The size of software project teams has been considered to be a driver of project productivity. Although there is a large literature on this, new publicly available software repositories allow us to empirically perform further research. In this paper we analyse the relationships between productivity, team size and other project variables using the International Software Benchmarking Standards Group (ISBSG) repository. To do so, we apply statistical and machine learning approaches to a preprocessed subset of the ISBSG repository to facilitate the study. The results show some expected correlations between productivity, effort and time as well as corroborating some other beliefs concerning team size and productivity. In addition, this study concludes that in order to apply statistical or data mining techniques to these type of repositories extensive preprocessing of the data needs to be performed due to ambiguities, wrongly recorded values, missing values, unbalanced datasets, etc. Such preprocessing is a difficult and error prone activity that would need further guidance and information that is not always provided in the repository.
Abstract:The Knowledge Society is the new context of our living and working. Towards this milestone, the International Journal of Knowledge and Learning reveals a scientific debate where academics, practitioners, researchers, policy makers, as well as government bodies, industry and nonprofit organisations provide their understanding for the integrated character of knowledge and learning. In this position document, we comment on the nature of Knowledge Society and we develop a 'Roadmap' for our future discussions and contributions.
Recent work has reintroduced ontology as a research topic in learning theories, as a mean to make explicit the differences and links between existing approaches to the design of learning programs. In the context of technology-supported information systems, ontologies can be represented in machine-understandable form to serve as a basis for automation and assessment. The notion of change is in some form part of any ontology of learning, but the interpretations attributed to the term differ between them both in scope and characterization. Since change is central to the evolving behaviour of learning organizations, it is worth the effort of specifying it, especially for the sake of objective measurement and automation. This paper describes ontological structures for generic constructivist and socio-cultural learning frameworks, stating the differences in their overall concepts of change, and their implications for practice and assessment. The ontological definitions provided are intended to motivate further work in more specific approaches for learning technology-supported experiences.
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