Abstract
This chapter presents the combined results and over-arching conclusions of a two-phase project to assess a pilot distributed e-learning repository for computer-based assessment resources. This investigation takes place within the larger concerns of communities of practice, such as learners interacting with computer-based assessments or the tutors delivering courses or developing themselves as professionals. On the one hand, the online repository not only offers easy ac-cess to online quality materials, but communities of learners may overlap and in-teract through a distributed repository, using such collaborative web-technologies for lifelong learning, particularly as their size and content expand into large scale digital libraries. On the other hand, the online repository enables tutors to share knowledge about the courses and could well serve to create a virtual network among tutors for sharing knowledge and views related to the teaching activity. The online repository presented in this chapter has been evaluated in with real us-ers in two phases. The first phase investigated direct users perceptions of the re-pository and its usability and pedagogical effectiveness with a toolkit of six ex-perimental methods for triangulation. The second phase consisted of interviews with senior staff involved in educational management roles to assess the wider or-ganisational perspective on the acceptability of such a repository. The results of this study showed the benefits of using the e-learning distributed repository to support learning processes of a community of learners and the importance of eva-luating the online repository with real learners in order to achieve its organiza tional acceptability.
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Bessis, N., Norrington, P., Xhafa, F., Venturi, G. (2011). User-Centred Evaluation and Organisational Acceptability of a Distributed Repository to Support Communities of Learners. In: Daradoumis, T., Caballé, S., Juan, A.A., Xhafa, F. (eds) Technology-Enhanced Systems and Tools for Collaborative Learning Scaffolding. Studies in Computational Intelligence, vol 350. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19814-4_1
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