Call for Papers

Conference Theme: Learning Futures @ Scale 

The widespread move to online learning during the last few years due to the global pandemic has opened up new opportunities and challenges for the Learning at Scale (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. The theme of this year’s conference is the learning futures that the L@S community aims to develop and support in the coming decades. Of special interest this year are contributions that examine the design and the deployment of large-scale systems for the future of learning at scale. We are especially welcoming works targeting not only learners but also educators, educational institutions and other stakeholders involved in the design, use and evaluation of large-scale learning systems. Moreover, we welcome qualitative and mixed-methods contributions, as well as studies that are not at scale themselves but about scaled learning phenomena/environments. Finally, we are also welcoming submissions focusing on the role of culture and cultural values in the implementation and evaluation of large-scale systems.

Submissions

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 included in the proceedings (more details about these contributions can be found below).

Paper submissions, reviewing and notification to authors will be handled using the conference page at Easy Chair (the link is coming soon!). Submissions must be in PDF format, anonymized for double-blind review (see below), follow 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.

The submission link (2023): https://easychair.org/conferences/?conf=ls2023 

Anonymization policy for double-blind review: Submissions will be reviewed on the basis of originality, research quality, potential impact, and value to the development of future learning at scale. In order to increase high-quality papers and independent merit, the evaluation process will be double-blind. All submissions, with the exception of workshop proposals (see below), should be anonymous. Thus, papers submitted for review MUST NOT contain the authors’ names, affiliations, or any information that may disclose the author’s identity (this information is to be restored in the camera-ready version upon acceptance). Please replace author names and affiliations with Xs on submitted papers. In particular, in the version submitted for review, please avoid explicit self-references, such as “in [1] we show” — consider instead “in [1] it is shown” or “in [1] Smith et al. show …” (citing yourself in the third person just like how you would cite other researchers). You should definitely cite your own relevant previous work, so that a reviewer can access it and see the new contributions. However, the text should not explicitly state that the cited work belongs to the authors.

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 (not including references); abstract due January 27 2023, papers due Feb 3, 2023. However, we would recommend to keep the length of the papers proportional to the size and the scope of the research contribution.

We solicit empirical and theoretical papers on a diverse range of topics relevant to successful learning at scale. For Learning@Scale 2023, 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. 

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 2023 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: Eleanor O’Rourke) — 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).

Work-in-Progress

Up to 4 pages (not including references); due April 7, 2023.

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. Areas of interest 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.

Demonstrations

Up to 2 pages (not including references); due April 7, 2023.

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:

1. 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.
2. Details of how the demo will be executed in practice, and how visitors will interact with it aduring the conference.

Workshops and tutorials

Up to 4 pages (including references); due February 24, 2023

Workshops serve as a gathering place for attendees with shared interests to build community, and are expected to dedicate a substantial time for interaction between participants.  A workshop can be half-day or full-day, depending on the goals of the organizers. Workshops can address any Learning @ Scale topic.  

Tutorials aim to offer the opportunity to acquire new skills and knowledge valuable to community members. Tutorials should aim to promote participation and interaction between participants as well. Organizers need to prepare a guided introduction to a topic including hands-on activities for the participants. Proposals should be clear about what the need is for particular knowledge, target audience and their prior knowledge, and the intended learning outcomes.

The organizers of accepted workshops and tutorials are expected to set up a website including at least a call for participation and a description of the planned activities. The content of the call for papers and the planned activities will be provided at submission time by means of a form (see below). The description of the accepted workshop and tutorial proposals will be published in the conference proceedings. To that aim, the submission requires that organizers upload a file with this description. 

Submission Format: Workshop and Tutorials organizers should submit their proposals by means of a workshop/tutorial submission form. This form asks organizers to describe: Type of event (workshop / tutorial), Title, Organizers, Duration of the event (half-day or full-day), Intended audience, Call for Participation, Planned activities, and Requirements for participation. In addition to this form, workshop organizers should submit a document with the description of the workshop / tutorial using the conference page at EasyChair (see below). 

Workshop/tutorial description for the proceedings: The document with the workshop and tutorial proposals must not exceed 4 pages (not including references) and use the ACM Proceedings Format, available in LaTeX, Word, or Overleaf. Unlike other submission types, workshop and tutorial submissions are not anonymous and should include all author names, affiliations and contact information. The suggested structure for workshop/tutorial description is the following: Title, Organizers’ names and affiliations, Theme and goals, Theoretical background and relevance to Learning at Scale, Expected outcomes and contributions, and References.  

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 before 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).

Important Dates

Research and Synthesis Papers

Please, note that this year there will NOT be any extensions of the deadlines for all types of submissions! All deadlines are final.

• Abstract Submissions:  January 27, 2023 (11:59 PM AoE)
• Full Paper Submission:  February 3, 2023 ( 11:59 PM AoE)
• Author Notification: March 31, 2023 (11:59 PM AoE)
• Camera-ready Version: April 14, 2023(11:59 PM AoE) 

Work-in-progress and Demonstrations

• Paper Submission:  April 7, 2023 (11:59 PM AoE)
• Author Notification: April 21, 2023 (11:59 PM AoE)
• Camera-ready Version: April 28, 2023 (11:59 PM AoE) 

Workshops and Tutorials

• Workshop Proposal Submission: February 24, 2023 (11:59 PM AoE)
• Organizer Notification: March 11, 2023 (11:59 PM AoE)
• Camera-ready Version: April 14, 2023 (11:59 PM AoE) 

The submission link (2023): https://easychair.org/conferences/?conf=ls2023