Call for Participation

The 8th International Conference on
Learning Analytics & Knowledge

Towards User-Centred Analytics

5-9 March 2018, Sydney, Australia | #LAK18

The International Conference on Learning Analytics & Knowledge moves to the southern hemisphere for the first time, convening in the centre of historic, vibrant Sydney. LAK18 is organised by the Society for Learning Analytics Research (SoLAR) and is hosted by The University of Sydney, one of Australia’s leading research universities.

We extend invitations to researchers, practitioners, leaders, administrators, government and industry professionals interested in the field of learning analytics and related disciplines. LAK provides a forum to address critical issues and challenges confronting the education sector today, by harnessing the power of data science in combination with learner-centred design.

An important feature of the LAK community that attracts diverse delegates is our interest in the human factors in learning analytics systems. As learning analytics tools move out of the lab into the real world, their success or failure must be judged not only on technical criteria, but also by their adoption and effectiveness in schools, universities and workplaces. Often this is where the gulf between hype and reality becomes apparent. The complexities of embedding innovative technology in authentic contexts open a range of critical challenges for the field.

While LAK has always encouraged contributions dealing with issues related to adoption, LAK18 will place particular emphasis on how various stakeholders can, or must, be engaged in the design, deployment and assessment of learning analytics if they are to be successful and sustainable. We welcome theoretical, methodological, empirical and technical contributions addressing topics including:

  • Which design processes involve learners, educators and other users effectively in the co-design of analytics tools?
  • Which techniques are effective in assessing how end-users make sense of, interact with, and act on analytics feedback?
  • In what ways can learning analytics systems be biased, and can they be made more transparent and accountable to different stakeholder groups?
  • How are educational leaders creating the conditions for learning analytics systems to take root and grow?
  • How strong is the evidence that the adoption of learning analytics benefits stakeholders?

LAK18 encourages contributions from the Schools sector, which has been under-represented at previous conferences. We will be proactive in welcoming and connecting researchers and practitioners working in the K-12 levels. Please contact the Program Chairs to learn more.

An innovation at LAK18 will be the addition of Extended Abstract as a submission category. This is designed to encourage submissions from researchers previously under-represented at LAK, but who can bring new perspectives. In many academic communities, writers submit extended abstracts rather than papers, in order to receive feedback prior to submission of journal papers. See the Research Track guidelines for details.

The Research and Practitioner tracks are summarised below.

Research Track

Focus: Rigorous academic research
Review Process: Double-blind peer review
Submission Types: Full Paper, Short Paper, Extended Abstract, Poster, Demo
Proceedings: Full and Short Papers archived and indexed in the ACM Digital Library. Others in Companion Proceedings.

Practitioner Track

Focus: Innovative, impactful, and insightful  implementations of learning analytics
Review Process: Double-blind peer review
Submission Types: Extended Abstract, Poster and Demo
Proceedings: LAK18 Companion Proceedings archived on the SoLAR website

Awards: Best Full Paper, Best Short Paper, Best Practitioner Extended Abstract, Best Poster, Best Demo Movie

Additional calls for participation are also out for Workshops and Tutorials and the Doctoral Consortium.

See Submission Guidelines for full details of the review process and submission guidelines for each category.

Conference Topics

We take learning analytics to be the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs.

The following categories reflect the primary objectives of learning analytics research and practice, and will be used to help classify submissions. Given the conference theme, all submissions are expected to attend in some way to the question of user-centred analytics:

Tracing Learning & Teaching:

  • Feature Finding: Studies that identify and explain useful data features for analysing, understanding and optimising learning and teaching.
  • Learning Metrics: Studies that assess learning progress through the computation and analysis of learner actions or artefacts.
  • Data Storage and Sharing: Proposals of technical and methodological procedures to store, share and preserve learning and teaching traces.

Understanding Learning & Teaching:

  • Data-Informed Learning Theories: Proposal of new learning/teaching theories or revisions/reinterpretations of existing theories based on large-scale data analysis.
  • Insights into Particular Learning Processes: Studies to understand particular aspects of a learning/teaching process through the use of data science techniques.
  • Modeling: Creating mathematical, statistical or computational models of a learning/teaching process, including its actors and context.

Improving Learning & Teaching:

  • Feedback and Decision-Support Systems:  Studies that evaluate the impact of feedback or decision-support systems based on learning analytics (dashboards, early-alert systems, automated messages, etc.).
  • Data-Informed Efforts:  Empirical evidence about the effectiveness of learning analytics implementations or educational initiatives guided by learning analytics.
  • Personalized and Adaptive Learning: Studies that evaluate the effectiveness and impact of (semi-)automatic adaptive technologies based on learning analytics.


  • Values, Ethics and Law: Analysis of issues and approaches to the lawful and ethical capture and use of educational data traces; tackling unintended bias and value judgements in the selection of data and algorithms; perspectives and methods for value-sensitive, participatory design that empowers stakeholders.
  • Adoption: Discussion and evaluation of strategies to promote and embed learning analytics initiatives in educational institutions and learning organisations.
  • Scalability: Discussion and evaluation of strategies to scale the capture and analysis of information at the program, institution or national level; critical reflection on organisational structures that promote analytics innovation and impact in an institution.

Key Dates

All deadlines are 23:59 GMT-11

Submission Deadline for Research Papers and Extended Abstracts, Practitioner Extended Abstracts, Posters, Demos, Workshops and Tutorials 2 October 2017
Notification of Acceptance for Workshops and Tutorials 16 October 2017
Workshop Calls for Participation 30 October 2017
Submission Deadline for Doctoral Consortium 10 November 2017
Notification of acceptance for Research Papers, Extended Abstracts, Practitioner Extended Abstracts, Posters, Demos 20 November 2017
Submission Deadline for Workshop Papers 18 December 2017
Camera-ready papers for ACM Proceedings: Full Research Papers and Short Research Papers 18 December 2017
Notification of acceptance for Doctoral Consortium</td>

8 January 2018
Release of Preliminary Program (titles, authors) 8 January 2018
Early-bird registration closes 9 January 2018
Notification of Acceptance for Workshop Papers 15 January 2018
Announcement of Final Program 29 January 2018
Camera-ready papers for Companion Proceedings: Workshop Papers 30 January 2018
Camera-ready papers for Companion Proceedings: Extended Abstracts, Practitioner Extended Abstracts, Posters, Demos, Tutorials, Doctoral Consortium 5 February 2018
LAK18, Sydney 5-9 March 2018

See Submission Guidelines for details.