Concluded in December, 2014
The JavaTutor project investigates human-human natural language tutorial dialogue as a model for human-computer tutorial dialogue. With a curricular focus of first-year post-secondary computer science education and a task focus of problem-solving dialogues, a corpora of human-human tutorial dialogues are collected, annotated with rich dialogue act tags, and then machine learning techniques automatically acquire the structure of effective tutorial dialogue.
The JavaTutor project is concerned with 1) designing rich dialogue act coding schemes for coding cognitive and affective dimensions of task-oriented tutorial dialogue interactions, and 2) learning hidden Markov models to discover the structure of task-oriented tutorial dialogue.
To learn more about this project, please visit the CEI website.