The impact of analytics in Higher Education on academic practice

Many strong claims have been made for Learning Analytics and the potential which it has to transform the education system, which deserve to be treated with caution, particularly as they regard teaching practice.

The introduction of these techniques cannot be understood in isolation from the methods of educational management as they have grown up over the past two centuries. These methods are conditioned by the fact that educational managers are limited in their capability to monitor and act upon the range of states which are taken up by teachers and learners in their learning activities. Strategies for simplification have been developed which classify the range of knowledge as a number of subjects, reduce the subjects to courses, and assign students to cohorts which carry out the same activities. Teachers, meanwhile, deal as best they can with the full variety of learners’ needs in their practice. Over the years, an accommodation has developed between regulatory authorities, management and teaching professionals: educational managers indicate the goals which teachers and learners should work towards, provide a framework for them to act within, and ensure that the results of their activity meet some minimum standards. The rest is left up to the professional skills of teachers and the ethical integrity of both teachers and learners.

This accommodation has been eroded by the efforts of successive governments to increase their control over the education received by both school and higher education students. Learning Analytics radically reduces the effort involved in gathering information on the way in which lecturers deliver the curriculum, and also to automate the work of analysing this information. An alliance of these two trends has the potential to constrain teaching practice, and therefore it is necessary to take a systemic view when assessing the impact of analytics on teaching practice.

Item Info

URL: http://publications.cetis.ac.uk/2012/532
Publication Date: December, 2012
Author(s): Dai Griffiths
Source: Cetis Analytics Series

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