How programmers find online learning resources

• Published in: Empirical software engineering : an international journal Vol. 28; no. 2; p. 23
• Main Authors: Arya, Deeksha M., Guo, Jin L. C., Robillard, Martin P.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-03-2023; Springer Nature B.V
• Subjects: Compilers; Computer Science; Distance learning; Internet resources; Interpreters; New technology; Programmers; Programming Languages; Quantitative analysis; Questions; Software Engineering/Programming and Operating Systems; Online learning resources; Information seeking; Software documentation; User study; Diary study; Qualitative analysis; Quantitative analysis
• ISSN: 1382-3256; 1573-7616
• DOI: 10.1007/s10664-022-10246-y

When learning a new technology, programmers often have to sift through multiple online resources to find information that addresses their questions. Prior work has reported that information seekers use a number of different strategies, including following
scents
, or indicators, to locate appropriate resources. We present a qualitative and quantitative investigation of how programmers learning a new technology employ these strategies to navigate between online resources and evaluate the pertinence of these resources. We performed a diary and interview study with ten programmers learning a new technology, to study how users navigate from the question they have to the resource that satisfies this need. Based on our observations, we propose a resource-seeking model that represents the online resource seeking behaviour of programmers when learning a new technology. The model is comprised of six components that can be divided into two groups: Need-oriented components, i.e. Questions, Preferences, and Beliefs, and Resource-oriented components, i.e. Resources, Cues, and Impression Factors. We identified nine relations between these components and studied how the components are associated. We report on the characteristics of the components and the relationships between them, and discuss the importance of search customization and other implications of our observations for resource creators and search tools.