Collaboration in Pair Programming: Driving and Switching

Plonka, Laura; Segal, Judith; Sharp, Helen; Linden, Janet van der

doi:10.1007/978-3-642-20677-1_4

Cited by 14 publications

(15 citation statements)

References 15 publications

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“…The remaining time they were discussing, coordinating their actions or executing the program. A similar study indicates that professional developers spend only a third of the session time non-driving [12].…”

Section: Interaction Analysismentioning

confidence: 57%

Exploring the effects of collaboration scripts embedded in a distributed pair programming system

Tsompanoudi

Satratzemi

Xinogalos

2013

Proceedings of the 18th ACM Conference on Innovation and Technology in Computer Science Education

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Collaboration scripts provide an integrated framework aimed to foster fruitful collaboration in collaborative learning settings. Since pair programming is also a form of collaborative learning, we explored whether collaboration scripts can improve collaboration in distributed pair programming. For this purpose, we incorporated collaboration scripts in an existing distributed pair programming system. We conducted a pilot study to evaluate the new system by a group of students. Our goal was to examine students' perceptions of computer mediated scripted collaboration and furthermore to evaluate the effectiveness of adaptive role switching in students' participation. The study showed that students' attitude toward distributed pair programming and scripted collaboration was quite positive, however they prefer to distribute tasks by themselves which led half of them not to follow system's suggestions for role distribution.

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Section: Interaction Analysismentioning

confidence: 57%

Exploring the effects of collaboration scripts embedded in a distributed pair programming system

Tsompanoudi

Satratzemi

Xinogalos

2013

Proceedings of the 18th ACM Conference on Innovation and Technology in Computer Science Education

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“…Similar work can be seen in [5]. A study considering possible pair dynamics outside the traditional driver-navigator roles would allow for further understanding of these pair dynamics, and how certain combinations may impact successful collaboration.…”

Section: Limitations and Further Workmentioning

confidence: 72%

Further Evaluations of Industry-Inspired Pair Programming Communication Guidelines with Undergraduate Students

Zarb

Hughes

Richards

2015

Proceedings of the 46th ACM Technical Symposium on Computer Science Education

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“…Each session lasted between one and a half and three and a half hours. In previous studies [29,27] we had analysed the full 37 hours using different analysis methods. Hence, we had excellent knowledge of the data before the Interaction Analysis started.…”

Section: Analysis Stepsmentioning

confidence: 99%

“…In this study, the video data was annotated through previous analyses [29,27] and these annotations were used as content logs for this study.…”

Section: Procedure: Content Logsmentioning

confidence: 99%

Knowledge transfer in pair programming: An in-depth analysis

Plonka

Sharp

Linden

et al. 2015

International Journal of Human-Computer Studies

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Whilst knowledge transfer is one of the most widely-claimed benefits of pair programming, little is known about how knowledge transfer is achieved in this setting. This is particularly pertinent for novice−expert constellations, but knowledge transfer takes place to some degree in all constellations.We ask "what does it take to be a good "expert" and how can a "novice" best learn from a more experienced developer?". An in-depth investigation of video and audio excerpts of professional pair programming sessions using Interaction Analysis reveals: six teaching strategies, ranging from "giving direct instructions" to "subtle hints";; and challenges and benefits for both partners. These strategies are instantiations of some but not all teaching methods promoted in cognitive apprenticeship; novice articulation, reflection and exploration are not seen in the data. The context of pair programming influences the strategies, challenges and benefits, in particular the roles of driver and navigator and agile prioritisation which considers business value rather than educational progression. Utilising these strategies more widely and recognizing the challenges and benefits for both partners will help developers to maximise the benefits from pairing sessions. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 1 Introduction "Two heads are better than one" is a common idiom referring to the advantages of collaborative work. *ManuscriptThe value of collaboration is explicitly encouraged in software development through a practice known as pair programming. Pair programming (PP) is a software development technique where two developers work closely together to solve a development problem [41,1].Several benefits of PP have been claimed including improved understandability and maintainability of code and design [35,37], decreased defect rates [24,18,23,10,25] and knowledge transfer [21,20,23,32,34,35,36,38,40]. This paper focuses on knowledge transfer in PP. This is common when a more experienced developer teaches a less experienced developer, for example, to bring new staff up to speed [3,42]. However, given that developers never have identical knowledge, a certain degree of knowledge transfer would be expected within every PP constellation.Pairing with someone who has a different knowledge level can be problematic [2,7] and developers tend to interact differently in this situation in comparison to pairing with other developers with similar knowledge levels [9,7]. For example, Plonka et al. [29] showed that less knowledgeable developers (novices) can disengage in PP sessions and can sometimes not follow their more knowledgeable partner (expert). These three questions are addressed through a qualitative analysis (using Interaction Analysis [19]) of video recordings of professional developers working together on their day to day t...

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Collaboration in Pair Programming: Driving and Switching

Cited by 14 publications

References 15 publications

Exploring the effects of collaboration scripts embedded in a distributed pair programming system

Exploring the effects of collaboration scripts embedded in a distributed pair programming system

Further Evaluations of Industry-Inspired Pair Programming Communication Guidelines with Undergraduate Students

Knowledge transfer in pair programming: An in-depth analysis

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