We are very pleased to welcome you to the Twelfth International Conference on Learning Analytics and Knowledge (LAK22), organized by the Society for Learning Analytics Research (SoLAR). This year’s conference, while originally planned to be hosted by University of California, Irvine at the Newport Beach Marriott, is held virtually March 21-25, 2022 in an effort to protect the LAK community from the ongoing COVID-19 pandemic.

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 raised 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. We have three excellent keynotes who will address this theme across the complementary lenses of education, data science and social change: Lorri J. Santamaría from California Lutheran University who will speak about how equity-driven and culturally sustaining leadership can enhance learning analytics, Catherine D’Ignazio from the Massachusetts Institute of Technology who will speak about how feminist thinking can help envision more ethical and equitable data practices, and Pierre Dillenbourg from the Swiss Federal Institute of Technology who will speak about the future of classroom analytics to smooth orchestration.

We received a large number of high-quality submissions this year across the Practitioner Track, Posters and Demonstrations, Workshops and Tutorials and to the Doctoral Consortium. After undergoing a rigorous selection process, we were pleased to accept 6 Practitioner Track Papers, 27 Posters, 4 Demos, 17 Workshops and 8 participants to the Doctoral Consortium, each of which is represented in this Companion Proceedings. In addition, we accepted 2 Tutorials to be held at the conference: Processing and Visualizing Clickstream Data Using R and Aligning Decision-Making Models with Curriculum Theory.

We would like to emphasize our ongoing gratitude for the efforts made by everyone involved in our community during these difficult COVID times. We recognize that as we move through the second full year of the pandemic that the students, researchers and staff in our community face continued physical and emotional challenges, including stress, uncertainty and fear. These are difficult times for us all and we want to thank each one of you for the important efforts you have devoted that have allowed this conference to continue as a scientific event and scholarly exchange of ideas of the highest caliber.

We hope that LAK22 participants and other readers of these companion proceedings will find value in the many varied contributions to the field of learning analytics contained within and also recognize their positionality with respect to the different interdisciplinary fields from which we draw. This includes contributions to theory, methods and practice as well as both basic and applied work. As we continue to navigate these challenging times, the power and potential for analytics to help us achieve deeper understandings of learning and create better support for students, teachers and other educational stakeholders motivate us to persevere in this important work.

Alyssa Friend Wise
New York University, USA
Roberto Martinez-Maldonado
Monash University, Australia
Isabel Hilliger
Pontificia Universidad Católica de Chile, Chile

Item Info

URL: https://www.solaresearch.org/wp-content/uploads/2022/03/LAK22_CompanionProceedings.pdf
Publication Date: March, 2022
Author(s): Wise, A., Martinez-Maldonado, R., & Hilliger, I.
Source: Society for Learning Analytics Research (SoLAR)