The persistence and transfer of learning in industrial settings
Management Science
Coordination in software development
Communications of the ACM
An empirical study of global software development: distance and speed
ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
On the Job Learning in the Software Industry: Corporate Culture and the Acquisition of Knowledge
On the Job Learning in the Software Industry: Corporate Culture and the Acquisition of Knowledge
Two case studies of open source software development: Apache and Mozilla
ACM Transactions on Software Engineering and Methodology (TOSEM)
Recombinant Uncertainty in Technological Search
Management Science
The Promise of Research on Open Source Software
Management Science
Learning from Experience in Software Development: A Multilevel Analysis
Management Science
ACM Transactions on Software Engineering and Methodology (TOSEM)
Firms as Incubators of Open-Source Software
Information Systems Research
Information Systems Research
Developer Heterogeneity and Formation of Communication Networks in Open Source Software Projects
Journal of Management Information Systems
Information Systems Research
Developer Heterogeneity and Formation of Communication Networks in Open Source Software Projects
Journal of Management Information Systems
Train and retain: the impact of mentoring on the retention of FLOSS developers
Proceedings of the 50th annual conference on Computers and People Research
Developer Heterogeneity and Formation of Communication Networks in Open Source Software Projects
Journal of Management Information Systems
A hidden Markov model for collaborative filtering
MIS Quarterly
Proceedings of the 2013 annual conference on Computers and people research
Single machine scheduling with autonomous learning and induced learning
Computers and Industrial Engineering
Network ties and the success of open source software development
The Journal of Strategic Information Systems
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This study develops a stochastic model to capture developer learning dynamics in open source software projects (OSS). A hidden Markov model (HMM) is proposed that allows us to investigate (1) the extent to which individuals learn from their own experience and from interactions with peers, (2) whether an individual's ability to learn from these activities varies as she evolves/learns over time, and (3) to what extent individual learning persists over time. We calibrate the model based on six years of detailed data collected from 251 developers working on 25 OSS projects hosted at Sourceforge. Using the HMM, three latent learning states (high, medium, and low) are identified, and the marginal impact of learning activities on moving the developer between these states is estimated. Our findings reveal different patterns of learning in different learning states. Learning from peers appears to be the most important source of learning for developers across the three states. Developers in the medium learning state benefit the most through discussions that they initiate. On the other hand, developers in the low and the high states benefit the most by participating in discussions started by others. While in the low state, developers depend entirely upon their peers to learn, whereas in the medium or high state, they can also draw upon their own experiences. Explanations for these varying impacts of learning activities on the transitions of developers between the three learning states are provided. The HMM is shown to outperform the classical learning curve model. The HMM modeling of this study contributes to the development of a theoretically grounded understanding of learning behavior of individuals. Such a theory and associated findings have important managerial and operational implications for devising interventions to promote learning in a variety of settings.