Supporting Higher Education to Integrate Learning Analytics (SHEILA)

Research areas 
Data Society
Research team 

The University of Edinburgh - Dragan Gasevic, Jeff Haywood, Sian Bayne, Pete Evans, Yi-Shan Tsai, Jeremy Knox | Brussels Education Services | Open Universiteit Nederland | Tallinn University | Universidad Carlos III de Madrid | European Association for Quality Assurance in Higher Education | Erasmus Student Network


European Commission Erasmus+

01 Jan 201530 Jun 2018

To assist European universities to become more mature users and custodians of digital data about their students as they learn online, the SHEILA Project will build a policy development framework that promotes formative assessment and personalized learning, by taking advantage of direct engagement of stakeholders in the development process. It will run over 2016-18.

The field of learning analytics (LA) with its associated methods of online student data analysis, holds great potential to address the challenges confronting European HEIs. By merging technical methods for data mining and with current educational theory research and practice, LA has provided novel and real-time approaches to assessing critical issues such as student progression and retention, establishment of indicators of 21st century skills acquisition, as well as personalised and adaptive learning. The use of semantic technologies for the development of LA methods has been reported to be especially effective. 

While the use of LA has gained much attention and has been/is being adopted by many higher education institutions (HEI) in Europe and the world, the maturity levels of HEIs in terms of being ‘student data informed’ are only in the early stages. According to recent reports, most HEIs are in the initial phase of LA adoption, i.e. aware of analytics and using some basic reports. The SHEILA Project will help to address this gap.

The project will use participatory action research and the Rapid Outcome Mapping Approach (ROMA), specifically designed for policy making derived from scientific evidence. The outputs will be validated through case studies, using the policy framework to guide the development, implementation, and evaluation of LA policy and strategy in four HEIs in different regions of Europe. The project will use innovative strategies to disseminate and translate the outputs, and to set up a long term learning analytics policy agenda and community among HEIs across Europe.

Find out more about the project on its web site here.

Key contact: Dragan Gasevic.