SHEILA policy framework: Informing institutional strategies and policy processes of learning analytics

Yi-Shan Tsai, Pedro Manuel Moreno-Marcos, Kairit Tammets, Kaire Kollom, Dragan Gašević

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

15 Citations (Scopus)


This paper introduces a learning analytics policy development framework developed by a cross-European research project team – SHEILA (Supporting Higher Education to Integrate Learning Analytics), based on interviews with 78 senior managers from 51 European higher education institutions across 16 countries. The framework was developed using the RAPID Outcome Mapping Approach (ROMA), which is designed to develop effective strategies and evidence-based policy in complex environments. This paper presents three case studies to illustrate the development process of the SHEILA policy framework, which can be used to inform strategic planning and policy processes in real world environments, particularly for large-scale implementation in higher education contexts.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Learning Analytics & Knowledge (LAK'18)
EditorsSimon Buckingham Shum, Rebecca Ferguson, Agathe Merceron, Xavier Ochoa
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages10
ISBN (Print)9781450364003
Publication statusPublished - 7 Mar 2018
EventInternational Learning Analytics & Knowledge Conference 2018 - SMC Conference & Function Centre, Sydney, Australia
Duration: 5 Mar 20189 Mar 2018
Conference number: 8th (Conference website) (Proceedings)


ConferenceInternational Learning Analytics & Knowledge Conference 2018
Abbreviated titleLAK 2018
Internet address


  • Higher education
  • Learning analytics
  • Policy
  • ROMA model
  • Strategy

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