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.

The eighteenth annual International Workshop on Principles of Diagnosis was held in Nashville, Tennessee, May 29–31, 2007. Papers presented at the workshop covered a variety of theories, principles, and computational techniques for diagnosis, monitoring, testing, reconfiguration, fault-adaptive control, and repair of complex systems. This year's workshop emphasized inter-actions and exchange of ideas and experiences between researchers and practitioners whose backgrounds included AI, control theory, systems engineering, software engineering, and related areas.

The eighteenth annual International Workshop on Principles of Diagnosis was held in Nashville, Tennessee, May 29–31, 2007. Papers presented at the workshop covered a variety of theories, principles, and computational techniques for diagnosis, monitoring, testing, reconfiguration, fault-adaptive control, and repair of complex systems. This year’s workshop emphasized inter-actions and exchange of ideas and experiences between researchers and practitioners whose backgrounds included AI, control theory, systems engineering, software engineering, and related areas.