ACM Learning at Scale

Learning at Scale (L@S)

L@S investigates large-scale, technology-mediated learning environments that typically have many active learners and few experts on hand to guide their progress or respond to individual needs. They are inviting contributions that address innovations in scaling and enhancing learning, empirical investigations of learning at scale, new technical systems for learning at scale, and novel syntheses of relevant research on these areas. Work from both formal and informal education environments at all levels is encouraged; L@S welcomes studies of higher education and informal adult learning.

Abstracts for Research Papers due February 8, 2021. Author guidelines and important dates for all other submissions can be found in the call for submissions.