1. Analyzing Students' Behavior in a Beginner's Programming Course Marija Brkić, Higher Teaching Assistant mbrkic@inf.uniri.hr Maja Matetić, Associate Professor majam@inf.uniri.hr Department of Informatics, University of Rijeka Radmile Matejčić 2, 51000 Rijeka, Croatia http://www.inf.uniri.hr

2. Why are we doing this? Task 6 of the strategy of the University of Rijeka for the period 2008-2013: Pass rate increase for 2nd year enrollment to 75% The course pass rate in the academic year 2012/2013 was 61%. The course pass rate in the academic year 2011/2012 was 63%. We are facing a falling pass rate!!!

3. Course info Programming 1 mandatory course 1 st year of undergraduate study of Informatics C++ procedural programming 82 students in our case study LMS Moodle, supplemental instruction classes ActivityScores Online quizzes 25 Self-evaluation4 Labs9 Glossary2 Exam25 Activity6

4. Visualization as a pre-processing tool

5. Grade distribution

6. Avoiding examination

7. Repeating the course

8. Additional activity I

9. Additional activity II

10. Relationship with the final grade

11. Pre-processing Missing values for one part of activities have been replaced with minimum values Examples with the remaining missing values have been filtered out Additional attribute has been generated (Labs)

12. Data mining techniques Association Classification Clustering Outlier detection

13. Association rules NoAntecedentConfidenceLift 1Exam11,761 2Self-evaluation, Exam11,761 3Labs, Exam11,761 4Quizzes, Exam11,761 5Self-evaluation, Labs, Exam11,761 6Self-evaluation, Quizzes, Exam11,761 7Labs, Quizzes, Exam11,761 8Self-evaluation, Labs, Quizzes, Exam11,761 9Labs, Quizzes, Glossary0,951,677 10Self-evaluation, Labs, Quizzes, Glossary0,951,677 11Quizzes, Glossary0,911,601 12Self-evaluation, Quizzes, Glossary0,911,601 13Labs, Quizzes0,881,55 14Self-evaluation, Labs, Quizzes0,881,55 15Quizzes0,831,467 16Self-evaluation, Quizzes0,831,467

14. Classification rules

15. Clustering Activity 6 Exam 25 Self- evaluation 4 Glossary 2 Quizzes 25 Labs 9 Total 71 Items Cluster 02.76520.6183.8060.37921.0187.05955.64417 Cluster 10.76514.4123.3610.29618.0214.41241.26617 Cluster 21.2005.5483.2120.14015.7943.00028.84320 Cluster 30.0711.0932.7880.0699.9071.60715.39214 Cluster 40.000 0.8860.0061.7500.3642.94113

16. Outlier detection ActivityExamSelf-evaluationGlossaryQuizzesLabsTotal Cluster 06.016.53.860.2819.06.051.64 Cluster 01.025.04.01.223.756.060.95 Cluster 00.023.03.861.2817.53.048.64 Cluster 05.020.03.860.023.759.061.61 Cluster 20.015.53.140.013.51.533.64 Cluster 20.019.03.710.014.06.042.71 Cluster 25.011.03.931.0421.83.045.77 Cluster 22.013.03.681.1221.07.548.3 Cluster 30.07.52.00.08.251.519.25 Cluster 44.01.53.50.0818.00.027.08

17. Student comments on newly introduced activities Official evaluation –I liked the labs because they force us to work on new materials continuously –I liked the labs because they encourage us to exercise regularly –professors gave us a lot of materials and organized everything perfectly – from labs to supplemental instruction Class evaluation –the labs made us work continuously –it is a good idea for getting scores, though the evaluation system should be less harsh and give partial credits –excellent idea set to practice perfectly –labs helped a lot for continuous engagement

18. Future work Time analysis (self-evaluation) Log analysis (forum, laboratory exercises, etc.) Classification issues

19. Conclusion We are actually not facing a falling pass rate!!!

20. Thank You for your attention!