征 稿 通 知
第25届国际人工智能教育重要会议（AIED 2024）“世界转型中的人工智能教育” 专题征稿通知
AIED全称为International Conference on Artificial Intelligence in Education，是国际人工智能教育领域的重要会议，由国际人工智能教育协会组织，旨在推进支持学习的智能人机生态系统的科学和工程，以在AI辅助系统和认知科学方法方面进行高质量和创新性研究而闻名。
今年AIED大会的主题是“世界转型中的人工智能教育”，会议旨在探讨在颠覆性技术颠覆教育的情况下，如何利用人工智能提升学生和教师的学习体验。会议希望促进讨论人工智能如何塑造各行各业的教育，如何推动人工智能辅助学习系统的科学和工程发展，以及如何促进广泛采用。据悉，会议将制定更广泛的议程，与研究人员、教育从业人员、企业、政策制定者以及教师和学生等各利益相关方一起，就新颖的研究理念如何满足实际需求，建立有效的智能人类-技术生态系统，以支持新的、复杂的和未知场景下的学习。
对于人工智能赋能教育产业从业者来说，这是一个充分了解产业发展的新机遇、与其他同行合作并招募优秀人才的绝佳机会。对于研究界的学者来说，这也是一个展示他们的科研成果、促进新技术商业化和广泛传播的恰当时机。本赛道对于人工智能赋能教育产业的从业者和研究学者来说，都是一个交流经验、分享成果、获得反馈的良好平台。
征文范围
AI-assisted and Interactive Technologies in an Educational Context: Data-driven processing techniques (educational data mining, deep learning, machine learning); Knowledge representation and reasoning; Generative AI; Semantic web technologies; Multi-agent architectures; Tangible interfaces, Wearables; Natural language processing and speech technologies; Virtual and augmented reality.
Modeling and Representation: Models of learners, including open learner models; facilitators, tasks and problem-solving processes; Models of groups and communities for learning; Modeling motivation, metacognition, and affective aspects of learning; Ontological modeling; Computational thinking and model-building; Representing and analyzing activity flow and discourse during learning; Representing and modeling 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 modeling (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.
AI Literacy: Skills and knowledge that enable individuals to understand, use, and critically evaluate AI; Definitions of AI literacy; Learning to use AI; Developing a basic understanding of how AI works; Learning to communicate and collaborate with AI; learning to live with AI, Understanding limitations and problems of AI.
AIED for Development: Focuses on leveraging AI technology to address and improve various aspects of development in societies and education, particularly in low and middle-income countries; AIED Divide; AIED Unplugged; Low-cost solutions; Low-tech solutions; Frugal Innovation; Jugaad Innovation.
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.
Human-AI Partnership: Shared decision making between systems and users that promote agency and improve learning.
AI in Ed for Theory: Using bottom-up and top-down approaches to analyze data in order to inform learning theories and gain better understanding of the socio-cognitive nature of learning.
投稿须知
投稿要求：
All submissions will be reviewed by three members of the program committee, followed by a metareview conducted by a senior member of the program committee (all double-masked) to meet rigorous academic standards of publication. processing techniques.
Papers will be reviewed for relevance, novelty, technical soundness, significance and clarity of presentation. It is important to note that the work presented should not have been published previously or be under consideration in other conferences of journals. Any paper caught in double submission will be rejected without review. The review process is documented in detail at https://tinyurl.com/mprfusvp.
提交格式：
All submissions must be in Springer format. Papers that do not use the required format may be rejected without review. Authors should consult Springer’s authors’ guidelines and use their proceedings templates, either for LaTeX or for Word, for the preparation of their papers. Springer encourages authors to include their ORCIDs in their papers. Submissions are handled via EasyChair.
论文要求长度：
Full papers (14 pages including references; for a long oral presentation)
Short papers (8 pages including references; for a short oral presentation)
重要日期
Abstracts due: January 29, 2024
Papers due: February 5, 2024
Notification of acceptance to authors: March 13th, 2024
Camera-ready paper due: April 29th, 2024
Conference: July 8 – 12, 2024
All deadlines are anywhere on earth (AoE). Please adhere to these deadlines as there will NOT be any extensions to the above dates forfull and short submissions to the main track of the conference.
组织委员会
General Chairs：
Olga C. Santos, UNED, Spain
Ig Bittencourt, Federal University of Alagoas, Brazil
Program Co-chairs:
Andrew Olney, University of Memphis, USA
Irene-Angelica Chounta, University of Duisburg-Essen, Germany
Zitao Liu, Jinan University, China
Local Chairs:
Rafael Ferreira Leite de Mello, CESAR and Federal Rural University of Pernambuco, Brazil
Taciana Pontual, Federal Rural University of Pernambuco, Brazil
