2022 4th International Workshop on Artificial Intelligence and Education (WAIE 2022) will take place in Xiamen, China during November 11-13, 2022.
AI has already been applied to education primarily in some tools that help develop skills and testing systems. As AI educational solutions continue to mature, the hope is that AI can help fill needs gaps in learning and teaching and allow schools and teachers to do more than ever before. AI can drive efficiency, personalization and streamline admin tasks to allow teachers the time and freedom to provide understanding and adaptability—uniquely human capabilities where machines would struggle. By leveraging the best attributes of machines and teachers, the vision for AI in education is one where they work together for the best outcome for students. Since the students of today will need to work in a future where AI is the reality, it’s important that our educational institutions expose students to and use the technology.
Call for Papers
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
