Ranking & Metrics Conference Call for Papers Other Conferences in United States
Conference on Learning at Scale

Conference on Learning at Scale

Roosevelt Island , United States

Submission Deadline: Monday 31 Jan 2022

Conference Dates: Jun 01, 2022 - Jun 03, 2022

Research
Impact Score 0.90

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Ranking & Metrics Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.

Research Impact Score: 0.90
Contributing Best Scientists: 10
H5-index:
Papers published by Best Scientists 10
Research Ranking (Computer Science) 212
Research Ranking (Psychology) 32
Research Ranking (Social Sciences and Humanities) 9

Conference Call for Papers

We solicit empirical and theoretical papers on a diverse range of topics relevant to successful learning at scale. For [email protected] 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.

Overview

Top Research Topics at Learning at Scale?

  • Multimedia (21.50%)
  • Mathematics education (18.74%)
  • Artificial intelligence (15.78%)

The aim of Learning at Scale is to expand the discussion of research in Multimedia, Mathematics education, Artificial intelligence, Machine learning and Data science. Multimedia research featured in it incorporates concerns from various other topics such as Scalability, World Wide Web and Human–computer interaction. Massive open online course research are fields of study within Mathematics education but they also intertwine with concepts in Online learning.

Discussions in the conference are anchored in the subject of Artificial intelligence and the similar topic of Tracing. The works on Data science deal in particular with Learning analytics. Learning at Scale focuses on Learning analytics as well as the interrelated topic of Analytics.

What are the most cited papers published at the conference?

  • How video production affects student engagement: an empirical study of MOOC videos (849 citations)
  • Understanding in-video dropouts and interaction peaks inonline lecture videos (254 citations)
  • Attrition and Achievement Gaps in Online Learning (147 citations)

Research areas of the most cited articles at Learning at Scale:

The most cited articles mainly deal with areas of study such as Multimedia, Machine learning, Artificial intelligence, World Wide Web and Mathematics education. The most cited articles blend together research topics in Multimedia and Online learning. The most cited papers with studies in Artificial intelligence featured incorporate elements of Crowdsourcing and Online course.

What topics the last edition of the conference is best known for?

  • Artificial intelligence
  • Operating system
  • The Internet

The previous edition focused in particular on these issues:

The discussions in the conference mainly cover the fields of Mathematics education, Multimedia, Data science, Learning analytics and Online learning. It features works in Mathematics education, more specifically Student engagement and Active learning, and explores their relation to disciplines like Value (ethics). The event explores issues in Multimedia which can be linked to other research areas like Control (management) and Automatic question generation.

It explores topics in Data science which can be helpful for research in disciplines like Toolbox, Peer grading, Educational software and Credential. The research on Learning analytics featured in it combines topics in other fields like Reliability (statistics), Baseline (configuration management) and Inference. Learning at Scale addresses concerns in Chemistry (relationship) which are intertwined with other disciplines, such as Task (project management) and Artificial intelligence.

The most cited articles from the last conference are:

  • Learning Analytics Dashboard Research Has Neglected Diversity, Equity and Inclusion (2 citations)
  • Student Barriers to Active Learning in Synchronous Online Classes: Characterization, Reflections, and Suggestions (1 citations)
  • Toward Reshaping the Syllabus for Education at Scale (1 citations)

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Research.com

The top authors publishing at Learning at Scale (based on the number of publications) are:

  • David A. Joyner (25 papers) published 4 papers at the last edition, 5 less than at the previous edition,
  • Neil T. Heffernan (16 papers) published 2 papers at the last edition the same number as at the previous edition,
  • René F. Kizilcec (15 papers) published 5 papers at the last edition, 2 more than at the previous edition,
  • Joseph Jay Williams (11 papers) published 4 papers at the last edition, 2 more than at the previous edition,
  • Christoph Meinel (11 papers) published 3 papers at the last edition, 1 more than at the previous edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Research.com

Only papers with recognized affiliations are considered

The top affiliations publishing at Learning at Scale (based on the number of publications) are:

  • Massachusetts Institute of Technology (45 papers) published 1 paper at the last edition, 4 less than at the previous edition,
  • Georgia Institute of Technology (39 papers) published 7 papers at the last edition, 11 less than at the previous edition,
  • Stanford University (39 papers) published 3 papers at the last edition, 2 less than at the previous edition,
  • Carnegie Mellon University (36 papers) published 4 papers at the last edition the same number as at the previous edition,
  • University of Illinois at Urbana–Champaign (27 papers) published 3 papers at the last edition, 1 less than at the previous edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Research.com

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

Research.com

During the most recent 2021 edition, 7.02% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 47.17% were posted by at least one author from the top 10 institutions publishing at the conference. Another 15.09% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 11.32% of all publications and 26.42% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Research.com

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

Research.com

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

Research.com

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Research.com

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57th Annual Conference on Information Sciences and Systems

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52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks

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International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research

Jun 20, 2022 - Jun 23, 2022

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Deadline: Saturday 03 Dec 2022

Previous Editions

L@S 2021 : ACM Conference on Learning @ Scale

Jun 22, 2021 - Jun 22, 2021

Potsdam , Germany, Germany

Conference on Learning at Scale

Jun 01, 2022 - Jun 03, 2022

Roosevelt Island , United States, United States

9th ACM Conference on Learning at Scale

Jun 01, 2022 - Jun 03, 2022

New York City , United States, United States

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