The ABLE Project (2015-2018) focused on the challenge of using learning analytics to support student transition into, during and beyond the first year of university. There is a significant body of research taking place in universities across the sector, but that relatively few had fully embedded that learning into institutional support systems. It is important to note that the national contexts profoundly influenced the way that learning analytics was used to support first year students. In the UK, the emphasis was upon supporting first year student retention, in Belgium and the Netherlands, the focus was on study efficiency: ensuring that students were on the right programme. However, in practice the tools were used in similar ways, either by staff members (study advisers or personal tutors) using the learning analytics dashboards with first year students or by students using them independently.ObjectivesThe ABLE Project worked on four key priorities1. The development of learning analytics to support the first year experience2. Identifying strategies for integrating institutional support around the data generated by learning analytics3. Strengthening research into the issues associated with students in transition and integrate these to learning analytics resources4. Providing recommendations and resources for the sectorNumber and profile of participating organisationsThere are three partners:Nottingham Trent University (NTU) is the project lead. During the lifecycle of project NTU has won the following UK awards THE University of the Year, Times/ Sunday Times Modern University of the Year (in which the Dashboard was cited extensively), TEF gold for teaching quality and the Queen’s Anniversary award for Research. KU Leuven (KUL) is a general large research-intensive university and also the oldest and highest ranked in Flanders, Belgium, ranked 14 in the 2018 THE European ranking.University of Leiden (UL) is the oldest university in the Netherlands, it has a significant research interest hosting over 40 national and international research institutes.Description of main activities undertakenThe project team produced 20 intellectual outputs. These can be grouped into the following:- Reports into the realities of transition into HE and learning analytics- Case studies into our institutional experiences using learning analytics with first year students - Workshops, papers and online resources to engage peers across the sector- Open source learning analytics resource for the sector to download and use- Recommendations for the sector about using learning analytics to support the transition processResults and impact attainedThe objectives of the ABLE project were met during the project lifespan. Due to the initial set-up of the project, the majority of results can be found in the range of written outputs of the project, hosted on the project website: www.ABLEproject.eu. We would direct the interested reader to Output O17: Summarizing report on learning analytics for the transition from secondary to higher education, for further details. This output contains a model developed during the ABLE project to help those considering implementing learning analytics understand key considerations for effectively embedding the tool into institutional practices.In the project bid, we sought different types of impact for different stakeholders: students, participating organisations, external organisations, and local and national policy makers. The impact varied from providing relevant tools and associated resources/advice for informed usage at an institutional level to awareness raising and best-practice sharing on a wider scale. The project team was able to realise this impact by completing the planned outputs and by disseminated widely through a mix of internal events, local workshops, conferences and digital media (Twitter, online blogs). Perhaps even more so than originally envisaged, the project team managed to secure platforms for disseminating results to a range of high profile individuals and organisations.If relevant, longer-term benefitsThe project has significantly contributed to the development of learning analytics at the partner institutions, with each institution committing to continue with learning analytics after the end of the project. The participating institutions have gained a far greater understanding of the problems associated with embedding learning analytics, the learnings from which we believe will be transferrable across the implementation of other initiatives. The team has attempted to convey these learnings within the written outputs so other institutions can gain long term benefits from the findings.