At CALST (Co-study Group on Advanced Learning Science and Technology), we view learning as one of the most profound intellectual activities in human life. Our mission is to advance this critical intellectual endeavor through innovative research in artificial intelligence and beyond, focusing on the modeling and systematization of learning processes.
Mission Statement
Encourage In-depth Discussion: To encourage logical and in-depth discussion of the complexities of learning as an intellectual activity, and to promote wide-ranging debates within advanced learning science and technology, free from conventional constraints and excuses.
Enhancing Research Skills: To assist members in refining their research skills, emphasizing presentations and feedback that push the boundaries of conventional knowledge, with the goal of developing groundbreaking contributions to the field.
Facilitating Knowledge Exchange: To act as a nexus for the exchange of insights, methodologies, and research findings from diverse fields, understanding learning as both a pervasive activity in human endeavor and a phenomenon uniquely shaped by individual contexts and experiences.
Foster Collaboration: To cultivate a collaborative atmosphere in which the integration of perspectives from fields such as information technology, cognitive science, educational engineering, and practical educational methodologies is essential to a comprehensive understanding of learning.
Support Career Development: To provide a supportive network that navigates the broad and interdisciplinary implications of learning research across academia and industry, enabling members to confidently explore their career trajectories.
Research Topics
Recognizing the inherent complexity and multifaceted nature of learning, CALST embraces a wide range of research topics that reflect our interdisciplinary ethos. These include:
Artificial Intelligence in Education: Exploring the potential of AI to customize and enrich learning experiences, with a focus on its ability to adapt to and support the diverse natural learning processes of individuals.
Knowledge Engineering for Learning: To develop tools and technologies, inspired by achievements in knowledge engineering and applied ontology, to support and enhance learning, with a focus on intelligent tutoring systems and adaptive learning environments.
Learning Sciences and Engineering: To create an ecosystem that uses learning sciences findings to formulate hypotheses that accelerate learning processes, and to develop educational systems to test these theories and methods that improve learning effectiveness.
Cognitive Science Applications: Applying cognitive science theories to analyze and improve fundamental learning processes, emphasizing the ubiquity and diversity of learning across contexts and experiences.
Technology-Enhanced Learning: Exploring the transformative role of technology in learning, from virtual and augmented reality to mobile learning platforms and online collaboration tools, all aimed at improving educational outcomes and experiences.
Human-Computer Interaction (HCI) in Education: Developing educational technologies that prioritize effective human-computer interaction to enhance the learning experience, with a focus on user-friendly interfaces and interactions.
Learning Analytics and Educational Data Mining: Using analytics and machine learning to extract meaningful insights from educational data, with the goal of improving teaching practices and learning outcomes by understanding the diverse and situational characteristics of learning.
Through discussions related to these topics, CALST aims to encourage our members to cultivate innovative ideas and perspectives, fostering a rich, dynamic, and evolving environment of discussion and discovery.