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September 2021


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Society for Learning Analytics Research <[log in to unmask]>
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Classification, clustering, and phylogeny estimation
Thu, 2 Sep 2021 21:23:40 +0100
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[apologies for cross posting]



Hi all,


As we plan for LAK22 (The 12th International Conference on Learning Analytics & Knowledge), COVID-19 is still a serious issue for many globally. We realise that a fully face to face event for everyone is unlikely given the current global nature and ongoing impacts from COVID-19 and organizers are constantly monitoring the situation. That said, LAK22 Organizers are exploring two main options: 


·       A hybrid event with face to face elements for those who are able to attend in California and virtual participation for those attendees and presenters unable to travel.


·       Fully virtual as per LAK21.


Organizers will make a final decision on the format for LAK22 in October/November this year and communicate with the community as things evolve. Please be assured that regardless of format LAK22 will continue to be a high quality learning analytics conference experience. 




The 2022 edition of The International Conference on Learning Analytics & Knowledge (LAK22) will take place in Newport Beach, California! LAK22 is organised by the Society for Learning Analytics Research (SoLAR) with location hosts from the University of California, Irvine. LAK22 is a collaborative effort by learning analytics researchers and practitioners to share the most rigorous cutting edge work in learning analytics.


The theme for the 12th annual LAK conference is Learning Analytics for Transition, Disruption and Social Change. This theme brings to the forefront both the dynamic world situation in which learning analytics now operate and the potential role of learning analytics as a driving force for change within it. In a moment when questions about transparency, fairness, equity and privacy of analytics are being brought to the forefront in many areas of application, there is both an opportunity and an imperative to engage with these issues in support of ethical pedagogical transitions and transformative social justice. In addition, as LAK itself explores changing formats for knowledge exchange and generation, this theme offers the opportunity for reflection on how to make the conference more sustainable and accessible for people around the world.


The LAK conference is intended for both researchers and practitioners. We invite both researchers and practitioners of learning analytics to come and join a proactive dialogue around the future of learning analytics and its practical adoption. We further extend our invite to educators, leaders, administrators, government and industry professionals interested in the field of learning analytics and its related disciplines. 


Authors should note that:


·       The LAK conference has received a CORE ranking of A (top 16% of all 811 ranked venues).

·       LAK is the only conference in the top 10 Google Scholar citation ranks for educational technology publications.




We welcome submissions from both research and practice, encompassing different theoretical, methodological, empirical and technical contributions to the learning analytics field. Learning analytics research draws on many distinct academic fields, including psychology, the learning sciences, education, neuroscience, computer science and design. We encourage the submission of work conducted in any of these traditions, as long as it is done rigorously. We also welcome research that validates, replicates and examines the generalizability of previously published findings, as well as examines aspects of adoption of existing learning analytics methods and approaches. 


Specifically, this year, we encourage contributors to consider how learning analytics is playing a role in social change. Since its inception, the field of learning analytics has had the goal of improving learning; this year we ask submissions to think beyond individual learners to also consider how our work intersects and interacts with existing power structures and systemic inequities. Despite the promising growth of online learning strategies and related approaches to data collection and analysis, the COVID-19 pandemic has both revealed and exacerbated equity and quality issues in educational systems, between and within regions and countries. 


Thus for our 12th Annual conference, we encourage authors to address some of the following questions in their submissions:


1.    Who decides what learning analytics get created and implemented?

2.    What groups and individuals are impacted by the use of learning analytics and in what ways?

3.    What value systems are embedded within learning analytics?

4.    What opportunities do learning analytics offer to drive positive social change?

5.    In what ways can we prevent learning analytics from perpetuating problematic systems or practices?


Topics of interest include, but are not limited to, the following:


Understanding Learning & Teaching:


·       Data-informed learning theories: Proposals of new learning/teaching theories or revisions/reinterpretations of existing theories based on large-scale data analysis.

·       Insights into specific learning processes: Studies to understand particular aspects of a learning/teaching process through the use of data science techniques, including negative results.

·       Learning and teaching modeling: Creating mathematical, statistical or computational models of a learning/teaching process, including its actors and context.

·       Systematic reviews: Studies that provide a systematic and methodological synthesis of the available evidence in an area of learning analytics.


Tracing Learning & Teaching:


·       Finding evidence of learning: Studies that identify and explain useful data for analysing, understanding and optimising learning and teaching.

·       Assessing student learning: Studies that assess learning progress through the computational analysis of learner actions or artefacts.

·       Analytical and methodological approaches: Studies that introduce analytical techniques, methods, and tools for modelling student learning.

·       Technological infrastructures for data storage and sharing: Proposals of technical and methodological procedures to store, share and preserve learning and teaching traces, taking appropriate ethical considerations into account.


Impacting Learning & Teaching:


·       Human-centered design processes: Research that documents practices of giving an active voice to learners, teachers, and other educational stakeholders in the design process of learning analytics initiatives and enabling technologies.

·       Providing decision support and feedback: Studies that evaluate the use and impact of feedback or decision-support systems based on learning analytics (dashboards, early-alert systems, automated messages, etc.).

·       Data-informed decision-making: Studies that examine how teachers, students or other educational stakeholders come to, work with and make changes using learning analytics information.

·       Personalised and adaptive learning: Studies that evaluate the effectiveness and impact of adaptive technologies based on learning analytics.

·       Practical evaluations of learning analytics efforts: Empirical evidence about the effectiveness of learning analytics implementations or educational initiatives guided by learning analytics.


Implementing Change in Learning & Teaching:


·       Ethical issues around learning analytics: 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 that empower stakeholders.

·       Learning analytics adoption: Discussions and evaluations of strategies to promote and embed learning analytics initiatives in educational institutions and learning organisations. Studies that examine processes of organizational change and practices of professional development that support impactful learning analytics use.

·       Learning analytics strategies for scalability: Discussions and evaluations of strategies to scale capture and analysis of information in useful and ethical ways at the program, institution or national level; critical reflections on organisational structures that promote analytics innovation and impact in an institution.

·       Equity and fairness in learning analytics: Consideration of how certain practices of data collection, analysis and subsequent action impact particular populations and affect human well-being, specifically groups that have been previously disadvantaged. Discussions of how learning analytics may impact (positively or negatively) social change and transformative social justice.




1.    Research Track (Full & Short Papers)

2.    Practitioner and Corporate Learning Analytics Track (Practitioner Reports)

3.    Posters & Demos (Posters and Interactive Demos)

4.    Pre-conference Event Track (Workshops and Tutorials)

5.    Doctoral Consortium (See DC CFP here)


Submission Guidelines for all tracks to outline submission details, technical formats and recommendations are available here! 




LAK22 will use a double-blind peer review process for all submissions except demos and the doctoral consortium (which each require elements that prevent blinding). To continue to strengthen the review process for both authors and reviewers  LAK22 will have a rebuttal phase for full and short research papers in which authors will be given five days to respond to remarks and comments raised by reviewers in a maximum of 500 words. Rebuttals are optional, and there is no requirement to respond. Authors should keep in mind that papers are being evaluated as submitted and thus, responses should not propose new results or restructuring of the presentation. Therefore, rebuttals should focus on answering specific questions raised by reviewers (if any) and providing clarifications and justifications to reviewers. Meta-reviewers, senior members of the research community, make final recommendations for paper acceptance or rejection with justification to the program committee chairs after the rebuttal phase is concluded. Acceptance decisions are ultimately taken by the program committee chairs based on all available information from the review process in combination with the constraints of the allowable space in the conference program.


Finally, please note that the conference timeline allows for rejected submissions to be re-submitted in revised form as poster, demo and workshop papers. 




Accepted full and short research papers will be included in the LAK22 conference proceedings published and archived by ACM (pending ACM approval). Other types of submissions (posters, demos, workshops, tutorials, practitioner reports and doctoral consortium) will be included in the open access LAK companion proceedings, published on SoLAR’s website. Please note at least one of the authors of each accepted submission must register for the conference by the Early Bird deadline in order for the paper to be included in the ACM or LAK Companion Proceedings.




Note: all dates are 23:59 GMT-12 (AOE Timezone)


Full / Short Research Papers


·       4 Oct 2021: Deadline for submission 

·       8 Nov 2021: Rebuttal submissions open

·       15 Nov 2021: Deadline for rebuttal submissions

·       3 Dec 2021: Notification of acceptance 

·       20 Dec 2021: Deadline for camera-ready versions of all accepted full and short research papers 

·       14 March 2022: Proceedings available in ACM digital library (pending ACM approval)


Practitioner Reports


·       4 Oct 2021: Deadline for submission 

·       3 Dec 2021: Notification of acceptance 

·       20 Dec 2021: Deadline for camera-ready versions of practitioner reports


Posters / Demos


·       17 Dec 2021: Deadline for poster and interactive demo submissions 

·       14 Jan 2022: Notification of acceptance for posters/demos and papers submitted to individual workshops 

·       31 Jan 2022: Deadline for camera-ready versions of posters/demos


Doctoral Consortium


·       18 Oct 2021: Deadline for submission to doctoral consortium 

·       3 Dec 2021: Notification of acceptance 

·       20 Dec 2021: Deadline for camera-ready versions of all accepted papers


Workshops / Tutorials


·       4 Oct 2021: Deadline for submission to organize workshops/tutorials 

·       21 Oct 2021: Notification of acceptance for workshop/tutorial organization

·       17 Dec 2021: Deadline for submission of papers to individual workshops that issue calls**

·       14 Jan 2022: Notification of acceptance for posters/demos and papers submitted to individual workshops** 

·       31 Jan 2022: Deadline for camera-ready versions of workshop/tutorial organizer docs and any individual papers** accepted by workshops

**Workshop Paper Submissions - this term refers to papers submitted to be presented within an accepted LAK pre-conference workshop. Many LAK workshops are mini-symposium style and issue calls for papers. Please visit the pre-conference schedule when available, to view which workshops have CFP’s that you may submit to.


Conference and registration dates:


·       28 Jan 2022: Early-bird registration closes at 11:59pm PST

·       19 - 23 March 2022: LAK22 conference, Newport Beach, California


We are looking forward to seeing you at LAK22!!


Kind regards,


Organizing Committee of LAK22

Society for Learning Analytics Research (SoLAR)