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24th International Conference on Artificial Intelligence in Education

24th International Conference on Artificial Intelligence in Education

Tokyo + Online , Japan

Submission Deadline: Monday 09 Jan 2023

Conference Dates: Jul 03, 2023 - Sep 07, 2023

Research
Impact Score 1.00

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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: 1.00
Contributing Best Scientists: 8
H5-index:
Papers published by Best Scientists 25
Research Ranking (Computer Science) 346
Research Ranking (Psychology) 8
Research Ranking (Social Sciences and Humanities) 5

Conference Call for Papers

AIED 2023 solicits empirical and theoretical papers particularly (but not exclusively) in the following lines of research and application:

AI-assisted and Interactive Technologies in an Educational Context: Natural language processing and speech technologies; Data-driven processing techniques (educational data mining, deep learning, machine learning,...); Knowledge representation and reasoning; Semantic web technologies; Multi-agent architectures; Tangible interfaces, Wearables; Virtual 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 analysing activity flow and discourse during learning; Representing and modelling psychomotor learning.
Models of Teaching and Learning: AI-assisted tutoring and scaffolding; Motivational diagnosis and feedback; Learner engagement; Interactive pedagogical agents and learning companions; Agents that promote metacognition, motivation and positive affect; Adaptive question-answering and dialogue; Data-driven modelling (educational data mining, deep learning, machine learning,...); Learning analytics and teaching support; Learning with simulations; Explainability of models for teaching and learning.
Learning Contexts and Informal Learning: Game-based learning; 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 learning; Learning in informal settings (museum, workplace, etc.); Learning in the physical space; Learning of motor skills. Evaluation: Studies on human learning, cognition, affect, motivation, engagement, 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, sports and more); Scaling up and large-scale deployment of AIED systems.
Equity and Inclusion in Education: Socio-economic, gender, and racial issues; AI-assisted techniques to support students from under resourced schools and communities; Sponsorship, scientific validity, participant’s rights and responsibilities, data collection, management and dissemination.
Ethics of AI in Education: explainability, transparency, accountability, and responsible AIED; Learner consent and opt out; Surveillance and privacy; the impact of AIED on teachers, learners and classrooms; Teacher empowerment and student agency; the community’s responsibility for commercial applications; AIED ethical frameworks and principles for application.
Explore 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 Learning Spaces: Massive open online courses; Remote learning in k-12 schools; Synchronous and asynchronous learning; Mobile learning; Active learning in virtual settings; Video-based learning; Mixed reality and learning.

Overview

Top Research Topics at Artificial Intelligence in Education?

  • Artificial intelligence (24.56%)
  • Mathematics education (18.10%)
  • Multimedia (14.44%)

Artificial Intelligence in Education generally zeroes in on subjects such as Artificial intelligence, Mathematics education, Multimedia, Human–computer interaction and Machine learning. Task (project management) and Natural language processing are some topics wherein Artificial intelligence research discussed in Artificial Intelligence in Education have an impact. It is focused mainly on Mathematics education, particularly TUTOR.

What are the most cited papers published at the conference?

  • Intelligent Tutoring Goes To School in the Big City (984 citations)
  • Adaptive and Intelligent Web-based Educational Systems (668 citations)
  • Methodological Issues in the Content Analysis of Computer Conference Transcripts (611 citations)

Research areas of the most cited articles at Artificial Intelligence in Education:

The conference articles are mainly concerned with subjects like Multimedia, Artificial intelligence, TUTOR, Mathematics education and Machine learning. The conference papers explore issues in Multimedia which can be linked to other research areas like Higher education, Educational technology and Human–computer interaction. While the primary focus in the most cited papers is TUTOR, they also dissect topics surrounding Intelligent tutoring system and Affect (psychology) as a whole.

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 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.

Research.com

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.

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 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.

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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Deadline: Thursday 01 Dec 2022

Previous Editions

AIED 2021 : Artificial Intelligence in Education

Jul 14, 2021 - Jul 14, 2021

Utrecht , Netherlands, Netherlands

International Conference on Artificial Intelligence in Education

Jul 27, 2022 - Jul 31, 2022

Durham , United Kingdom, United Kingdom

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