Call for Papers
We are inviting contributions that address innovations in scaling, enhancing, and increasing reach, quality, and equity in learning. Of special interest are empirical investigations of learning at scale, new technical systems for scaling learning solutions, and novel syntheses of relevant research on these areas. Work from both formal and informal education environments at all levels is encouraged.
Conference Theme: Blending @ Scale
The emergency move to online learning last year has created opportunities and challenges in the field of Learning at Scale. On one hand, it has highlighted the role of educational technology as a driver for more efficient and scalable learning. On the other, it has also exposed existing access inequalities to those technologies and amplified their consequences. It is becoming clear that the immediate future will not be a return to past practices, but a blending of new and old, face-to-face and online, traditional and technology-enhanced. The theme of this year’s conference is how the L@S community should adapt to more blended scenarios, exploiting new opportunities, but also addressing technological challenges and inequalities. Of special interest this year are works that examine the lessons learned during the deployment and use of large-scale systems for emergency online learning, with focus on determining for which students it was beneficial, but also those students for whom the interventions were suboptimal or detrimental. Also, works that analyze how institutions have responded, adopted and adapted to learning at scale solutions during the past year are welcomed.
The ACM Learning at Scale conference solicits original research paper submissions on methodologies, case studies, analyses, tools, or technologies for learning at scale, broadly construed. Five kinds of contributions will be accepted: Research Papers, Synthesis Papers, Work-in-Progress, Demonstrations, and Workshops. Accepted works must be presented at the conference and will be included in the proceedings.
Paper submissions, reviewing and notification to authors will be handled using the conference page at Easy Chair. Submissions must be in PDF format, following the ACM 2-column proceedings template (Word or Latex), written in English, contain original work and not be under review for any other venue while under review for this conference. The page limits for the different submissions exclude the pages used for references. For research and synthesis papers, the abstract must be submitted before the final contribution. The length of the abstract should not exceed 350 words.
Accepted authors will have the option of presenting supplementary online materials to aid in their presentation. Presenters are encouraged to use their allotted conference time for activities or discussion in addition to delivering presentations or showing posters. We encourage best practices in open science as described in the Statement on Open Science below.
Research and Synthesis Papers
Up to 10 pages; abstract due January 24, 2022, final submission due January 31, 2022.
We solicit empirical and theoretical papers on a diverse range of topics relevant to successful learning at scale. For Learning@Scale 2022, we specifically solicit work in six areas of interest to grow our community whilst being inclusive to other work: (1) Instruction @ scale, (2) Studies and interventions @ scale, (3) Intelligence @ Scale, (4) Informal learning @ scale, (5) Systems and tools @ scale, and (6) Review and Synthesis papers. Accounts of robust methodologies from the learning sciences theory, practice, and/or engineering perspectives are encouraged. Regardless of approach, strong contributions address relevance in terms of theory and practice.
Each area is represented by a community champion who can answer questions about the fit of potential submissions and who helps ensure a high-quality reviewing process in the area. The L@S 2022 areas of interest are:
Instruction @ Scale (Champion: Marco Kalz) — Studies that explore what aspects of instruction could be scaled effectively, as well as which of them are the most effective for learning. Some of the research questions to explore are: What kinds of instructional designs help educators to scale learning online and in hybrid settings? How can learning make use of scaled environments while remaining embedded in a learning community?
Studies And Interventions @ Scale (Champion: René Kizilcec) — Studies that take a qualitative or mixed-methods approach to understand learners’ and teachers’ experiences and contextual factors in scaled or scalable learning environments to inform theory and/or design. Some of the research questions to explore are: What kind of learning support is efficient, effective and enjoyable in hybrid learning environments at scale?
Intelligence @ Scale (Champion: Kenneth Koedinger) — Putting Artificial Intelligence models and techniques at the service of education at scale. Some of the research questions to explore are: How can AI and hybrid models help to scale learning practices? How can AI technologies be used to adapt and personalize learning at scale?
Informal Learning @ Scale (Champion: Justin Reich) – Studies that explore how people take advantage of online environments to pursue their interests informally. Some of the research questions to explore are: What features of online environments motivate and sustain informal learning at scale? Who has access to informal learning experiences at scale, who does not, and why?
Systems and Tools @ Scale (Champion: Pedro Muñoz-Merino) — Studies that build and evaluate novel systems or tools for supporting learning scenarios at scale. Some research questions to explore are: What type of architectures do we need? What type of processes do we need to follow to scale tools institutionally, and what actors do we involve in these processes?
Review and Synthesis papers (Champion: Yannis Dimitriadis) – To support collaboration between learning scientists, computer scientists and contributors from other relevant fields, we invite papers that evaluate, synthesize, and contextualize existing bodies of knowledge and research that may be targeted at one or more communities. Such papers may have high value to the community but might not otherwise be accepted only on the basis of original research contributions. Suitable papers include survey papers that provide useful perspectives on major research areas, papers that support or challenge long-held beliefs with compelling evidence, or papers that provide an extensive and realistic evaluation of competing approaches to solving specific problems.
Statement on Open Science
Authors are encouraged to conduct their scientific inquiry using emerging best practices in open science. Authors are encouraged to preregister their study design, hypotheses, and analysis plans, and publish these using platforms such as OSF.io or AsPredicted.org. Whenever possible, feasible, and ethical, authors are encouraged to make their data, materials, and scripts openly available for inspection, replication, and follow-up analysis. The best way to share these materials is to use an established platform like OSF.io.
Authors are also encouraged to post pre-prints of their submissions with preprint hosting sites such as EdArXiv.org or on their own sites. If accepted, any preprint version should be updated to refer readers to the journal version as the document of record. The Learning@Scale steering committee supports open dissemination of knowledge as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Up to 4 pages; due February 28, 2022.
A Work-in-Progress (WiP) concisely summarizes recent findings or other types of innovative or thought-provoking work that has not yet reached a level of completion for a full paper. Topics are the same as for full papers. At the conference, all accepted WiP submissions will be presented in poster form. Selected WiPs may be invited for oral presentation during the conference. Rejected full papers can be resubmitted as WiP and will be evaluated accordingly.
Up to 2 pages; due February 28, 2022.
Demonstrations show aspects of learning at scale in an interactive, hands-on form. A live demonstration is a great opportunity to communicate ideas and concepts in a powerful way that a regular presentation cannot provide. We invite demonstrations of learning and analytical environments and other systems that have direct relevance to learning at scale. We especially encourage authors of accepted papers to showcase their technologies using this format. A demonstration submission should address two components:
- The merit and nature of the demonstrated technology. If the proposed demonstration is associated with a Full Paper or a WiP submission, please point to the title of the submission instead of repeating the information here.
- Details of how the demo will be executed in practice, and how visitors will interact with it during the conference.
Up to 4 pages; due February 14, 2022.
Workshops serve as a gathering place for attendees with shared interests to build community. A workshop can be half-day or full-day, depending on the goals of the organizers. Workshops can address any Learning @ Scale topic. In your proposal, be clear about the purpose of the workshop, who will benefit from participating, and what participants will be able to do after engaging in the workshop. Specify if the participants need to bring a laptop or other equipment to the workshop.
A workshop submission should include the following sections: Background, Organizers, Pre-Workshop Plans, Workshop Structure, Post-Workshop Plans, 250-word Call for Participation, References.
Submission Format: Workshop proposals must not exceed 4 pages (including references) and use the ACM Proceedings Format, available in LaTeX, Word, or Overleaf. Workshop submissions are not anonymous and should therefore include all author names, affiliations and contact information.
Open Access to Proceedings
The official publication date is the date the proceedings are made available in the ACM Digital Library. This date may be up to two weeks prior to the first day of your conference. The official publication date affects the deadline for any patent filings related to published work. (For those rare conferences whose proceedings are published in the ACM Digital Library after the conference is over, the official publication date remains the first day of the conference).
Research and Synthesis Papers
- Abstract Submissions: January 24, 2022 (23:59 GMT+12 / 11:59 PM AoE)
- Final Version Submission: January 31, 2022 (23:59 GMT+12 / 11:59 PM AoE)
- Author Notification: March 14, 2022
- Camera-ready Version: March 30, 2022
Work-in-progress and Demonstrations
- Final Version Submission: February 28, 2022 (23:59 GMT+12 / 11:59 PM AoE)
- Author Notification: March 21, 2022 (23:59 GMT+12 / 11:59 PM AoE)
- Participant Submissions: March 21, 2022
- Camera-ready Version: March 30, 2022
- Final Version Submission: February 14, 2022 (23:59 GMT+12 / 11:59 PM AoE)
- Organizer Notification: February 21, 2022 (23:59 GMT+12 / 11:59 PM AoE)
- Participant Submissions: March 21, 2022
- Notification of Acceptance to Participants: April 18, 2022