Compounding the Problem: Average College Debt $39,400 $37,173 $29,400 $23,450 Amount in Dollars $18,750 $17,550 $12,850 $9,450 • 1993 2017

  4. Adaptive Learning… • Personalizes the educational experience • Customizes content • Assesses continuously

  5. An Adaptive Learning Partnership CTU UCF

  6. A Model of School Learning: John Carroll 1963, Teachers College Record Degree of Learning = f

  7. How Hans Rosling Might Explain It How Much You Learn Time You Have

  8. Pieces in the Adaptive Learning Puzzle Cognitive Social Learning Scaling Behavioral Affective Time Access Perspective

  9. Public, metropolitan • 68,000+ students • 224 degrees, 12 colleges • 42% SCU online • 88% 18-24 year olds • 54% female • 35% 4+ online courses • 43% unemployed • Private, for profit • 25,000+ students • 123 degrees, 6 colleges • 23,000+ online students • 8% 18-24 year olds • 72% female • 71% 4+ online courses • 43% 40+ hours per week

  10. Adaptive Learning at UCF

  11. UCF Faculty Development – PAL 6000 • Pedagogy for adaptive courses • Technical and logistical issues • Course delivery strategies • Course building in Realizeit and Canvas • Information unique to teaching adaptive courses at UCF • 5 PAL Instructional Designers support faculty

  12. Adaptive Learning Approaches Every module – simple use with feedback One module or topic In-depth, detailed full course A few modules or concepts Every module – advanced use

  13. Adaptive Learning Scale at UCF *as of Spring 2019

  14. UCF Examples: Adaptive Learning in Practice

  15. Advantages of Adaptive Learning:Faculty Viewpoint • Low or no cost to the student; can replace textbook • Can customize content (word problems) based on institution, major demographics, student needs, level of preparation, connection to other courses, etc.

  16. Learning Content, Verbiage, and Demographics are Algorithmic

  17. Adaptive Learning at CTU: Faculty

  18. Watch Them Learn: Real-Time Instructor View

  19. How did we scale faculty use? • Initially, asynchronous specialized training (mandatory) was provided to faculty • Faculty training team also hosted regular office hours using a video conferencing and screen sharing platform, where faculty could login, ask questions in a synchronous environment • Surveys were used to collect feedback on the effectiveness of the training. • Besides the initial specialized training and office hours, faculty had specific requests on need-it-now resources to highlight functionality, terminology, and how-to guides.

  20. Student Attitudes Toward Adaptive Learning Perspective

  21. Adaptive Learning at UCF and CTU* *Data provided by Realizeit; correct as of May 16, 2018

  22. Adaptive learning gave me feedback on objectives P=.00

  23. Adaptive learning became personalized to me over time P=.00

  24. Adaptive learning increased my engagement P=.00

  25. I would take another adaptive learning course P=.00

  26. How often did you interact with students (compared to non-adaptive course)? P=.00

  27. What do students say? “I loved it. I love the ease and the ability to see exactly what I am struggling with instead of getting overwhelmed on the whole subject. I can focus on what I am not retaining.” “The material could have been more closely aligned with the test material so that my efforts in Realizeit better prepared me for the actual in-class exams.”

  28. Student Behaviors Behavioral

  29. Prototype Behaviors@ UCF Psychology http://bit.ly/RealizeitPsyc Intermediate and College Algebra http://bit.ly/RealizeitAlg

  30. Automated method for detecting outlier behaviors

  31. What about the least successful behaviors? Students stop too early and don’t have enough days with progress. Students leave too big a gap in the middle and don’t have enough days with progress. Started a little late and needs to make more progress in a single sitting.

  32. Intervention Strategies • What are effective intervention strategies in a system with full or partial student agency? • Does experience built in traditional settings transfer to adaptive learning? • Are there some behaviors that should be avoided? Do some lead to better outcomes or retention of knowledge? Do some have an impact on other aspects of learning? Changing Mindsets • Teaching students to be self-regulated adaptive learners • We have taken the approach of build it, give it to them, and they will figure it out. • Can we improve student outcomes by teaching them to self-regulated adaptive learners? • How do we strike a balance between self-regulated versus expert-assisted versus machine-guided learning?

  33. Determine if differing disciplines and university contexts alter learning patterns New Research

  34. The Realizeit Domain Knowledge Coverage TypicalPerformance Calculated Score Coverage Increase Baseline Messages Interaction Total Time Total Activity Practice Revisions

  35. Adaptive Learning: Underlying Dimensions Introductory Algebra-CTU • Intermediate Algebra-UCF • Analytic Algebra-CTU • College Algebra-UCF • Trends in Contemporary Nursing-CTU • Pathophysiology-UCF Knowledge Acquisition Engagement Growth Communication

  36. Comparison of Courses – Communication

  37. What is the Moral Algebra for You and Adaptive Learning? What problem can you solve? (Value Add) What is it going to cost you? (Opportunity Cost) Learn more Think about it Dabble Pilot Test “Implement”

  38. Useful Links & References • Dziuban, C., Howlin, C., Johnson, C., & Moskal, P. (2017, December 18). An Adaptive Learning Partnership. EDUCAUSE Review: https://er.educause.edu/articles/2017/12/an-adaptive-learning-partnership • Dziuban, C., Howlin, C., Moskal, P., Johnson, C., Parker, L., & Campbell, M. (2018). Adaptive learning: A stabilizing influence across disciplines and universities. Online Learning, 22(3), 7-39. https://olj.onlinelearningconsortium.org/index.php/olj/article/view/1465 • Dziuban, C., Howlin, C., Moskal, P., Johnson, C., Eid, M., Kmetz, B. (2019). Adaptive Learning: Context and Complexity. E-mentor, 5(77), http://www.e-mentor.edu.pl/eng/article/index/number/77/id/1384 • Summary of paper and principal component analysis: https://lab.realizeitlearning.com/blog/

  39. For more information: Patsy Moskal University of Central Florida Patsy.Moskal@ucf.edu Connie Johnson Colorado Technical University Cjohnson@coloradotech.edu Chuck Dziuban University of Central Florida Charles.Dziuban@ucf.edu Colm Howlin Realizeit Colm.Howlin@realizeitlearning.com

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