Writer performance ranges on the NBT Academic Literacy Test: an analysis through a Semantics lens

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Karl Maton argues that Legitimation Code Theory (LCT) not only allows knowledge practices to be seen and analysed; it also brings them into relation with the analysis of students themselves. In other words, it views educational experiences as an outcome of the dispositions brought by actors to a knowledge context, and the nature of the context itself. My dissertation research addressed the question of how LCT can be used to analyse student performance of a higher education applicant cohort on a National Benchmark Test (NBT) Academic Literacy assessment. This was done in order to glean more information that can be used firstly as a predictive tool for future success, and as an identifier of specific areas that reveal student academic under-preparedness. The study also attempted to show how this information might play a role in the development of interventions intended for students identified in this way. I argued that an appropriately designed tool can enable the lecturer to surface additional information from the NBTs that may be of further use after admission and placement, particularly when applied to an aspect of the curriculum of an extended or support programme. I proceeded by analysing the performance patterns of an NBT Academic Literacy test-taker cohort. I focused on the semantic gravity and semantic density ranges of these test-takers' performance, and used this analysis as a tool to gauge the level of performance of the NBT test-taker against what is considered to be the 'legitimate' indicator for success: status and achievement in this domain in a first year classroom. I demonstrated how, by using this tool, the lecturer might be able to determine what information from the NBT AL may be deemed to be of value to complement existing provision of support in this domain