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Erschienen in: Empirical Software Engineering 2/2023

01.03.2023

How programmers find online learning resources

verfasst von: Deeksha M. Arya, Jin L. C. Guo, Martin P. Robillard

Erschienen in: Empirical Software Engineering | Ausgabe 2/2023

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Abstract

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.

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Metadaten
Titel
How programmers find online learning resources
verfasst von
Deeksha M. Arya
Jin L. C. Guo
Martin P. Robillard
Publikationsdatum
01.03.2023
Verlag
Springer US
Erschienen in
Empirical Software Engineering / Ausgabe 2/2023
Print ISSN: 1382-3256
Elektronische ISSN: 1573-7616
DOI
https://doi.org/10.1007/s10664-022-10246-y

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