Bay Area Learning Analytics (BayLAN) Conference Call for Proposals

Bay Area Learning Analytics (BayLAN) Conference Call for Proposals


The 2018 Bay Area Learning Analytics Conference is February 24 at the University of California, Berkeley. BayLAN brings together researchers from both industry and academia who are using data and technology to improve education. 

BayLAN is soliciting abstract submissions reporting on research in the broadly defined topic of learning analytics. This includes technical work that applies data science or other quantitative methods to improve education, as well as interventions, methodologies, tools or technology that are intended to improve learning outcomes.

Abstracts will be assessed by the program committee on the relevance to the field of Learning Analytics. BayLAN aims to provide a platform for discussion on how to gain insight of best educational practices, and this includes interventions that are well designed, but showed no positive effect on learning.  Accepted work will be presented as one of:

  • Long research talk.  30 minutes (including Q&A) - Must include a clearly explained substantial conceptual, technical or empirical contribution. We welcome thoughts and findings that stem from learning analytics project implementations.
  • Short research talk.  15 minutes (including Q&A) - Can address on-going work, which may include a briefly described theoretical underpinning, an initial proposal or rationale for a technical solution, and preliminary results in an experience.
  • Lightning talk.   5-minute talk

Thought-provoking work that has not yet reached a level of completion that would warrant a longer presentation is also welcome.

  • Demo - A live demonstration is a great opportunity to communicate ideas and concepts in a powerful way that a regular presentation cannot. Show aspects of learning analytics in an interactive hands-on form. Feel free to include a link to a video on your abstract.
  • Poster - Research in progress, ideas for projects, etc.

Suggested Topics

  • Theoretical topics: cognitive science models about education, data science methods applied to learning, novel theories about learning
  • Lessons learned: After going through the learning analytics implementation process, share insights that have surfaced that affect the completion of the project
  • Innovative new tools/techniques: Share newly developed tools or approaches to learning analytics that have been implemented at an institution.
  • Application of standards: A project making use of data/analytics standards and illustrating the benefits of such an approach.
  • Collaboration and sharing: How are groups of institutions/practitioners partnering to solve shared problems in the learning analytics space?

More information and instructions for submission:

Submission deadline: December 15, 2017




Friday, December 15, 2017