Recognizing and responding to student affect

Beverly Woolf, Toby Dragon, Ivon Arroyo, David Cooper, Winslow Burleson, Kasia Muldner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper describes the use of wireless sensors to recognize student emotion and the use of pedagogical agents to respond to students with these emotions. Minimally invasive sensor technology has reached such a maturity level that students engaged in classroom work can us sensors while using a computer-based tutor. The sensors, located on each of 25 student's chair, mouse, monitor, and wrist, provide data about posture, movement, grip tension, facially expressed mental states and arousal. This data has demonstrated that intelligent tutoring systems can provide adaptive feedback based on an individual student's affective state. We also describe the evaluation of emotional embodied animated pedagogical agents and their impact on student motivation and achievement. Empirical studies show that students using the agents increased their math value, self-concept and mastery orientation.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages713-722
Number of pages10
Volume5612 LNCS
EditionPART 3
DOIs
StatePublished - 2009
Event13th International Conference on Human-Computer Interaction, HCI International 2009 - San Diego, CA, United States
Duration: Jul 19 2009Jul 24 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume5612 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other13th International Conference on Human-Computer Interaction, HCI International 2009
CountryUnited States
CitySan Diego, CA
Period7/19/097/24/09

Fingerprint

Students
Sensor
Intelligent Tutoring Systems
Wireless Sensors
Sensors
Empirical Study
Mouse
Monitor
Evaluation
Intelligent systems
Emotion
Feedback
Concepts
Movement

Keywords

  • Intelligent tutoring systems
  • Pedagogical agents
  • Student emotion
  • Wireless sensors

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Woolf, B., Dragon, T., Arroyo, I., Cooper, D., Burleson, W., & Muldner, K. (2009). Recognizing and responding to student affect. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 3 ed., Vol. 5612 LNCS, pp. 713-722). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5612 LNCS, No. PART 3). https://doi.org/10.1007/978-3-642-02580-8_78

Recognizing and responding to student affect. / Woolf, Beverly; Dragon, Toby; Arroyo, Ivon; Cooper, David; Burleson, Winslow; Muldner, Kasia.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5612 LNCS PART 3. ed. 2009. p. 713-722 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5612 LNCS, No. PART 3).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Woolf, B, Dragon, T, Arroyo, I, Cooper, D, Burleson, W & Muldner, K 2009, Recognizing and responding to student affect. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 3 edn, vol. 5612 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 5612 LNCS, pp. 713-722, 13th International Conference on Human-Computer Interaction, HCI International 2009, San Diego, CA, United States, 7/19/09. https://doi.org/10.1007/978-3-642-02580-8_78
Woolf B, Dragon T, Arroyo I, Cooper D, Burleson W, Muldner K. Recognizing and responding to student affect. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 3 ed. Vol. 5612 LNCS. 2009. p. 713-722. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). https://doi.org/10.1007/978-3-642-02580-8_78
Woolf, Beverly ; Dragon, Toby ; Arroyo, Ivon ; Cooper, David ; Burleson, Winslow ; Muldner, Kasia. / Recognizing and responding to student affect. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5612 LNCS PART 3. ed. 2009. pp. 713-722 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).
@inproceedings{0d31ede89db64ed8993c767487b3af65,
title = "Recognizing and responding to student affect",
abstract = "This paper describes the use of wireless sensors to recognize student emotion and the use of pedagogical agents to respond to students with these emotions. Minimally invasive sensor technology has reached such a maturity level that students engaged in classroom work can us sensors while using a computer-based tutor. The sensors, located on each of 25 student's chair, mouse, monitor, and wrist, provide data about posture, movement, grip tension, facially expressed mental states and arousal. This data has demonstrated that intelligent tutoring systems can provide adaptive feedback based on an individual student's affective state. We also describe the evaluation of emotional embodied animated pedagogical agents and their impact on student motivation and achievement. Empirical studies show that students using the agents increased their math value, self-concept and mastery orientation.",
keywords = "Intelligent tutoring systems, Pedagogical agents, Student emotion, Wireless sensors",
author = "Beverly Woolf and Toby Dragon and Ivon Arroyo and David Cooper and Winslow Burleson and Kasia Muldner",
year = "2009",
doi = "10.1007/978-3-642-02580-8_78",
language = "English (US)",
isbn = "364202579X",
volume = "5612 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 3",
pages = "713--722",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
edition = "PART 3",

}

TY - GEN

T1 - Recognizing and responding to student affect

AU - Woolf, Beverly

AU - Dragon, Toby

AU - Arroyo, Ivon

AU - Cooper, David

AU - Burleson, Winslow

AU - Muldner, Kasia

PY - 2009

Y1 - 2009

N2 - This paper describes the use of wireless sensors to recognize student emotion and the use of pedagogical agents to respond to students with these emotions. Minimally invasive sensor technology has reached such a maturity level that students engaged in classroom work can us sensors while using a computer-based tutor. The sensors, located on each of 25 student's chair, mouse, monitor, and wrist, provide data about posture, movement, grip tension, facially expressed mental states and arousal. This data has demonstrated that intelligent tutoring systems can provide adaptive feedback based on an individual student's affective state. We also describe the evaluation of emotional embodied animated pedagogical agents and their impact on student motivation and achievement. Empirical studies show that students using the agents increased their math value, self-concept and mastery orientation.

AB - This paper describes the use of wireless sensors to recognize student emotion and the use of pedagogical agents to respond to students with these emotions. Minimally invasive sensor technology has reached such a maturity level that students engaged in classroom work can us sensors while using a computer-based tutor. The sensors, located on each of 25 student's chair, mouse, monitor, and wrist, provide data about posture, movement, grip tension, facially expressed mental states and arousal. This data has demonstrated that intelligent tutoring systems can provide adaptive feedback based on an individual student's affective state. We also describe the evaluation of emotional embodied animated pedagogical agents and their impact on student motivation and achievement. Empirical studies show that students using the agents increased their math value, self-concept and mastery orientation.

KW - Intelligent tutoring systems

KW - Pedagogical agents

KW - Student emotion

KW - Wireless sensors

UR - http://www.scopus.com/inward/record.url?scp=70350333926&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70350333926&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-02580-8_78

DO - 10.1007/978-3-642-02580-8_78

M3 - Conference contribution

SN - 364202579X

SN - 9783642025792

VL - 5612 LNCS

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

SP - 713

EP - 722

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

ER -