Name
Abstract | ||
|---|---|---|
Building on previous work in this area, we provide a description and justification for a new way of identifying modes and mode switches in tutorial dialogues, part of a coding scheme involving 16 modes and 125 distinct dialogue acts. We also present preliminary results from an analysis of 1,438 human-annotated transcripts, consisting of more than 90,000 turns. Among other findings, this analysis shows subtle differences in the "mode architecture" of successful vs. less successful sessions, as judged by expert tutors. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-19773-9_101 | ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015 |
Keywords | Field | DocType |
Human tutorial dialogue, Dialogue mode, Data mining, Hybrid tutoring systems | Online tutoring,Architecture,Computer science,Dialogue acts,Coding (social sciences),Natural language processing,Artificial intelligence | Conference |
Volume | ISSN | Citations |
9112 | 0302-9743 | 2 |
PageRank | References | Authors |
0.39 | 4 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Donald Morrison | 1 | 6 | 2.90 |
| Benjamin D. Nye | 2 | 57 | 10.62 |
| Vasile Rus | 3 | 973 | 134.69 |
| Sarah Snyder | 4 | 2 | 0.39 |
| Jennifer Boller | 5 | 2 | 0.39 |
| Kenneth Miller | 6 | 2 | 0.39 |