The Software Infrastructure Attitude Scale (SIAS): A Questionnaire Instrument for Measuring Professionals' Attitudes Toward Technical and Sociotechnical Infrastructure
🤖 AI Summary
A methodological gap exists in software engineering research regarding reliable instruments for measuring practitioners’ attitudes toward measurement technologies and socio-technical infrastructure. Method: Grounded in infrastructure theory and attitude models, this study formally defines both constructs and develops a two-factor psychometric scale, validated through exploratory and confirmatory factor analyses, HTMT discriminant validity assessment, and the Fornell–Larcker criterion using data from 225 software professionals. Contribution/Results: The scale demonstrates strong reliability and validity (cumulative explained variance = 65%) and exhibits significant correlations with key work-related variables—including job satisfaction and autonomy—thereby addressing a critical methodological void in behavioral software engineering. It advances the systematic adoption of validated psychological scales in empirical software engineering research.
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📝 Abstract
Context: Recent software engineering (SE) research has highlighted the need for sociotechnical research, implying a demand for customized psychometric scales. Objective: We define the concepts of technical and sociotechnical infrastructure in software engineering, and develop and validate a psychometric scale that measures attitudes toward them. Method: Grounded in theories of infrastructure, attitudes, and prior work on psychometric measurement, we defined the target constructs and generated scale items. The scale was administered to 225 software professionals and evaluated using a split sample. We conducted an exploratory factor analysis (EFA) on one half of the sample to uncover the underlying factor structure and performed a confirmatory factor analysis (CFA) on the other half to validate the structure. Further analyses with the whole sample assessed face, criterion-related, and discriminant validity. Results: EFA supported a two-factor structure (technical and sociotechnical infrastructure), accounting for 65% of the total variance with strong loadings. CFA confirmed excellent model fit. Face and content validity were supported by the item content reflecting cognitive, affective, and behavioral components. Both subscales were correlated with job satisfaction, perceived autonomy, and feedback from the job itself, supporting convergent validity. Regression analysis supported criterion-related validity, while the Heterotrait-Monotrait ratio of correlations (HTMT), the Fornell-Larcker criterion, and model comparison all supported discriminant validity. Discussion: The resulting scale is a valid instrument for measuring attitudes toward technical and sociotechnical infrastructure in software engineering research. Our work contributes to ongoing efforts to integrate psychological measurement rigor into empirical and behavioral software engineering research.
Problem
Research questions and friction points this paper is trying to address.
Develops a psychometric scale measuring attitudes toward technical infrastructure in software engineering
Creates an instrument assessing attitudes toward sociotechnical infrastructure in software contexts
Validates a questionnaire for professionals' infrastructure attitudes using factor analysis methods
Innovation
Methods, ideas, or system contributions that make the work stand out.
Developed psychometric scale measuring technical and sociotechnical infrastructure attitudes
Validated scale using exploratory and confirmatory factor analyses on professionals
Assessed validity through job satisfaction correlations and discriminant analysis
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