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Animated Examples as Practice Content
in a Java Programming Course
Roya Hosseini, Teemu Sirkiä, Julio Guerra
Peter Brusilo...
www.techinasia.com
2
Understanding Program Dynamics
3
Jeliot 3
4
[Moreno et al., 2004]
Python Tutor
5
[Guo, 2013]
Were They Successful?
6
7
Labs
8
Classrooms
Practice System
9
10
✓ Teachers use it
✗ Students don’t use it
11
Engagement
Social Comparison
Open Student Modeling
Organized Course Structure
Mastery Grids [Loboda et al., 2014]
12
13
Demo
14
15
16
Classroom Studies
17
PITT 2014 (n=56)
PITT 2015 (n=33)
WSSU 2015 (n=20)
Practice System: Mastery Grids
Domain: Java Progra...
• Value of animated examples
• Baseline: annotated examples
18
Data Analysis
Measures
• Engagement
• Problem solving performance
• Learning gain
• Grade
19
20
71.4%
95.0%
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%
Annotated Ex. Animated Ex.
Avg. completion% (N=109)
Avg. %exampl...
21
61.1
128.2
0
40
80
120
160
Annotated Ex. Animated Ex.
Avg. time per example
(sec) N=109 Avg. total time (sec)
spent on ...
22
Regression Analysis
example
attempts
knowledge+
-
23
IV Impact on
#correct problems
#Animated ex. +
Time on annotated ex. -
Step-wise regression (N = 109)
DV: #correct prob...
24
Step-wise regression (N = 75)
DV: post-test
IV: pretest, gender, group, usage measures
IV Impact on
post-test
#Animated...
25
IV Impact on
grade
#Animated ex. +
#Annotated ex. -
Step-wise regression (N = 75)
DV: grade
IV: pretest, gender, group,...
Technology Pays Back!
✓Example completion
✓Student performance
✓More work  higher performance
26
Guiding student within animation
• saves time
• assures viewing must-seen parts
27
Selected References
Mastery Grids
Loboda et al. (2014). Mastery grids: An open source social educational progress
visualiz...
29
Jeliot 3
Moreno et al. (2004). Visualizing programs with Jeliot 3. Proc. of the working
conference on Advanced visual i...
30
http://people.cs.pitt.edu/~hosseini/mg.html
Contact: roh38@pitt.edu
Practice System
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SIGCSE 2016

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SIGCSE 2016

  1. 1. Animated Examples as Practice Content in a Java Programming Course Roya Hosseini, Teemu Sirkiä, Julio Guerra Peter Brusilovsky, Lauri Malmi SIGCSE 2016 1
  2. 2. www.techinasia.com 2
  3. 3. Understanding Program Dynamics 3
  4. 4. Jeliot 3 4 [Moreno et al., 2004]
  5. 5. Python Tutor 5 [Guo, 2013]
  6. 6. Were They Successful? 6
  7. 7. 7 Labs
  8. 8. 8 Classrooms
  9. 9. Practice System 9
  10. 10. 10 ✓ Teachers use it ✗ Students don’t use it
  11. 11. 11 Engagement Social Comparison Open Student Modeling Organized Course Structure
  12. 12. Mastery Grids [Loboda et al., 2014] 12
  13. 13. 13
  14. 14. Demo 14
  15. 15. 15
  16. 16. 16
  17. 17. Classroom Studies 17 PITT 2014 (n=56) PITT 2015 (n=33) WSSU 2015 (n=20) Practice System: Mastery Grids Domain: Java Programming 3 types of interactive content in 19 topics
  18. 18. • Value of animated examples • Baseline: annotated examples 18 Data Analysis
  19. 19. Measures • Engagement • Problem solving performance • Learning gain • Grade 19
  20. 20. 20 71.4% 95.0% 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% 120.0% Annotated Ex. Animated Ex. Avg. completion% (N=109) Avg. %examples viewed by user Annot. : 33%(SE=3%) Anim. : 24%(SE=3%)
  21. 21. 21 61.1 128.2 0 40 80 120 160 Annotated Ex. Animated Ex. Avg. time per example (sec) N=109 Avg. total time (sec) spent on examples by user Annot. : 2196.5 (SE=285.6) Anim. : 1585.7 (SE=426.5)
  22. 22. 22 Regression Analysis example attempts knowledge+ -
  23. 23. 23 IV Impact on #correct problems #Animated ex. + Time on annotated ex. - Step-wise regression (N = 109) DV: #correct problems IV: pretest, gender, group, usage measures
  24. 24. 24 Step-wise regression (N = 75) DV: post-test IV: pretest, gender, group, usage measures IV Impact on post-test #Animated ex. + #Annotated ex. -
  25. 25. 25 IV Impact on grade #Animated ex. + #Annotated ex. - Step-wise regression (N = 75) DV: grade IV: pretest, gender, group, usage measures
  26. 26. Technology Pays Back! ✓Example completion ✓Student performance ✓More work  higher performance 26
  27. 27. Guiding student within animation • saves time • assures viewing must-seen parts 27
  28. 28. Selected References Mastery Grids Loboda et al. (2014). Mastery grids: An open source social educational progress visualization. In Open Learning and Teaching in Educational Communities (pp. 235- 248) Animated Examples Sirkiä, T. (2013). A JavaScript library for visualizing program execution. The 13th Koli Calling International Conf. on Computing Education Research (pp. 189-190) WebEx Brusilovsky et al. (2009). Problem solving examples as first class objects in educational digital libraries: Three obstacles to overcome. Journal of Educational Multimedia and Hypermedia, 18(3) (pp. 267–288) 28
  29. 29. 29 Jeliot 3 Moreno et al. (2004). Visualizing programs with Jeliot 3. Proc. of the working conference on Advanced visual interfaces (pp. 373-376) Python Tutor Guo, P. J. (2013). Online python tutor: embeddable web-based program visualization for cs education. Proc. of the 44th ACM technical symposium on Computer science education (pp. 579-584) QuizJET Hsiao et al. (2008). Web-based parameterized questions for object-oriented programming. Proc. of the World Conference on E-Learning (pp. 17-21)
  30. 30. 30 http://people.cs.pitt.edu/~hosseini/mg.html Contact: roh38@pitt.edu Practice System

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