Knowledge transfer in pair programming: an in-depth analysis
- Submitting institution
-
The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1452753
- Type
- D - Journal article
- DOI
-
10.1016/j.ijhcs.2014.09.001
- Title of journal
- International Journal of Human-Computer Studies
- Article number
- -
- First page
- 66
- Volume
- 73
- Issue
- 1
- ISSN
- 1071-5819
- Open access status
- Out of scope for open access requirements
- Month of publication
- September
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 25
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Pair programming has been widely-used in industry since 2000, but its use is controversial. One recognised advantage is knowledge transfer between developers, but most studies of this phenomenon focus on student data rather than industrial practice. This paper reports the first systematic, in-depth analysis of knowledge transfer between expert-novice practitioner pairs while performing their normal tasks in an industrial setting. It uses Interaction Analysis, a rigorous interdisciplinary technique rarely used in empirical software engineering, to extract practitioners’ teaching strategies. The findings have been translated into guidelines for practice, and extended by academics in people analytics, collaborative working and knowledge sharing.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -