Invited speakers

Nikol Rummel | (Digital) Learning Sciences

Lehrstuhl für Pädagogische Psychologie, Ruhr-Universität Bochum Universitätsstraße, Germany

Francesco Mondada | Robots in Education

École Polytechnique Fédérale de Lausanne, Switzerland

Gautam Biswas (Vanderbilt University, USA) | Betty’s Brain: A Learning by Teaching Environment for Middle School Science Classrooms

Abstract: Over several years, our research team has developed Betty’s Brain, a multi-agent environment that utilizes the learning-by-teaching paradigm to help middle school students learn science. In Betty’s Brain, students teach a virtual Teachable Agent (TA) called Betty using a visual causal map representation. Once taught, Betty, can answer questions, explain her answers, and when requested by the student take quizzes, which are a set of questions created and graded by a mentor agent named Mr. Davis. The TA’s quiz performance helps students indirectly assess their own knowledge, and it also motivates them to learn more and improve their TA’s quiz scores. Overall, the learning and teaching task is complex, open-ended, and choice-rich. Thus, learners must employ a number of cognitive and metacognitive strategies to succeed in their tasks. At the cognitive level, they need to identify, understand, and represent important information from online resources in the causal map format, and use the affordances of the system to assess Betty’s progress using the quiz results. In terms of strategies, they must decide when and how to acquire information, build and modify the causal map they are creating to teach Betty, check Betty’s progress, reflect on their own understanding of both the science knowledge and the evolving causal map structure, and seek help when necessary. Their cognitive and metacognitive activities are scaffolded through dialogue and feedback provided by Betty and Mr. Davis. This feedback aims to help students progress in their learning, teaching, and monitoring tasks.
Experimental studies run in middle school classrooms show that students learn science content and do develop some metacognitive strategies through interactions with Betty and Mr. Davis. However, a number of students fail to complete their teaching task because they lack an understanding of the cognitive and metacognitive skills they need to become successful learners. In this talk, I will discuss the Betty’s Brain system, the data mining techniques we have developed to analyze students’ learning behaviors, and then discuss how we translate this understanding to develop better conversational structures to help students develop the cognitive and metacognitive skills they need to achieve success in their learning task.

Bio: Gautam Biswas is a Cornelius Vanderbilt Professor of Engineering, a Professor of Computer Science and Engineering in the EECS Department, and a Senior Research Scientist at the Institute for Software Integrated Systems, Vanderbilt University. He conducts research in intelligent systems with primary interests in modeling and simulation, analysis of complex embedded systems, data mining, and Open-Ended Learning Environments (CBLEs) for STEM disciplines. The most notable project in this area is the Teachable Agents project, where students learn science by building causal models of scientific processes. His work on learning environments has exploited the synergy between computational thinking ideas and STEM concepts and practices to help students learn STEM topics by building simulation models. He has also developed innovative educational data mining techniques for studying students learning behaviors and linking them to metacognitive strategies. For his work in data mining for diagnosis, he received the NASA 2011 Aeronautics Research Mission Directorate Technology and Innovation Group Award for Vehicle Level Reasoning Systems.
Prof. Biswas has over 650 refereed publications, and his research has been supported by funding from ARL, NASA, NSF, DARPA, and the US Department of Education. He is an associate editor of Metacognition and Learning and the IEEE Transactions on Learning Technologies. He is a fellow of the IEEE and the Prognostics and Health Management Society, and member of the AAAI, AAAS, ACM, AIED, EDM, ISLS, LAK, and the Sigma Xi Research Societies.


Tanja Kaser | Student Modelling

Stanford University

Joakim Gustafson (KTH, Sweden) | Towards situated interaction with social robots

Abstract: Professor Gustafson will present the work done on social robots at KTH. He will describe their efforts in developing the social robot platform Furhat and methods for interpreting and generating multimodal attention and turntaking behaviours, with a special focus on multiparty interactions. Finally, he will describe the work done on mutual gaze and joint attention in human-robot collaboration on assembly tasks.

Bio: Joakim Gustafson (KTH) is a professor in speech technology and head of the department of Speech, Music and Hearing. He has been a prolific researcher and active systems developer of spoken and multimodal dialogue systems since 1993. He has an industrial background from Telia Research where he led the research work of the EU project NICE, that developed a computer game where kids could interact with animated 3D characters using a combination of speech and gestures. He currently has three research projects where social robots act as third-hand helpers in assembly, social skills coaches for autistic children and companions for the elderly with the task of detecting early signs of dementia. ​

Luis Pietro | Classroom Orchestration

Talinn University, Estonia