+ Examining the Effect of Programming Experience When Using Snap - - PowerPoint PPT Presentation

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Examining the Effect of Programming Experience When Using Snap

Raquel Lawrence

LearnDialogue

a

Da Learn

+Introduction

n Created a parser

n Developed a parser for data in a database

n Study

n Used data from two studies

n Research Hypothesis

n Students with prior programming experience will have a

relatively better interaction with Snap than students with little prior programming experience

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+Background

n Snap! Visual Programming language

n A free browser-based graphical programming language tool

designed to teach CS concepts to students

n The benefits of pair programming[2]:

n Higher retention rates n Increase in meaningful interaction between students and

instructor

n Increase in student enjoyment of programming 3

+Related Work

n Effects of pair programming performance[1]

n Data collected on 600 students programmed who

individually and in pairs

n Pairs produced better programs n Pairs completed the course at higher rates n Scored significantly higher on programming assignments n Did just as well as individual students on final exam n Several advantages to pair programming, however, not yet

proven if it’s advantageous to student’s performance in the long term (exam scores)[2]

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+Prior Work

n Prior study conducted at North Carolina State University to

model students’ problem-solving modes[3]

n Students worked individually and in pairs

n 14 individuals and 8 pairs assigned randomly n Completed a rock, paper, scissors game in Snap n No prior visual programming experience n Prior java programming experience (nearly 2 full semesters)

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+Implementation

n 6 pairs of undergraduate students from introductory

programming course

n Remote collaboration, students worked in Google Hangouts,

with screen sharing using only text chat for communication

n Given pre/post test and survey and 95 minutes in total to

complete the assignment

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+Snap

n Visual programming language

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Image: Rodríguez, F., Boyer, K.: Discovering Individual and Collaborative Problem-Solving Modes with Hidden Markov

• Models. In: Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), pp.

408-418 (2015)

+Cont’d

n SAX Parser was developed to read activity logs of student’s

actions within Snap interface

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+Parser

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+Results

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100 200 300 400 500 600 700 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0

• No. of Events

Duration (in minutes)

Inexperienced Pairs Experienced Pairs

+Discussion/Conclusion

n Mann-Whitney U-Test

n Using the Mann-Whitney U-Test, there was no significant

difference in the number of actions between conditions

n Activity duration for inexperienced pairs was significantly

higher than for experienced pairs

n Suggests that the experienced pairs had less trouble

handling the interface.

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Inexperienced ¡Pairs ¡ Mean ¡Dura)on ¡ 64.2 ¡

• Std. ¡Dev ¡Dura)on ¡

19.3 ¡ Mean ¡ ¡# ¡of ¡Events ¡ 379.7 ¡

• Std. ¡Dev ¡# ¡of ¡Events ¡

205.6 ¡ Experienced ¡Pairs ¡ Mean ¡Dura)on ¡ 34 ¡

• Std. ¡Dev ¡Dura)on ¡

6.3 ¡ Mean ¡ ¡# ¡of ¡Events ¡ 337.1 ¡

• Std. ¡Dev ¡Dura)on ¡

76 ¡

+Threats

n Technical Difficulties

n Two groups did not finish n Computers crashed 3 times n Slow computer speed

n Difference Study Design

n One study had explicitly textual discourse between

partners

n Takes longer to type than to speak during collaboration n Partners type at different speeds

n Mann Whitney U -Test

n Used for small data sets that are too small to be significant

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+Future Work

n Conduct the study once again without technical difficulties

and with a bigger sample size

n Analyzing the effect of dialogue between the pairs.

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+References

1.

McDowell, C., Werner, L., Bullock, H., Fernald, J.: The effects of pair- programming on performance in an introductory programming course. In: Proceedings of the 33rd ACM Technical Symposium on Computer Science Education (SIGCSE 2002), pp. 38–42 (2002)

2.

Radermacher, A., Gursimran W ., Rummelt, R.,: Improving Student Learning Outcomes with Pair Programming. In: Proceedings of the ninth International conference on Computing education research (ICER '12) , pp. 87-92 (2012)

3.

Rodríguez, F., Boyer, K.: Discovering Individual and Collaborative Problem- Solving Modes with Hidden Markov Models. In: Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), pp. 408-418 (2015)

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+

Questions?

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