Viewing student affect and learning through classroom observation and physical sensors

Toby Dragon; Ivon Arroyo; Beverly P. Woolf; Winslow Burleson; Rana El Kaliouby; Hoda Eydgahi

doi:10.1007/978-3-540-69132-7_8

Viewing student affect and learning through classroom observation and physical sensors

Toby Dragon, Ivon Arroyo, Beverly P. Woolf, Winslow Burleson, Rana El Kaliouby, Hoda Eydgahi

Computing, Informatics and Decision Systems Engineering, School of (CIDSE)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

47 Scopus citations

Abstract

We describe technology to dynamically collect information about students' emotional state, including human observation and real-time multi-modal sensors. Our goal is to identify physical behaviors that are linked to emotional states, and then identify how these emotional states are linked to student learning. This involves quantitative field observations in the classroom in which researchers record the behavior of students who are using intelligent tutors. We study the specific elements of learner's behavior and expression that could be observed by sensors. The long-term goal is to dynamically predict student performance, detect a need for intervention, and determine which interventions are most successful for individual students and the learning context (problem and emotional state).

Original language	English (US)
Title of host publication	Intelligent Tutoring Systems - 9th International Conference, ITS 2008, Proceedings
Publisher	Springer Verlag
Pages	29-39
Number of pages	11
ISBN (Print)	3540691308, 9783540691303
DOIs	https://doi.org/10.1007/978-3-540-69132-7_8
State	Published - 2008
Event	9th International Conference on Intelligent Tutoring Systems, ITS 2008 - Montreal, QC, Canada Duration: Jun 23 2008 → Jun 27 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5091 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	9th International Conference on Intelligent Tutoring Systems, ITS 2008
Country	Canada
City	Montreal, QC
Period	6/23/08 → 6/27/08

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-69132-7_8

Fingerprint Dive into the research topics of 'Viewing student affect and learning through classroom observation and physical sensors'. Together they form a unique fingerprint.

Cite this

Dragon, T., Arroyo, I., Woolf, B. P., Burleson, W., El Kaliouby, R., & Eydgahi, H. (2008). Viewing student affect and learning through classroom observation and physical sensors. In Intelligent Tutoring Systems - 9th International Conference, ITS 2008, Proceedings (pp. 29-39). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5091 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-69132-7_8

Viewing student affect and learning through classroom observation and physical sensors. / Dragon, Toby; Arroyo, Ivon; Woolf, Beverly P.; Burleson, Winslow; El Kaliouby, Rana; Eydgahi, Hoda.

Intelligent Tutoring Systems - 9th International Conference, ITS 2008, Proceedings. Springer Verlag, 2008. p. 29-39 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5091 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Dragon, T, Arroyo, I, Woolf, BP, Burleson, W, El Kaliouby, R & Eydgahi, H 2008, Viewing student affect and learning through classroom observation and physical sensors. in Intelligent Tutoring Systems - 9th International Conference, ITS 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5091 LNCS, Springer Verlag, pp. 29-39, 9th International Conference on Intelligent Tutoring Systems, ITS 2008, Montreal, QC, Canada, 6/23/08. https://doi.org/10.1007/978-3-540-69132-7_8

Dragon T, Arroyo I, Woolf BP, Burleson W, El Kaliouby R, Eydgahi H. Viewing student affect and learning through classroom observation and physical sensors. In Intelligent Tutoring Systems - 9th International Conference, ITS 2008, Proceedings. Springer Verlag. 2008. p. 29-39. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-69132-7_8

Dragon, Toby ; Arroyo, Ivon ; Woolf, Beverly P. ; Burleson, Winslow ; El Kaliouby, Rana ; Eydgahi, Hoda. / Viewing student affect and learning through classroom observation and physical sensors. Intelligent Tutoring Systems - 9th International Conference, ITS 2008, Proceedings. Springer Verlag, 2008. pp. 29-39 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{94984c2a24574a189f736bdfd4d680fa,

title = "Viewing student affect and learning through classroom observation and physical sensors",

abstract = "We describe technology to dynamically collect information about students' emotional state, including human observation and real-time multi-modal sensors. Our goal is to identify physical behaviors that are linked to emotional states, and then identify how these emotional states are linked to student learning. This involves quantitative field observations in the classroom in which researchers record the behavior of students who are using intelligent tutors. We study the specific elements of learner's behavior and expression that could be observed by sensors. The long-term goal is to dynamically predict student performance, detect a need for intervention, and determine which interventions are most successful for individual students and the learning context (problem and emotional state).",

author = "Toby Dragon and Ivon Arroyo and Woolf, {Beverly P.} and Winslow Burleson and {El Kaliouby}, Rana and Hoda Eydgahi",

year = "2008",

doi = "10.1007/978-3-540-69132-7_8",

language = "English (US)",

isbn = "3540691308",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "29--39",

booktitle = "Intelligent Tutoring Systems - 9th International Conference, ITS 2008, Proceedings",

}

TY - GEN

T1 - Viewing student affect and learning through classroom observation and physical sensors

AU - Dragon, Toby

AU - Arroyo, Ivon

AU - Woolf, Beverly P.

AU - Burleson, Winslow

AU - El Kaliouby, Rana

AU - Eydgahi, Hoda

PY - 2008

Y1 - 2008

N2 - We describe technology to dynamically collect information about students' emotional state, including human observation and real-time multi-modal sensors. Our goal is to identify physical behaviors that are linked to emotional states, and then identify how these emotional states are linked to student learning. This involves quantitative field observations in the classroom in which researchers record the behavior of students who are using intelligent tutors. We study the specific elements of learner's behavior and expression that could be observed by sensors. The long-term goal is to dynamically predict student performance, detect a need for intervention, and determine which interventions are most successful for individual students and the learning context (problem and emotional state).

AB - We describe technology to dynamically collect information about students' emotional state, including human observation and real-time multi-modal sensors. Our goal is to identify physical behaviors that are linked to emotional states, and then identify how these emotional states are linked to student learning. This involves quantitative field observations in the classroom in which researchers record the behavior of students who are using intelligent tutors. We study the specific elements of learner's behavior and expression that could be observed by sensors. The long-term goal is to dynamically predict student performance, detect a need for intervention, and determine which interventions are most successful for individual students and the learning context (problem and emotional state).

UR - http://www.scopus.com/inward/record.url?scp=70349805480&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70349805480&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-69132-7_8

DO - 10.1007/978-3-540-69132-7_8

M3 - Conference contribution

AN - SCOPUS:70349805480

SN - 3540691308

SN - 9783540691303

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 29

EP - 39

BT - Intelligent Tutoring Systems - 9th International Conference, ITS 2008, Proceedings

PB - Springer Verlag

T2 - 9th International Conference on Intelligent Tutoring Systems, ITS 2008

Y2 - 23 June 2008 through 27 June 2008

ER -