LEARNING WHILE HOLDING A CONVERSATION WITH A COMPUTER
Arthur C. Graesser, Zhijun Lu, Moon Gee Jeon, Bethany McDaniel · 2005
Some of the recent electronic learning environments have moved beyond the conventional delivery of text, multimedia, and objective tests. There are systems with animated conversational agents, intelligent adaptive tutoring, interactive simulations, and other features designed to engage learners and promote deeper comprehension. One system is AutoTutor, a learning environment that tutors students by holding a conversation in natural language. AutoTutor’s design was inspired by explanation-based constructivist theories of learning, intelligent tutoring systems that adaptively respond to student knowledge, and empirical research on dialogue patterns in tutorial discourse. AutoTutor presents challenging questions and then engages in mixed initiative dialogue that guides the student in building an answer. It provides feedback to the student on what the student types in (positive, neutral, negative feedback), pumps the student for more information, prompts the student to fill in missing words, gives hints, fills in missing information, identifies and