Development and evaluation of a lesson authoring tool for AutoTutor

This paper describes the process of developing an Electronic Performance Support System (EPSS) for AutoTutor 3D. The new architecture of AutoTutor 3D has four models: Domain model, Student model, Tutor model and Interface model. To date, the complexity of authoring the scripts used by AutoTutor has presented a significant challenge. Creation of a tool to simplify this process gives us the ability to disseminate AutoTutor across many different domains. The tool was created using a rapid prototyping approach and incorporates real world case based scenarios based on actual teacher experience with the tool, and a point-and-query help system. This tool and the model for its design may inform the development of similar EPSSs in the future

Pedagogical Agents for Fostering Question-Asking Skills in Children

Question asking is an important tool for constructing academic knowledge, and a self-reinforcing driver of curiosity. However, research has found that question asking is infrequent in the classroom and children's questions are often superficial, lacking deep reasoning. In this work, we developed a pedagogical agent that encourages children to ask divergent-thinking questions, a more complex form of questions that is associated with curiosity. We conducted a study with 95 fifth grade students, who interacted with an agent that encourages either convergent-thinking or divergent-thinking questions. Results showed that both interventions increased the number of divergent-thinking questions and the fluency of question asking, while they did not significantly alter children's perception of curiosity despite their high intrinsic motivation scores. In addition, children's curiosity trait has a mediating effect on question asking under the divergent-thinking agent, suggesting that question-asking interventions must be personalized to each student based on their tendency to be curious.Comment: Accepted at CHI 202

The look and feel of a confident entailer

The paper presents a software system that embodies a lexico-syntactic approach to the task of Textual Entailment. Although the approach is based on a minimal set of resources it is highly confident. The architecture of the system is open and can be easily expanded with more and deeper processing modules. Results on a standard data set are presented

Modeling Cognition with Software Agents

We propose the use of autonomous software agents as cognitive models that generate testable hypotheses about human cognition. While such agents are typically produced to automate practical human tasks, they can be designed within the constraints of a psychological theory. As an example we describe an agent designed within global workspace theory that accommodates several other theories as well. We discuss various resulting hypotheses, including a new interpretation of the readiness potential data of Libet

Is it an Agent, or just a Program?: A Taxonomy for Autonomous Agents

The advent of software agents gave rise to much discussion of just what such an agent is, and of how they differ from programs in general. Here we propose a formal definition of an autonomous agent which clearly distinguishes a software agent from just any program. We also offer the beginnings of a natural kinds taxonomy of autonomous agents, and discuss possibilities for further classification. Finally, we discuss subagents and multiagent systems