Abstract: While human tutors typically interact with students using spoken dialogue, most computer dialogue tutors are text-based. To evaluate the utility of adding spoken language capabilities to dialogue tutors, we have developed ITSPOKE, a speech-based dialogue system that uses the Why2-Atlas text-based tutoring system as its "back-end.'' In ITSPOKE, a student first types a natural language answer to a qualitative physics problem. ITSPOKE then engages the student in a spoken dialogue to provide feedback and correct misconceptions, and to elicit more complete explanations.

In this talk, I will first describe ITSPOKE. I will then present the results of two experiments comparing typed and spoken tutoring dialogues, one in a human-human scenario, and another in the ITSPOKE human-computer scenario. Our main results are that changing the modality from text to speech caused large differences in the learning gains, efficiency and superficial dialogue characteristics of human tutoring, but for our first version of ITSPOKE, it made less difference.