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Moving Towards Individualised Learning Experiences through Data Analytics

BOLTON-KING, Rachel (2016) Moving Towards Individualised Learning Experiences through Data Analytics. In: Learning & Teaching Conference, 7th July 2016, Stoke-on-Trent, Staffordshire. (Unpublished)

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Abstract or description

Understanding the prior learning experiences and background demographics of our students is vital to provide added value during the university experience. SITS stores a wealth of detail about our students, which we can harness to inform our teaching and utilise to support monitoring of student progression.

Analysing data gathered from recent student cohorts, we have been able to map the typical demographic of students on undergraduate Forensic and Crime Science awards. By examining student’s Personal Development Planning (PDP) scores at the end of Level 4 and mapping PDP progression through to Level 6, we can typically predict the final classification awarded to the student on graduation at the end of Level 4. Comparing final degree classifications and student population demographics has enabled us to reflect on our awards at a much deeper level and we have used this intelligence as evidence to inform future teaching practices.

Based on the research conducted, we have identified a new teaching and learning strategy to pilot with new Level 4 students in September 2016. Our proposal will commence during Welcome Week, identifying specific groups of individuals to target bespoke teaching and learning initiatives during the 2016-17 academic year. The aim of this pilot programme is to move towards developing a more individualised learning experience for our students to improve student progression, retention and success.

This oral presentation will therefore provide an insight into a ‘typical FACS student’, highlight the intelligence we have gathered about our awards through data analysis and detail how the Forensic and Crime Science Department aims to incorporate bespoke approaches to learning and teaching from September 2016.

Item Type: Conference or Workshop Item (Other)
Faculty: Previous Faculty of Computing, Engineering and Sciences > Sciences
Depositing User: Rachel BOLTON-KING
Date Deposited: 10 Oct 2016 11:32
Last Modified: 10 Oct 2016 15:35
URI: http://eprints.staffs.ac.uk/id/eprint/2537

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