L-AT-S

It is our great pleasure to present the Proceedings of the Tenth Annual ACM Conference on Learning at Scale, L@S 2023, held July 20-22, 2023, in Copenhagen, Denmark.

The Association for Computing Machinery (ACM) created the conference, inspired by the emergence of Massive Open Online Courses (MOOCs) and the accompanying shift in thinking about education. During the last few years, new opportunities for scaling up learning have emerged, like hybrid learning environments combining online and face-to-face, informal learning enabled by all sorts of platforms (e.g., gamified language learning, citizen science communities, and collaborative programming communities), or new ways of learning supported by recent advances in artificial intelligence. L@S has evolved along with these emergent massive learning scenarios and opportunities and is today one of the most prominent venues for discussion of the highest quality research on how learning and teaching can be transformed at scale, in diverse learning environments.

L@S examines learning and teaching processes in all large-scale, technology-mediated learning environments that typically have many active learners and few experts to guide their learning progress or respond to individual needs in time. Research on learning at scale involves the examination of learning and teaching processes, based on the diverse types of data and technology-mediated environments, with a particular purpose of increasing human potential, leveraging data collection, data analysis, human interaction, and varying forms of computational and other types of assessment, adaptation, and guidance. Dealing with data and humans in the context of education requires a systemic approach considering organizational, technical, and social factors as well as factors related to fairness, accountability, trustworthiness, culture and equity, which are increasingly included as major research topics in the L@S community.,

As the complexity of data and learning settings evolves, the learning at scale research also expands, becoming more interdisciplinary, multifaceted, and advanced. As a community, we aim for novel methods and approaches to measure learning more directly, accompanied by generalizable insight around instructional techniques, learning habits and behavior change, technological infrastructures, and experimental interventions aiming at improving learning outcomes. Creating new methods and measures is only possible with an interdisciplinary community that brings together learning scientists with computer and data specialists.

The theme of L@S 2023 is Learning Futures@Scale. The widespread move to online learning during the last few years due to the global pandemic has opened new opportunities and challenges for the L@S community. These opportunities and challenges relate not only to the educational technologies used but also to the social, organizational, and contextual aspects of supporting learners and educators in these dynamic and, nowadays, often multicultural learning environments. How the future of learning at scale will look needs careful consideration from several points of view, including a focus on technological, social, organizational, cultural, and responsible aspects of learning and teaching.