Keynote Speakers

Prof. Yanyan Li, Faculty of Education, Beijing Normal University (BNU), China

李艳燕教授，北京师范大学教育学部，中国

Research Area: Educational Applications of Artificial Intelligence, Intelligent Robot Technology Innovation Practice, Computer Supported Collaborative Learning

Title: Learning Analytics for Intelligent Scaffolding Design and Application in Blended Learning Environments

Abstract:

The blended learning environments have been widely used in both formal and informal education. Nevertheless, due to factors such as low self-regulation and lack of social presence, students may fail in blended learning environments. Therefore, it is believed that providing external support, for example intelligent scaffolding during the learning process is important. How to design and develop intelligent scaffolding to improve and optimize the performance and harvest of teachers and students in blended learning environments becomes a core issue in many fields. Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts. With a large amount of data generated in the learning process, learning analytics provides possibilities to develop intelligent scaffolding that could provide real-time awareness of and interventions to the learning process via artificial intelligence. This report will introduce the theoretical models, self-developed tools and applications of intelligent learning scaffolding to give a glimpse of how the intelligent scaffolding works in diverse contexts. Furthermore, the trends of artificial intelligence in education are also discussed.

Assoc. Prof. Yu Lu, Faculty of Education, Beijing Normal University (BNU), China

卢宇副教授，北京师范大学教育学院，中国

Research Area: Learner Modeling, Robotics for Education, Intelligent Tutoring System, Educational Data Mining, Data Analytics and Ubiquitous Computing

Title: AI-Driven Intelligent Tutoring System in Education

Abstract:

Intelligent tutoring system (ITS) refers to the system that provides immediate and customized instruction or feedback to learners. Driven by the latest AI techniques and the large demands from the education community, new ITS design could better model learners, provide learners the automatic grading service and the personalized learning guidance. This talk will discuss the key AI techniques required, and then present the latest ITS developed by the advanced innovation center for future education at Beijing Normal University.

Assoc. Prof. Rosmayati Mohemad, Universiti Malaysia Terengganu, Malaysia

Rosmayati Mohemad副教授，马来西亚登嘉楼大学，马来西亚

Research Area: Decision Support System, Ontology Modelling, Knowledge Engineering  

Title: An Ontology Model For The Analysis And Recommendation Of Activities For Children With Learning Disabilities

Abstract:

Knowledge-based technology with complete access to useful information is critical to supporting decision-making and solving complex problems in a variety of fields such as management, medicine, business, education, and others. Current knowledge-based systems, on the other hand, lack an explicit representation of knowledge, limiting the effective sharing of knowledge between domain experts and general users. These systems are also difficult to maintain because the addition and modification of new knowledge always necessitates the involvement of software experts. Ontology-based knowledge representation is investigated in the context of special education, as little attention has been paid to specific learning disabilities such as dyslexia, dysgraphia, and dyscalculia. As such, this research aims to capture domain knowledge in special education, represent it using an ontology-based approach, and make it useful for decision-making process.

Assoc. Prof. Soraya Garcia-Esteban, Faculty of Education | University of Alcala (Spain), Spain

Research Area: Telecollaboration, EAP, Teacher Training, Computer-Assisted Language Learning, EAP, key / Global /Intercultural Competence

Title: Integrating Virtual Exchange for competence development in Higher Education

Abstract:

Virtual Exchange has been acknowledged to broaden academic horizons and to develop teaching and learning 21st century skills. Based on recent research and empirical study, this communication aims to present a methodological framework for the appropriate integration of global and key competences in higher education with collaborative educational technology.