Stemming the flow: improving retention for distance learning students

Slade, Sharon and Prinsloo, Paul (2015). Stemming the flow: improving retention for distance learning students. In: EDEN 2015 Annual Conference Proceedings, European Distance and E-Learning Network.

URL: http://www.eden-online.org/system/files/Book%20of%...

Abstract

Though concern about student attrition and failure is not a new phenomenon, higher education institutions (HEIs) have struggled to significantly reduce the revolving door syndrome. Open distance learning higher education is particularly susceptible to high student attrition. Despite a great deal of research into the student journey and factors impacting on likely success, we are not necessarily closer to understanding and being able to mitigate against student attrition. Learning analytics as emerging discipline and practice promises to help penetrate the fog…
This case study describes work undertaken at the Open University in the UK to investigate how a learning analytics approach allows the University to provide timely and appropriate student support in a cost-effective manner. It includes a summary of the establishment of curriculum-based student support teams and a framework which defines more standardised student support informed by both student data and an enhanced knowledge of the curriculum. The primary aim of student support teams is to proactively support students through their study journey and to optimise their chances of reaching their declared study goals.
Higher education institutions (HEIs) are making increasing use of learning analytics to support delivery of timely and relevant student support. The Open University in the UK, like other HEIs, knows a great deal about its students before they start to study and is able to track student behaviours once study has begun. Until recently, the university has not taken full advantage of the additional insight offered by such information. This paper describes the framework of support interventions established for all student support teams and describes the learning analytics approach used to support that framework.

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About

  • Item ORO ID
  • 44537
  • Item Type
  • Conference or Workshop Item
  • ISBN
  • 615-5511-02-0, 978-615-5511-02-8
  • Keywords
  • Learning Analytics; Student Support; Retention; Distance Learning; Curriculum Support
  • Academic Unit or School
  • Faculty of Business and Law (FBL) > Business
    Faculty of Business and Law (FBL)
  • Copyright Holders
  • © 2015 European Distance and E-Learning Network and the Authors
  • Depositing User
  • Sharon Slade

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