Background


Compared to other platforms such as Coursera and EdX, FutureLearn is a relatively new player in the MOOC arena and received limited coverage in the Learning Analytics and Educational Data Mining research.

This  is the first workshop of its kind providing an opportunity to showcase current research and evaluation of learning with the FutureLearn MOOC platform on an international stage.

Contributions are invited focusing on processes, methods and tools used to present, analyse, evaluate and use the data offered by FutureLearn. More details in the submission page.

Similar to the main LAK conference we encourage submissions from both researchers and practitioners. We also highly welcome technical submissions in order to share code and analytics tools to advance research and evaluation of learning in FL Moocs.

The case studies will be used to demonstrate how data made available could be used to inform pedagogical design and to explore a range of questions about learning and teaching with the platform.  For those more technically-versed we intend to provide a useful forum to exchange solutions and accelerate the analytical process by sharing details about the type and nature of technology stack used to analyse and present data at different institutions.

Focusing on a ‘hands-on’ approach, the workshop will provide opportunities to both technical and less technical people to leverage on what is offered and learn from others.

It is expected that participants will share not only their findings, but also some of the code, so that the work started with this workshop will continue beyond the conference. The workshop will also be an opportunity to share issues, problems and to identify what data is missing and what would be useful to have.

Who is this workshop for?

Those who wish to understand the possibilities offered by the data already offered by FutureLearn, discuss and share innovations, impact on education, and explore future directions in the application of learning analytics (LA) to Massive Open Online Courses (MOOC) design and development as well as learning design with MOOCs. Likely interested participants:
  • Educators/Teachers and researchers
  • Technologists and educational developers
  • Learning scientists and Data scientists/analysts
  • Academic managers
  • Entrepreneurs
  •  and anyone else interested in MOOCs (focusing on FutureLearn in this workshop) and LA

Outcomes for attending participants

All contributions (short 5-pages, long 10-pages papers; see the Submission section for details) accepted for this workshop will be included in a CEUR Workshop Proceedings (http://ceur-ws.org/). Please check the submission section for more information about the process and deadlines.

Participants will be able to:
  • Get an idea of the state of the art of work with FutureLearn data across institutions, disciplines and roles;
  • Discuss cases, issues and problems, sharing outcomes (both successes and failures in using the data offered);
  • Reflect on the impact of the work presented on learning design and the learners’ experiences;
  • Enable the development of common tools that educators and researchers may be able to re-use in their own contexts;
  • Connect relevant people with one another, in the broad area of data and LA applied to MOOCs and FutureLearn in particular.
  • Explore opportunities of sharing results for cross-course analysis and benchmarking
The inclusion of the FutureLearn data team demonstrates their commitment to support partners, collaborate and co-develop effective solutions to improve research opportunities, learning design and ultimately the learners’ experience.