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Contextualizing research evidence through knowledge translation in software engineering
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
2019 (English)In: ACM International Conference Proceeding Series, Association for Computing Machinery , 2019, p. 306-311Conference paper, Published paper (Refereed)
Abstract [en]

Usage of software engineering research in industrial practice is a well-known challenge. Synthesis of knowledge from multiple research studies is needed to provide evidence-based decision-support for industry. The objective of this paper is to present a vision of how a knowledge translation framework may look like in software engineering research, in particular how to translate research evidence into practice by combining contextualized expert opinions with research evidence. We adopted the framework of knowledge translation from health care research, adapted and combined it with a Bayesian synthesis method. The framework provided in this paper includes a description of each step of knowledge translation in software engineering. Knowledge translation using Bayesian synthesis intends to provide a systematic approach towards contextualized, collaborative and consensus-driven application of research results. In conclusion, this paper contributes towards the application of knowledge translation in software engineering through the presented framework. © 2019 Association for Computing Machinery.

Place, publisher, year, edition, pages
Association for Computing Machinery , 2019. p. 306-311
Keywords [en]
Bayesian synthesis, Decision-making, Knowledge translation, Application programs, Decision making, Decision support systems, Industrial research, Bayesian, Evidence- based decisions, Expert opinion, Industrial practices, Multiple research, Research results, Synthesis method, Engineering research
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-17891DOI: 10.1145/3319008.3319358Scopus ID: 2-s2.0-85064754769ISBN: 9781450371452 (print)OAI: oai:DiVA.org:bth-17891DiVA, id: diva2:1316772
Conference
23rd Evaluation and Assessment in Software Engineering Conference, EASE Copenhagen, 14 April 2019 through 17 April 2019
Available from: 2019-05-21 Created: 2019-05-21 Last updated: 2019-05-21Bibliographically approved

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Badampudi, DeepikaWohlin, ClaesGorschek, Tony

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf