Doctoral consortium



Time: April 26, 2016 8:30 AM – 4:30 PM
Location: Bonnar room, St Leonard’s Hall


  1. Angelique Kritzinger, University of Pretoria, South Africa
  2. Yuan “Elle” Wang, Columbia University, United States of America
  3. Korinn Ostrow, Worcester Polytechnic Institute, United States of America
  4. Héctor Pijeira-Díaz, University of Oulu, Finland
  5. Garron Hillaire, The Open University, United Kingdom
  6. Catherine Spann, University of Texas at Arlington, United States of America
  7. Michael Brown, University of Michigan, United States of America
  8. Jenna Mittelmeier, The Open University, United Kingdom
  9. Caitlin Holman, University of Michigan, United States of America
  10. Hazel Jones, University of Southern Queensland, Australia


  • Submission deadline: Close of 8 November, 2015 (HAST)
    Please email submissions to Simon Buckingham Shum to “Simon dot BuckinghamShum atsign”
  • Notification of acceptance:  30 November, 2015
  • Doctoral Consortium: 26th April, 2016


The LAK Doctoral Consortium is a one-day workshop to support emerging scholars in learning analytics by helping them develop productive approaches to studying the intersection of theory, data, and practice in the Learning Sciences, Data Sciences, and Human-Centered Computing.

The event will bring together Ph.D. students from a variety of disciplines working on topics related to Learning Analytics who are grappling with their dissertation research. The Consortium chairs serve as a mentor panel to provide feedback. Doctoral Consortium participants will be given the opportunity to present, discuss, and receive feedback on their research in an interdisciplinary and supportive atmosphere, as well as to be exposed to a wide range of different analytic approaches, methods, and tools for acquiring data about learners and their learning activities.


The specific objectives of the Doctoral Consortium are to:

  • Provide a setting for mutual feedback on participants’ current research and guidance on future research directions from a mentor panel
  • Create a forum for engaging in dialogue aimed at building capacity in the field with respect to current issues in learning analytics ranging from methods of gathering analytics, interpreting analytics with respect to learning issues, considering ethical issues, relaying the meaning of analytics to impact teaching and learning, etc.
  • Develop a supportive, multidisciplinary community of learning analytics scholars
  • Foster a spirit of collaborative research across countries, institutions and disciplinary background
  • Enhance participating students’ conference experience by connecting participants to other LAK delegates

The intention of this doctoral consortium is to support and inspire Ph.D. students during their ongoing research efforts. Ideally, participants will have developed and perhaps defended a proposal, but be early enough in carrying out the project that adjustments based on feedback received at the consortium can still be made (they should not have completed their degree, nor officially submitted their thesis prior to the doctoral consortium).

We are allocating places to students who have not yet participated in a LAK Doctoral Consortium.


Submissions are now closed.
See doctoral consortium submission guidelines

Please email submissions to Simon Buckingham Shum: “Simon dot BuckinghamShum atsign”

To apply to the Doctoral Consortium, student applicants are requested to submit the following documents:

1) A 5 page summary of your research, in the LAK 16 ACM conference format and written for the LAK community, that includes the following:

  • A 150 word abstract
  • Brief background of the project and identification of the significant problem(s) in the field the project addresses
  • Goals of the research and a clear formulation of the research question
  • An outline of the current knowledge of the problem domain and state of existing solutions
  • A discussion of how the Ph.D. project’s suggested solution is different, new, or better as compared to existing approaches to the problem
  • A sketch of the research methodology and identification of core methods/techniques used
  • Current status of the work and results achieved so far
  • Note that the page limit includes all tables, figures, references etc.

2) A supplementary page with additional information addressed to the DC committee to help us help you:

  • A statement of the particular issues/problems that you want to discuss, and/or types of feedback that might be particularly useful
  • Names of LAK researchers from whom you would like to receive feedback on your work. We are happy to contact them and ask if they can (e.g.) drop into the consortium for your session, visit your poster, or just meet up at LAK.

3) A letter of recommendation from your dissertation supervisor/advisor with an assessment of the current status of your work, how attending the doctoral consortium might be beneficial in your remaining process, and an expected date for dissertation completion.

Submission steps

  • Prepare doctoral consortium submission in accordance with ACM Proceedings format.
  • Combine the summary, the issues document, and the letter of recommendation together in a single file (ideally a single PDF file, else a Zip archive)
  • Email submissions to Simon Buckingham Shum to “Simon dot BuckinghamShum atsign”

Reviewing process

Proposals will be reviewed by the Doctoral Consortium Co-Chairs and additional Program Committee members as needed. Participants will be selected on the basis of the academic quality of their proposal, relevance and potential contribution to the Learning Analytics field, potential for the student and the dissertation work to benefit from participation in the doctoral consortium, and support of the dissertation advisor for this participation and potential benefit. The aggregate diversity of the cohort will also be considered, so that we have a rich set of examples of different kinds of learning analytics approaches.


The Doctoral Consortium will take place the day before the main conference. As you will see from previous years, the format interleaves research presentations and small group discussion where students have the chance to answer questions about their work in more depth.

A plenary discussion on career-development concludes the day, and has proven to be of great value at previous consortia.

Everyone is encouraged to join the Doctoral Consortium dinner to continue the conversation.

To help disseminate your work to all conference delegates, students will also present their work in the main LAK Poster session, and will be entered for the LAK Best Poster Award. If you are accepted to the DC, you will submit your poster in advance to us for comments.


We thank the Society for Learning Analytics Research (SoLAR) for providing financial support for this event, covering LAK conference registration, 2 nights’ hotel, and a contribution to some if not all travel costs.