A method for the analysis of data from online educational research
The intention of this article is to provide an alternative method of data analysis for online learning and VLE related research that is essentially paper based. The article describes the use of a paper-based method for data analysis of online learning type research that involves the collection and collation of electronic (and possibly also paper based) data. This method partly builds on the work of Tyler (2001) and has been used on research projects that investigated online learning as a method for widening participation (Hramiak, 2001a, 2002a) and also on a project that involved the e-professional development of staff at a Further Education (FE) college (Hramiak, 2004). Starting with the raw data sets, a distillation process for the data is described. This is followed by an explanation of how the data sets are examined for common themes.<p></p>\ud \ud One of the major challenges facing the e-learning researcher is how to analyze the electronic data such as discussion board messages and emails, and then how to understand the implications of this analysis for teaching and learning. Such analysis enables researchers to act upon the situation in order to improve it for the learners, as well as for themselves (Lally, 2000). This is particularly challenging when the messages are not only numerous, in the region of hundreds or even thousands, for a specific research study, but also because they can be both very complicated and very lengthy. Although tools for analyzing communication patterns have been developed in other disciplines, for example in applied linguistics, they are generally based upon the analysis of large bodies of text. They also involve relatively complex and cumbersome methods, and they are not designed for action research use in the immediacy of particular teaching and learning situations (Lally) such as those for which this article is aimed at – namely those in which students/participants are constantly messaging in real time synchronously and asynchronously. Moreover, such tools are not intentionally designed to analyze dynamic, ongoing collaborative and social situations where knowledge is actively being co-constructed by the participants (Lally).
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