Biswas, Gautam


Using Multiple Representations to Simultaneously Learn Computational Thinking and Middle School Science

AAAI Conferences

Computational Thinking (CT) is considered a core competency in problem formulation and problem solving. We have developed the Computational Thinking using Simulation and Modeling (CTSiM) learning environment to help middle school students learn science and CT concepts simultaneously. In this paper, we present an approach that leverages multiple linked representations to help students learn by constructing and analyzing computational models of science topics. Results from a recent study show that students successfully use the linked representations to become better modelers and learners.


Using the Dempster-Shafer Scheme in a Diagnostic Expert System Shell

arXiv.org Artificial Intelligence

This paper discusses an expert system shell that integrates rule-based reasoning and the Dempster-Shafer evidence combination scheme. Domain knowledge is stored as rules with associated belief functions. The reasoning component uses a combination of forward and backward inferencing mechanisms to allow interaction with users in a mixed-initiative format.


Modeling Learner’s Cognitive and Metacognitive Strategies in an Open-Ended Learning Environment

AAAI Conferences

The Betty’s Brain computer-based learning system provides an open-ended and choice-rich environment for science learning. Using the learning-by-teaching paradigm paired with feedback and support provided by two pedagogical agents, the system also promotes the development of self-regulated learning strategies to support preparation for future learning. We apply metacognitive learning theories and experiential analysis to interpret the results from previous classroom studies. We propose an integrated cognitive and metacognitive model for effective, self-regulated student learning in the Betty’s Brain environment, and then apply this model to interpret and analyze common suboptimal learning strategies students apply during their learning. This comparison is used to derive feedback for helping learners overcome these difficulties and adopt more effective strategies for regulating their learning. Preliminary results demonstrate that students who were responsive to the feedback had better learning performance.


Reports of the AAAI 2010 Fall Symposia

AI Magazine

The Association for the Advancement of Artificial Intelligence was pleased to present the 2010 Fall Symposium Series, held Thursday through Saturday, November 11-13, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the eight symposia are as follows: (1) Cognitive and Metacognitive Educational Systems; (2) Commonsense Knowledge; (3) Complex Adaptive Systems: Resilience, Robustness, and Evolvability; (4) Computational Models of Narrative; (5) Dialog with Robots; (6) Manifold Learning and Its Applications; (7) Proactive Assistant Agents; and (8) Quantum Informatics for Cognitive, Social, and Semantic Processes. The highlights of each symposium are presented in this report.


Reports of the AAAI 2010 Fall Symposia

AI Magazine

The Association for the Advancement of Artificial Intelligence was pleased to present the 2010 Fall Symposium Series, held Thursday through Saturday, November 11-13, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the eight symposia are as follows: (1) Cognitive and Metacognitive Educational Systems; (2) Commonsense Knowledge; (3) Complex Adaptive Systems: Resilience, Robustness, and Evolvability; (4) Computational Models of Narrative; (5) Dialog with Robots; (6) Manifold Learning and Its Applications; (7) Proactive Assistant Agents ; and (8) Quantum Informatics for Cognitive, Social, and Semantic Processes. The highlights of each symposium are presented in this report.


Modeling and Measuring Self-Regulated Learning in Teachable Agent Environments

AAAI Conferences

Our learning by teaching environment has students take on the role and responsibilities of a teacher to a virtual student named Betty. The environment is structured so that successfully instructing their teachable agent requires the students to learn and understand science topics for themselves. This process is supported by adaptive scaffolding and feedback from the system. This feedback is instantiated through the interactions with the teachable agent and a mentor agent, named Mr. Davis. This paper provides an overview of two studies that were conducted with 5th grade science students and a description of the analysis techniques that we have developed for interpreting students’ activities in this learning environment.


Preface: Meta-Cognitive Educational Systems: One Step Forward

AAAI Conferences

The AAAI Fall Symposium on Meta-Cognitive Educational Systems: One Step Forward is the second edition of the successful AAAI Fall 2009 Symposium with the same name. The idea for the first symposium stemmed from several theoretical, conceptual, empirical, and applied considerations about the role of metacognition and self-regulation when learning with computer based learning eEnvironments (CBLEs). This symposium aims to provide a com- prehensive definition of meta-cognitive educational systems that is inclusive of the theoretical, architectural, and educa- tional aspects of this field.


Reports of the AAAI 2009 Fall Symposia

AI Magazine

The Association for the Advancement of Artificial Intelligence was pleased to present the 2009 Fall Symposium Series, held Thursday through Saturday, November 5–7, at the Westin Arlington Gateway in Arlington, Virginia. The Symposium Series was preceded on Wednesday, November 4 by a one-day AI funding seminar. The titles of the seven symposia were as follows: (1) Biologically Inspired Cognitive Architectures, (2) Cognitive and Metacognitive Educational Systems, (3) Complex Adaptive Systems and the Threshold Effect: Views from the Natural and Social Sciences, (4) Manifold Learning and Its Applications, (5) Multirepresentational Architectures for Human-Level Intelligence, (6) The Uses of Computational Argumentation, and (7) Virtual Healthcare Interaction.


Reports of the AAAI 2009 Fall Symposia

AI Magazine

The Association for the Advancement of Artificial Intelligence was pleased to present the 2009 Fall Symposium Series, held Thursday through Saturday, November 5–7, at the Westin Arlington Gateway in Arlington, Virginia. The Symposium Series was preceded on Wednesday, November 4 by a one-day AI funding seminar. The titles of the seven symposia were as follows: (1) Biologically Inspired Cognitive Architectures, (2) Cognitive and Metacognitive Educational Systems, (3) Complex Adaptive Systems and the Threshold Effect: Views from the Natural and Social Sciences, (4) Manifold Learning and Its Applications, (5) Multirepresentational Architectures for Human-Level Intelligence, (6) The Uses of Computational Argumentation, and (7) Virtual Healthcare Interaction.


Promoting Motivation and Self-Regulated Learning Skills through Social Interactions in Agent-based Learning Environments

AAAI Conferences

We have developed computer environments that support learning by teaching and the use of self regulated learning (SRL) skills through interactions with virtual agents. More specifically, students teach a computer agent, Betty, and can monitor her progress by asking her questions and getting her to take quizzes. The system provides SRL support via dialog-embedded prompts by Betty, the teachable agent, and Mr. Davis, the mentor agent. Our primary goals have been to support learning in complex science domains and facilitate development of metacognitive skills. More recently, we have also employed sequence analysis schemes and hidden Markov model (HMM) methods for assigning context to and deriving aggregated student behavior sequences from activity data. These techniques allow us to go beyond analyses of individual behaviors, instead examining how these behaviors cohere in larger patterns. We discuss the information derived from these models, and draw inferences on students’ use of self-regulated learning strategies.