From Dr. Philip Pavlik, Institute for Intelligent Systems and Department of Psychology. If you have a chance to go and hear about Betty’s Brain, I highly encourage it. This is a fantastic example of technology-supported/enhanced learning in an open-ended learning environment.
Betty’s Brain: An open-ended learning environment that helps middle school students develop metacognitive strategies for learning science
Dr. Gautam Biswas, Vanderbilt University
Wed March 27, 2013 4:00pm – 5:20pm Cog Sci Seminar – FIT 405
Over several years, our research team has developed Betty’s Brain, an open-ended 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 skills to achieve success. 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 quizzes. At the metacognitive level, 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 learning strategies as they interact with Betty and Mr. Davis. However, a number of students fail to complete their teaching task because they lack an understanding of a number of the cognitive and metacognitive skills needed to become successful learners. We discuss recent additions to the Betty’s Brain system, primarily a model-driven assessments methodology for characterizing and evaluating the students’ actions as they learn in the environment. Our goal is to make the scaffolding provided by the system more relevant to the student’s current learning activities. This translates to a context-relevant, mixed-initiative conversational format for adaptive scaffolding, and we demonstrate that this helps students develop the cognitive and metacognitive skills they need to achieve success in their learning task.
Gautam Biswas is a Professor of Computer Science, Computer Engineering, and Engineering Management in the EECS Department and a Senior Research Scientist at the Institute for Software Integrated Systems (ISIS) at Vanderbilt University. He has an undergraduate degree in Electrical Engineering from the Indian Institute of Technology (IIT) in Mumbai, India, and M.S. and Ph.D. degrees in Computer Science from Michigan State University in E. Lansing, MI.
Prof. Biswas conducts research in Intelligent Systems with interests in hybrid systems modeling, simulation, and analysis, and their applications in two primary directions: (1) diagnosis, prognosis, and fault-adaptive control; and (2) their applications to develop STEM learning environments in K-12 classrooms. The most notable project with educational applications is the Teachable Agents project, where students learn science by building causal models of natural processes. He has also developed innovative educational data mining techniques for studying students’ learning behaviors and linking them to metacognitive strategies. He is currently working on projects that combine computational thinking with visual programming to help K-12 students develop a deep understanding of STEM content using model-building and simulation, and then applying these models to address real-world problems. His research projects in embedded systems and learning environments has been supported by funding from NASA, NSF, DARPA, and the US Department of Education. In one of the projects, working on Data Mining techniques to enhance aircraft diagnostic models in conjunction with Honeywell International researchers (NASA NRA) he won the 2011 Aeronautics Research Mission Directorate Technology and Innovation Group Award for Vehicle Level Reasoning System. He has published extensively, and has over 300 refereed publications.
Dr. Biswas is an associate editor of the IEEE Transactions on Systems, Man, and Cybernetics, Prognostics and Health Management, Educational Technology and Society journal, International Journal of Educational Data Mining and the Journal of Metacognition and Learning. He is currently serving on the Executive committee of the Asia Pacific Society for Computers in Education, a member of Executive Board of the Artificial Intelligence in Education Society, and is the IEEE Computer Society representative to the Transactions on Learning Technologies steering committee. He is also serving as the Secretary/Treasurer for ACM Sigart.