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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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Abstract. Learning activity or learning process models represent the basic material elements of any learning event. However, the organizational learning setting requires the consideration of objectives outside the individual, and the transformation of these activities into measurable, efficient behavior. In order to process learning activities with technological tools, such characteristics must be properly modeled. This paper describes a model for such a process-oriented view on learning in organizations, and sketches how that framework could be integrated with IMS Learning Design, a language for the description of pedagogical arrangement of multi-role activities.

A learning object can be considered as a unit of instructional content for which a metadata record describing its characteristics and intended educational usage is provided. Metadata records can be used to develop effective search and location of learning objects, and also to develop automated or semi-automated selection and composition tools. In consequence, the quality of metadata records is a critical point for applications, especially if consistent and standardized software tools are desired. Completeness is one of the essential facets of metadata quality, which can be defined in terms of the metadata elements required for each functionality or usage. The eventual emergence of a global space for learning object-based education requires the creation of learning object repositories providing large collections of contents in a form accessible to standardized software. These repositories are called to play a central role in automated approaches to e-learning, since they provide the required support for learning object access and search facilities, oriented not only to humans but to software agents or systems. In consequence, completeness of metadata records becomes a key requirement for learning object repositories. Nonetheless, metadata creation is a time-consuming and laborious process, and current basic standards for learning object metadata allow for a large degree of flexibility in metadata edition. These two factors combined may eventually result in incomplete and poorly structured metadata. In this paper, the completeness of learning object metadata of samples obtained from the MERLOT and CAREO repositories are analyzed from that viewpoint, using the IEEE LOM standard as a reference framework. The paper concludes with a proposal for the specification of completeness levels as compliancy requirements for learning-related services or processes.Keywords: Learning objects, metadata, learning object evaluation, learning object repositories. Biographical Notes:Miguel A. Sicilia obtained a university degree in Computer Science from the Pontifical University of Salamanca, Madrid, Spain, in 1996 and a Ph.D. degree from the Carlos III University in 1999. From 1997 to 1999 he worked as an assistant professor and later on as a part-time lecturer at the Computer Science Department of the same university. He also worked as a software architect in e-commerce consulting firms. From 2002 to 2003 he worked as a fulltime lecturer at the Carlos III University, after which he joined the University of Alcalá. His research interests are primarily in the areas of adaptive hypermedia, learning technology, and human-computer interaction, with a special focus on the role of uncertainty and imprecision handling techniques in those fields. Starting from 2001, she is associate professor at Computer Science Department of the University of Alcalá and she is a member of the Information System Engineering group of this University. Her research interests mainly focus on topics related to human-computer interaction and knowledge r...