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Experiences of studying attention through EEG in the context of review tasks
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Syddansk Universitet, DEN.
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. 313-318Conference paper, Published paper (Refereed)
Abstract [en]

Context: Electroencephalograms (EEG) have been used in a few cases in the context of software engineering (SE). EEGs allow capturing emotions and cognitive functioning. Such human factors have already shown to be important to understand software engineering tasks. Therefore, it is essential to gain experience in the community to utilize EEG as a research tool. Objective: To report experiences of using EEG in the context of a software engineering education (review of master theses proposals). We provide our reflections and lessons learned of (1) how to plan an EEG study, (2) how to conduct and execute (e.g., tools), (3) how to analyze. Method: We carried out an experiment using an EEG headset to measure the participants’ attention rate. The experiment task includes reviewing three master thesis project plans. Results: We describe how we evolved our understanding of experimentation practices to collect and analyze psychological and cognitive data. We also provide a set of lessons learned regarding the application of EEG technology for research. Conclusions: We believe that that EEG could benefit software engineering research to collect cognitive information under certain conditions. The lessons learned reported here should be used as inputs for future experiments in software engineering, where human aspects are of interest. © 2019 Association for Computing Machinery.

Place, publisher, year, edition, pages
Association for Computing Machinery , 2019. p. 313-318
Keywords [en]
Attention, Electroencephalogram, Experiment, Human subjects, Bioelectric phenomena, Electroencephalography, Engineering research, Experiments, Cognitive information, Electro-encephalogram (EEG), Human aspects, Project plans, Research tools, Software engineering
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-17890DOI: 10.1145/3319008.3319357Scopus ID: 2-s2.0-85064765914ISBN: 9781450371452 (print)OAI: oai:DiVA.org:bth-17890DiVA, id: diva2:1316771
Conference
23rd Evaluation and Assessment in Software Engineering Conference, EASE Copenhagen, 14 April 2019 through 17 April
Available from: 2019-05-21 Created: 2019-05-21 Last updated: 2019-05-21Bibliographically approved

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Molléri, Jefferson SeideFotrousi, FarnazPetersen, Kai

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CiteExportLink to record
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  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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  • Other locale
More languages
Output format
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