AutoTutor's Log Files and Categories of Language and Discourse

Johanna Marineau; Andrew Olney; Max Louwerse; Natalie Person; Brent Olde; Suresh Susarla; Patrick Chipman; Art Graesser; Tutoring Research Group

AutoTutor's Log Files and Categories of Language and Discourse

Johanna Marineau, Andrew Olney, Max Louwerse, Natalie Person, Brent Olde, Suresh Susarla, Patrick Chipman, Art Graesser, Tutoring Research Group

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

AutoTutor is a computer tutor that interacts with students in a multi-turn tutorial dialog with natural language. AutoTutor has been developed for computer literacy and conceptual physics, showing learning gains of .6
standard deviation units. This paper documents AutoTutor's log files. The log files record pertinent information about each turn that the student contributes, including syntactic parsing, speech act segmentation and classification,
coverage of the expected content, the quality of the student contribution, and other dimensions of language and discourse. The log file also records relevant information about the selection of tutor’s dialogue moves through the
Dialogue Advance Network (DAN).

Original language	English
Title of host publication	Workshop W6 on Empirical Methods for Tutorial Dialogue Systems
Subtitle of host publication	Held during ITS 2002, the Sixth International Conference on Intelligent Tutoring Systems San Sebastian, June 4, 2002
Editors	Carolyn P. Rose, Vincent Aleven
Pages	85-92
Publication status	Published - 2002
Externally published	Yes
Event	6th International Conference on Intelligent Tutoring Systems - San Sebastian, Spain Duration: 2 Jul 2002 → 7 Jul 2002 Conference number: 6

Conference

Conference	6th International Conference on Intelligent Tutoring Systems
Abbreviated title	ITS 2002
Country/Territory	Spain
City	San Sebastian
Period	2/07/02 → 7/07/02

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https://www.researchgate.net/profile/Oliver_Lemon/publication/220029559_Targeted_Help_Embedded_training_and_methods_for_evaluation/links/0fcfd50c5f9dedf500000000/Targeted-Help-Embedded-training-and-methods-for-evaluation.pdf

Cite this

Marineau, J., Olney, A., Louwerse, M., Person, N., Olde, B., Susarla, S., Chipman, P., Graesser, A., & Group, T. R. (2002). AutoTutor's Log Files and Categories of Language and Discourse. In C. P. Rose, & V. Aleven (Eds.), Workshop W6 on Empirical Methods for Tutorial Dialogue Systems: Held during ITS 2002, the Sixth International Conference on Intelligent Tutoring Systems San Sebastian, June 4, 2002 (pp. 85-92) https://www.researchgate.net/profile/Oliver_Lemon/publication/220029559_Targeted_Help_Embedded_training_and_methods_for_evaluation/links/0fcfd50c5f9dedf500000000/Targeted-Help-Embedded-training-and-methods-for-evaluation.pdf

@inproceedings{8628ee4add204966a0e3345910a79951,

title = "AutoTutor's Log Files and Categories of Language and Discourse",

abstract = "AutoTutor is a computer tutor that interacts with students in a multi-turn tutorial dialog with natural language. AutoTutor has been developed for computer literacy and conceptual physics, showing learning gains of .6 standard deviation units. This paper documents AutoTutor's log files. The log files record pertinent information about each turn that the student contributes, including syntactic parsing, speech act segmentation and classification, coverage of the expected content, the quality of the student contribution, and other dimensions of language and discourse. The log file also records relevant information about the selection of tutor{\textquoteright}s dialogue moves through the Dialogue Advance Network (DAN).",

author = "Johanna Marineau and Andrew Olney and Max Louwerse and Natalie Person and Brent Olde and Suresh Susarla and Patrick Chipman and Art Graesser and Group, {Tutoring Research}",

year = "2002",

language = "English",

pages = "85--92",

editor = "Rose, {Carolyn P.} and Vincent Aleven",

booktitle = "Workshop W6 on Empirical Methods for Tutorial Dialogue Systems",

note = "6th International Conference on Intelligent Tutoring Systems, ITS 2002 ; Conference date: 02-07-2002 Through 07-07-2002",

}

Marineau, J, Olney, A, Louwerse, M, Person, N, Olde, B, Susarla, S, Chipman, P, Graesser, A & Group, TR 2002, AutoTutor's Log Files and Categories of Language and Discourse. in CP Rose & V Aleven (eds), Workshop W6 on Empirical Methods for Tutorial Dialogue Systems: Held during ITS 2002, the Sixth International Conference on Intelligent Tutoring Systems San Sebastian, June 4, 2002. pp. 85-92, 6th International Conference on Intelligent Tutoring Systems, San Sebastian, Spain, 2/07/02. <https://www.researchgate.net/profile/Oliver_Lemon/publication/220029559_Targeted_Help_Embedded_training_and_methods_for_evaluation/links/0fcfd50c5f9dedf500000000/Targeted-Help-Embedded-training-and-methods-for-evaluation.pdf>

AutoTutor's Log Files and Categories of Language and Discourse. / Marineau, Johanna; Olney, Andrew; Louwerse, Max et al.
Workshop W6 on Empirical Methods for Tutorial Dialogue Systems: Held during ITS 2002, the Sixth International Conference on Intelligent Tutoring Systems San Sebastian, June 4, 2002. ed. / Carolyn P. Rose; Vincent Aleven. 2002. p. 85-92.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - AutoTutor's Log Files and Categories of Language and Discourse

AU - Marineau, Johanna

AU - Olney, Andrew

AU - Louwerse, Max

AU - Person, Natalie

AU - Olde, Brent

AU - Susarla, Suresh

AU - Chipman, Patrick

AU - Graesser, Art

AU - Group, Tutoring Research

N1 - Conference code: 6

PY - 2002

Y1 - 2002

N2 - AutoTutor is a computer tutor that interacts with students in a multi-turn tutorial dialog with natural language. AutoTutor has been developed for computer literacy and conceptual physics, showing learning gains of .6 standard deviation units. This paper documents AutoTutor's log files. The log files record pertinent information about each turn that the student contributes, including syntactic parsing, speech act segmentation and classification, coverage of the expected content, the quality of the student contribution, and other dimensions of language and discourse. The log file also records relevant information about the selection of tutor’s dialogue moves through the Dialogue Advance Network (DAN).

AB - AutoTutor is a computer tutor that interacts with students in a multi-turn tutorial dialog with natural language. AutoTutor has been developed for computer literacy and conceptual physics, showing learning gains of .6 standard deviation units. This paper documents AutoTutor's log files. The log files record pertinent information about each turn that the student contributes, including syntactic parsing, speech act segmentation and classification, coverage of the expected content, the quality of the student contribution, and other dimensions of language and discourse. The log file also records relevant information about the selection of tutor’s dialogue moves through the Dialogue Advance Network (DAN).

M3 - Conference contribution

SP - 85

EP - 92

BT - Workshop W6 on Empirical Methods for Tutorial Dialogue Systems

A2 - Rose, Carolyn P.

A2 - Aleven, Vincent

T2 - 6th International Conference on Intelligent Tutoring Systems

Y2 - 2 July 2002 through 7 July 2002

ER -

AutoTutor's Log Files and Categories of Language and Discourse

Abstract

Conference

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