Exploring school students’ online interactions within a science knowledge-building community

Abstract

A considerable quantity of research into online learning communities has been conducted on the assumption that the entire meaning of online interactions can be captured by the logfiles of online dialogue generated automatically by the computer. Recent work has highlighted the inadequacy of this approach, pointing out that the richness of human interactions, even when computer-mediated, makes them not susceptible to simple textual representation. This work strongly suggests that the use of more naturalistic approaches are likely to provide a deeper picture of the research setting, leading ultimately to a fuller understanding. Although the use of naturalistic methods may offer advantages in terms of the depth of description, this may be at the expense of an ability to generalise from the findings so as to be able to “search for universal laws which explain and govern the reality being observed” (Cohen & Manion, 1989:8); the adoption of a multi-method approach to data collection and analysis may go some way towards addressing these concerns.
This paper describes the methodological approach adopted in the analysis of online data gathered during a study conducted over 12 months with nearly 150 UK school students aged 13-14. In this study networked computers were used to provide students with a Computer Supported Collaborative Learning (CSCL) environment in which to engage in knowledge-building as they undertook practical science investigations as part of their school work.

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