This track focuses on the theoretical, model-based, strategic, and practical aspects of artificial intelligence (AI) in education, as well as the design, technology, and evaluation of intelligent learning environments. It also explores various scenarios for the application of AI in education.

The goal of this sub-conference is to better understand the various facets of the integration of AI and education, promoting the design and development of learning systems supported by AI. The development of AI in education applications and practices, along with the creation of intelligent learning environments, results from the convergence of multiple disciplines, including learning technology, educational research and practice, cognitive and learning sciences, computer science, psychology, linguistics, and other related fields. The challenges faced by AI in education stem from its interdisciplinary nature, often requiring collaboration among experts from various domains to provide innovative, interdisciplinary solutions to enhance teaching and learning.

This track aims to gather renowned experts and scholars globally in this field, using this open platform as a foundation to collectively explore new theoretical and practical insights, further advancing the development of this field.

Call for Paper Topics  (including but not limited to the following topics):

• Theories, models, and strategies of AI in Education (AIED)

• Teaching practices in AI Education

• Applications of generative AI models, large language models, and multimodal models in education

• Construction and application of large-scale educational models

• Construction, application, and evaluation of intelligent teaching systems

• Ethical, moral, and regulatory considerations in AI in Education (AIED)

• Educational applications of deep neural network technologies

• Applications of knowledge graphs in education

• Emerging AI models such as contrastive learning, meta-learning, and few-shot learning in education

• Research on AI and adaptive learning

• Learning analytics research based on big data

• Learning research using context-aware sensing technologies

• Adaptive diagnostics for personalized learning characteristics of students

• Intelligent decision-making in educational management

• Educational robots and intelligent learning companions

• AI-based automatic problem-solving and tutoring systems

Paper Submission Guidelines

This workshop only accepts full-length papers (including long, short papers, or poster papers) and does not accept abstract submissions. The conference employs a "double-blind" review system, where papers are anonymously reviewed without revealing the identities of the authors and reviewers. Therefore, during the paper review phase, authors must remove their information from the paper (including the title, main text, and references). After acceptance, the final version of the paper submitted for publication must include the relevant author information.

Starting from 2020, the nine sub-conferences of GCCCE will only accept Chinese papers. Therefore, papers submitted to this sub-conference must be written in Chinese (eight pages for long papers, four pages for short papers, and two pages for posters). Chinese papers should provide titles, abstracts, and keywords in both Chinese and English and should be uploaded in PDF format to the conference website: https://easychair.org/conferences/?conf=gccce2024 Please refer to the conference paper format example [in Chinese] to prepare your paper. Note that all English papers, regardless of the topic, should be submitted to the "English Paper Track."

Once a paper is accepted, at least one author must register and attend to present the paper.

Program Committee

Chair:

Penghe Chen, Beijing Normal University

Vice Chairs:

Jian Liao, Southwest University

Jia Zhu, Zhejiang Normal University

Qi Wang, Beijing Foreign Studies University