Socio-Technical Grounded Theory for Software Engineering

Grounded Theory (GT), a sociological research method designed to study social phenomena, is increasingly being used to investigate the human and social aspects of software engineering (SE). However, being written by and for sociologists, GT is often challenging for a majority of SE researchers to un...

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Bibliographic Details
Published in:IEEE transactions on software engineering Vol. 48; no. 10; pp. 3808 - 3832
Main Author: Hoda, Rashina
Format: Journal Article
Language:English
Published: New York IEEE 01.10.2022
IEEE Computer Society
Subjects:
Artificial intelligence
data analysis
Data collection
Digitization
Encoding
evaluation
Grounded theory
Guidelines
Information systems
New technology
qualitative research
research method
Research methodology
Social factors
Socio-technical grounded theory
Sociology
Software engineering
STGT
Systematics
theory
theory development
ISSN:0098-5589, 1939-3520
Online Access:Get full text
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Summary:Grounded Theory (GT), a sociological research method designed to study social phenomena, is increasingly being used to investigate the human and social aspects of software engineering (SE). However, being written by and for sociologists, GT is often challenging for a majority of SE researchers to understand and apply. Additionally, SE researchers attempting ad hoc adaptations of traditional GT guidelines for modern socio-technical (ST) contexts often struggle in the absence of clear and relevant guidelines to do so, resulting in poor quality studies. To overcome these research community challenges and leverage modern research opportunities, this paper presents Socio-Technical Grounded Theory (STGT) designed to ease application and achieve quality outcomes. It defines what exactly is meant by an ST research context and presents the STGT guidelines that expand GT's philosophical foundations, provide increased clarity and flexibility in its methodological steps and procedures, define possible scope and contexts of application, encourage frequent reporting of a variety of interim, preliminary, and mature outcomes, and introduce nuanced evaluation guidelines for different outcomes. It is hoped that the SE research community and related ST disciplines such as computer science, data science, artificial intelligence, information systems, human computer/robot/AI interaction, human-centered emerging technologies (and increasingly other disciplines being transformed by rapid digitalisation and AI-based augmentation), will benefit from applying STGT to conduct quality research studies and systematically produce rich findings and mature theories with confidence.
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ISSN:0098-5589
1939-3520
DOI:10.1109/TSE.2021.3106280