Doctoral Consortium

Chairs:

  • Oleksandra Poquet, Universite Paris Cite, France
  • Jelena Jovanović, University of Belgrade, Serbia
  • Christopher Brooks, University of Michigan, USA
  • Dragan Gašević, Monash University, AUS

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 learning analytics, the learning sciences, data sciences, and human-centered computing.

The event will bring together doctoral 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 opportunities to present, discuss, and receive feedback on their research in an interdisciplinary and supportive atmosphere. They will also be exposed to a wide range of different analytic approaches, methods, and tools for acquiring data about learners and their learning activities.

Objectives

The specific objectives of the Doctoral Consortium are to:

  • Provide a setting for mutual feedback on participants’ current research and advice 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 data, 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 conference experience of the participating students  by connecting the participants to other LAK attendees
  • Develop the next generation of learning analytics researchers and active members of SoLAR

The intention of this Doctoral Consortium is to support and inspire students who are currently enrolled in a formal doctoral programme, during their ongoing research efforts. Ideally, participants will have developed and (in some countries) defended a proposal, but their work will be at a sufficiently early stage that they can still make adjustments based on the feedback received at the consortium. They should neither have completed their doctorate, nor officially submitted their thesis prior to the Doctoral Consortium.

Proposal Format & Submission Process

To apply to the Doctoral Consortium, student applicants should submit the following documents as one single PDF file to the LAK23 EasyChair Submission System. Please ignore the EasyChair instruction about anonymisation, DC submissions should have identifying details.

  1. A summary of your research that is up to six pages long (including all tables, figures and references, except 1 additional page for appendices), using the LAK companion proceedings template. This document should include all the following elements:
    • A 150-word abstract
    • Brief background to the project and identification of the significant problem(s) in the field that it addresses
    • Goals of the research and a clear formulation of the research question(s)
    • An outline of the current knowledge of the problem domain and state of existing solutions
    • A discussion of how the doctoral project’s suggested solution is different, new, or better than existing approaches to the problem
    • A sketch of the research methodology and identification of core methods/techniques, including reference to ethical considerations
    • Current status of the work and results achieved so far (e.g literature review, submitted or accepted papers, prototypes designed or built, experiments carried out, etc.)
  2. A supplementary page with additional information addressed to the Doctoral Consortium committee to help us help you. This should include:
    • 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 would be willing to drop into the consortium for your session, visit your poster, or just meet up at LAK or virtually (if they happen not to attend LAK23 in person).
  3. A letter of recommendation from your supervisor/advisor with an assessment of the current status of your work, a brief summary of how attending the Doctoral Consortium is likely to benefit your work, and an expected date for dissertation completion.

Review Process

Doctoral Consortium co-chairs will review applications, with the help of additional Program Committee members where necessary. Participants will be selected on the basis of:

  • 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
  • Support of the dissertation advisor for participation and its potential benefit.

Students should not have participated in a previous LAK Doctoral Consortium. Our aim is to bring together a diverse cohort of emerging scholars of learning analytics.

Schedule

The Doctoral Consortium will take place during the pre-conference, exact date announced at a later stage, falling on March 13th or March 14th, 2023. As in previous years, the format interleaves research presentations and small-group discussions, so students have opportunities for in-depth conversations about their work. A plenary discussion on career development concludes the day. All participants are also encouraged to join the Doctoral Consortium dinner (if they are attending LAK23 in person) with the mentor team to continue the conversation. Participants’ papers and posters are published in the LAK Companion Proceedings. 

To help disseminate their work to all conference attendees, students will also present their work in the main LAK Poster session, and will be entered for the LAK Best Poster Award.

Financial Support

As in previous years, for this DC event we will provide financial support to cover costs related to the LAK conference registration and, if a face to face event is possible, then also accommodation for two nights, and a potential contribution towards other travel-related expenses. Some funds are already confirmed for SoLAR student members to cover a flat amount of their expenses.

Society for Learning Analytics Research (SoLAR)