Intelligent Game-based Learning Environments
Recent years have seen a growing recognition of the transformative potential of game-based learning technologies. CEI is exploring intelligent game-based learning environments that leverage commercial game engines and provide intelligent tutoring systems’ adaptive pedagogical functionalities for creating highly effective customized learning experiences that maximize learning gains. CEI is also designing intelligent game-based learning environments that integrate affect, natural language, and speech technologies.
Affective Computing for Interactive Learning
Students’ emotions play a central role in their learning processes, and effective interaction between teachers and students is guided by teachers’ and students’ ability to accurately recognize one another’s affective states and to appropriately express affect. To improve computer-based learning environments’ ability to recognize and generate affect, CEI devises computational models of affect recognition (automatically recognizing students’ affective states) and affect expression (automatically generating appropriate affective responses).
Virtual Humans for Learning and Teaching
Intelligent virtual tutors are “embodied” artificial intelligence-driven characters that interact with students to provide engaging, personalized tutorial support. Also known as pedagogical agents, intelligent virtual tutors employ language, facial expressions, and gestures to create effective learning experiences for students. Interacting with students in virtual learning environments, intelligent virtual tutors provide multimodal explanations, interactive demonstrations, and problem-solving advice to improve learning.
Computational Models of Interactive Narrative
Narrative plays a central role in communication and cognition, and there is a growing interest in devising interactive storytelling environments that create engaging narrative experiences. With an emphasis on narrative-centered learning environments, CEI is designing decision-theoretic models of interactive narrative, devising narrative-centered pedagogical planners for narrative-centered learning environments, and creating goal recognition systems to monitor students’ problem-solving actions and predict their goals.
Natural Language Tutorial Dialogue
Human-human tutorial dialogue offers an excellent model for effective learning. By understanding the pedagogical mechanisms of human-human tutorial dialogue, CEI designs natural language tutorial dialogue systems that offer similar benefits. CEI conducts corpus studies of human-human tutorial dialogue to explore how learner characteristics influence the structure of tutorial dialogue, how human tutors balance cognitive and motivational scaffolding, and how these impact learning gains and self-efficacy gains.
Intelligent Multimodal Interfaces
Two complementary technologies leveraging artificial intelligence have emerged that afford significant opportunities for learning: intelligent user interfaces and multimodal interaction technologies. To promote effective learning through rich interactions, CEI is designing intelligent multimodal interfaces that enable students to create graphical representations to model physical phenomena that come to life as interactive media artifacts combining animation, sound, and narration.