Theorising work-based learning: analysing interview data with deductive reasoning
Beighton, C. 2020. Theorising work-based learning: analysing interview data with deductive reasoning .
This case study discusses how theory and deductive analysis can be used to better understand work-based learning (WBL). Based in a UK teacher education setting, it discusses a project which examined how novice teachers in English Further Education develop their professional knowledge and how their experiences might help understand WBL more generally. Following a brief overview of the project and its rationale, I turn to research design, explaining how and why a qualitative approach to data collection and a deductive approach to analysis were chosen. To make sure that the results were as critical, informed and applicable as possible, Bourdieu’s concept of “learned ignorance” was used. I show how, as an analytical tool, it exemplifies the use theory in a deductive way. The practicalities of doing the research in these settings are then discussed, focusing on WBL environments and the various issues encountered in bringing the project to fruition. These issues then lead into discussion of the practical lessons learned from completing this kind of project, notably the importance of respecting professional ethics, developing research design in time-limited situations and tackling the process of theorizing and analysis in this situation. The conclusion highlights how a deductive approach to analysis facilitated two conclusions and a coherent set of outcomes. First, the project was able to critically analyse knowledge-making processes which can be difficult to discuss in these settings. Second, it allowed a critical appraisal of the theory used by applying it deductively to a concrete WBL setting.
|Keywords||Work based learning; Deductive reasoning; Qualitative research; Analysis|
File Access Level
|Output status||In press|
|Publication process dates|
|Deposited||09 Sep 2020|
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