2021 3rd International Workshop on Artificial Intelligence and Education will take place in Xian, China (中国西安) during November 19-21, 2021, sponsored by Xidian University, China, hosted by School of Telecommunications Engineering, Xidian University, supported by Université de Montréal, Canada, Okayama University, Japan, etc.
Inequity within and between countries continues to grow in the industrial age. Intelligent information technologies have been proposed to reduce this difference, but may instead increase the digital divide if applied without reflection. Education plays a central role in this problem, as it is one of the key approaches that could help to reduce this difference. However, further work is needed to understand how to provide equitable education for all, and many questions remain to be answered. What are the main barriers to providing educational opportunities to underserved teachers and learners? How can AI and advanced technologies help overcome these difficulties? How can this work be done ethically? In this conference we gather the collective intelligence of the community to think about this problem and provide innovative and creative solutions.
The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world. Topics of interest for submission include, but are not limited to:
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