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Springer

International Conference on Artificial Intelligence in Education (AIED)

Location: Durham , United Kingdom

Submission deadline: 1/31/2022

Conference dates: 7/27/2022 - 7/31/2022

Research H-index
13

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 262 35 48 13

Call for Papers

AIED 2022 solicits empirical and theoretical papers particularly (but not exclusively) in the following lines of research and application:

Intelligent and Interactive Technologies in an Educational Context: Natural language processing and speech technologies; Data mining and machine learning; Knowledge representation and reasoning; Semantic web technologies; Multi-agent architectures; Tangible interfaces, wearables and augmented reality.
Modelling and Representation: Models of learners, including open learner models; facilitators, tasks and problem-solving processes; Models of groups and communities for learning; Modelling motivation, metacognition, and affective aspects of learning; Ontological modelling; Computational thinking and model-building; Representing and analyzing activity flow and discourse during learning.
Models of Teaching and Learning: Intelligent tutoring and scaffolding; Motivational diagnosis and feedback; Interactive pedagogical agents and learning companions; Agents that promote metacognition, motivation and affect; Adaptive question-answering and dialogue, Educational data mining, Learning analytics and teaching support, Learning with simulations.
Learning Contexts and Informal Learning: Educational games and gamification; Collaborative and group learning; Social networks; Inquiry learning; Social dimensions of learning; Communities of practice; Ubiquitous learning environments; Learning through construction and making; Learning grid; Lifelong, museum, out-of-school, and workplace learning.
Evaluation: Studies on human learning, cognition, affect, motivation, and attitudes; Design and formative studies of AIED systems; Evaluation techniques relying on computational analyses.
Innovative Applications: Domain-specific learning applications (e.g. language, science, engineering, mathematics, medicine, military, industry); Scaling up and large-scale deployment of AIED systems.
Inequity and inequality in education: socio-economic, gender, and racial issues. Intelligent techniques to support disadvantaged schools and students. Ethics in educational research: sponsorship, scientific validity, participant’s rights and responsibilities, data collection, management and dissemination.
Design, use, and evaluation of human-AI hybrid systems for learning: Research that explores the potential of human-AI interaction in educational contexts; Systems and approaches in which educational stakeholders and AI tools build upon each other’s complementary strengths to achieve educational outcomes and/or improve mutually.
Online and distance learning: massive open online courses; remote learning in k-12 schools; synchronous and asynchronous learning; mobile learning; active learning in virtual settings.

Overview

This ranking presents a comprehensive evaluation of scientific conferences within the field of Computer Science. It has been meticulously developed by Research.com, a leading platform in science research that has provided authoritative and trusted data on scientific contributions across all major disciplines—including Computer Science—since 2014.

The positions in this ranking are determined through a unique bibliometric score formulated by Research.com, which incorporates the estimated h-index and the number of distinguished scientists who have contributed to and appeared at each conference over the past three years. The ranking features Impact Score values that were systematically collected as of November 27, 2024.

The analysis underpinning this ranking was exceptionally thorough, involving the review of more than 2,742 conferences. These conferences were rigorously selected following a detailed examination of over 148,739 scientific documents, all published within the last three years by 13,184 prominent and respected scientists specializing in Computer Science. This approach ensures that our ranking reflects both the quality and the scope of research contributions in the discipline.

For readers interested in a deeper understanding of our analytical approach, a comprehensive breakdown of the methodology used to develop these ranking scores can be accessed on our Methodology Page.

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.

The top authors publishing at Artificial Intelligence in Education (based on the number of publications) are:

  • Ryan S. Baker (23 papers) published 6 papers at the last edition,
  • Vincent Aleven (23 papers) published 4 papers at the last edition, 3 more than at the previous edition,
  • Danielle S. McNamara (21 papers) published 6 papers at the last edition,
  • James C. Lester (19 papers) published 5 papers at the last edition,
  • Arthur C. Graesser (19 papers) published 2 papers at the last 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.

Only papers with recognized affiliations are considered

The top affiliations publishing at Artificial Intelligence in Education (based on the number of publications) are:

  • Carnegie Mellon University (74 papers) published 10 papers at the last edition, 9 more than at the previous edition,
  • Worcester Polytechnic Institute (41 papers) published 3 papers at the last edition,
  • North Carolina State University (37 papers) published 8 papers at the last edition,
  • University of Memphis (35 papers) published 5 papers at the last edition,
  • Arizona State University (29 papers) published 9 papers at the last 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.

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.

During the most recent 2017 edition, 1.15% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 52.33% were posted by at least one author from the top 10 institutions publishing at the conference. Another 8.14% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 17.44% of all publications and 22.09% 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.

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.

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).

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

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