1. Adaptive Learning: Background, Applications and Lesson Building
Autar Kaw
AutarKaw.com
Eleonora Delgado
University of South Florida
2018 ASEE-SE Workshop – March 4, 2018

2. Acknowledgments
This material is based upon work supported partially by the National Science Foundation under Grant Number # , and the Research for Undergraduates Program in the College of Engineering at USF. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

3. BACKGROUND

4. Conventional, Mastery, Tutor
1-30*
Mastery
Learning
Tutorial
1-1*
*Teacher-Student Ratio
Source: The 2-Sigma Problem by Bloom, B., 1984

5. Definition of Effect Size
Effect Size
Percentage of control group who would be below the average person in experimental group
50%
0.5
69%
1.0
84%
1.5
94%
2.0
98%
Source: It is the Effect Size Stupid…. By Coe, R.

6. Effect Size
Source: The Relative Effectiveness of Human Tutoring …. By Vanlehn, K., 2011

7. What do you think is the actual effect size of human tutoring?
0.5
0.7
1.0
2.0

8. What do you believe is adaptive learning?
Reflection Exercise
What do you believe is adaptive learning?

9. What does adaptive learning involve?
Uses data to give and improve pathways to learning
Uses pre-set configurations
Is rule-based and uses decision trees

10. Adaptive Learning Pre-set categories Data driven and improves
DIFFERENTIATED
Pre-set categories
Rules-based and decision tree
Data driven and improves
ADAPTIVE
INTELLI TUTOR
Source:

11. Platform Players Knewton Smart Sparrow RealizeIT Pearson's McGraw-Hill
Wiley

12. PROCESS

13. A Typical Adaptive Path

14. Reflection Exercise
Think of your own course and imagine reasonable resources like video, text and questions are available to you for a single concept or topic. What path would you design for your students?

15. RESULTS

16. Adaptive Learning Results
ASU Math Readiness
Fall 2009-Spring 2011
(Without Adaptive Learning)
Fall 2011-Spring 2012 (With Adaptive Learning)
Pass Rates
64%
75%
Withdrawal Rates
16% 7%
Students Finishing Early
n/a
45%
Source:

17. Adaptive Learning MetaStudy
Source: Lessons Learned From Early Implementations of Adaptive

18. Adaptive Learning MetaStudy
Source: Lessons Learned From Early Implementations of Adaptive

19. Our Use of Adaptive Learning

20. What is different? Transmission in class and assimilation at home
Transmission at home and assimilation in class
Source: CTL, University of Washington

21. What happens BEFORE class?

22. Assign video lectures before class.

23. What is done before class at home?
Assign reading assignment.

24. What graded assignments are given before class?
Automatically graded quizzes are assigned

25. Effect Size For Free Response Questions in USF Course
Flipped Adaptive over Flipped
0.26
for Pell Grant Students
0.50
Flipped Adaptive over Blended
0.13
0.28

26. Analytics Summary

27. Analytics (Grade and Time Spent)

28. A LEARNING PHILOSOPHY

29. Universal Design Learning (UDL)

30. The Trinity of UDL What – Recognition network How – Strategic Network
Multiple means of representation
Multiple means of action and expression
Multiple means of engagement
How – Strategic Network
Why – Affective Network
Source: National Center on Universal Design for Learning

31. Reflection Exercise
Make a list of multiple means of a) representation b) action and expression c) engagement

32. LET’S BUILD A LESSON

33. Download files http://www.eng.usf.edu/~kaw/download/workshop/ OR

34. Contact: Autar Kaw kaw@usf.edu University of South Florida
Adaptive Learning: Background, Applications and Lesson Building
QUESTIONS?
Contact: Autar Kaw
University of South Florida