Choosing when to interact with learners

In this paper, we describe a method for pedagogical agents to choose when to interact with learners in interactive learning environments. This method is based on observations of human tutors coaching students in on-line learning tasks. It takes into account the focus of attention of the learner, the learner’s current task, and expected time required to perform the task. A Bayesian network model combines evidence from eye gaze and interface actions to infer learner focus of attention. The attention model is combined with a plan recognizer to detect different types of learner difficulties such as confusion and indecision which warrant intervention. We plan to incorporate this capability into a pedagogical agent able to interact with learners in socially appropriate ways. Categories and Subject Descriptors I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence – Intelligent agents; H.5.2 [Information Interfaces and Presentation]: User Interfaces – Training, help and ...

• Type: Conference
• Year: 2004
• Where: IUI
• Authors: Lei Qu, Ning Wang, W. Lewis Johnson
• Keywords: IUI 2004, Learners, Learner’s Current Task, Pedagogical Agents, Software Engineering