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Using Assessment Submission Data to Provide Timely and Contextualised Academic Support

Seb Dianati, Greg Collings

Journal of academic language and learning(2020)

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摘要
While it is well accepted that integrating academic skills into the curricula is best practice, in reality it is not always accepted by institutions. Such integration involves both contextualisation and appropriate timing. This presents real issues for adjunct academic language and learning centres that are centralised, rather than part of a specific faculty or course. To some degree, the issues arising from this disjoint can be minimised by the use of university-wide submission data indicating when students are required to submit their assessments. The overall objective of this paper was to identify how submission data could be used to contextualise and embed academic support services and improve the availability of those services during peak times. Specifically, it used a mixed methods approach to: a) investigate how assessment submission data could be employed to provide better timed and contextualised workshops; and b) how that data could be applied to predict the demand on an academic drop-in centre. The results of the study were twofold: first, that assessment submission data can be used to inform when and how contextualised academic support should be provided. Secondly, that assessment submission data can be used to inform when students require academic support services, and consequently staff those services appropriately.
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关键词
Temporal Learning Analytics,Assessment-Data,Embedded Academic Support,Drop-in centre,timely support,contextualised academic workshops
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