Affiliations: Center for the Study of Language and Information,
Stanford University, 210 Panama Street, Stanford, CA 94305-4115, USA. E-mail:
{ponbarry, schultzk, ebratt, bzack, peters}@csli.stanford.edu
Abstract: In designing and building tutorial dialogue systems it is important
not only to understand the tactics employed by human tutors but also to
understand how tutors decide when to use various tactics. We argue that these
decisions are based not only on student problem-solving steps and the content
of student utterances, but also on the meta-communicative information conveyed
through spoken utterances (e.g., pauses, disfluencies, intonation). Since this
information is often infrequent or unavailable in typed input, tutorial
dialogue systems with speech interfaces have the potential to be more effective
than those without. This paper gives an overview of the Spoken Conversational
Tutor (SCoT) that we have built and describes how we are beginning to make use
of spoken language information in SCoT. Specifically, we describe a study aimed
at using meta-communicative information to gauge student uncertainty and
respond accordingly. In this study, we identify linguistic devices used by
human tutors when responding to utterances containing signals of uncertainty,
integrate these response strategies into two versions of SCoT, and evaluate
their relative effectiveness. Our main hypothesis – that tutors are more
effective if they use these linguistic devices in response to student
uncertainty – was not confirmed, but our secondary hypothesis –
that tutors using these linguistic devices are more effective than tutors that
do not use them – was supported by the results.
