Multimodal learning analytics in a laboratory classroom

Man Ching Esther Chan, Xavier Ochoa, David Clarke

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Sophisticated research approaches and tools can help researchers to investigate the complex processes involved in learning in various settings. The use of video technology to record classroom practices, in particular, can be a powerful way for capturing and studying learning and related phenomena within a social setting such as the classroom. This chapter outlines several multimodal techniques to analyze the learning activities in a laboratory classroom. The video and audio recordings were processed automatically to obtain information rather than requiring manual coding. Moreover, these automated techniques are able to extract information with an efficiency that is beyond the capabilities of human-coders, providing the means to deal analytically with the multiple modalities that characterize the classroom. Once generated, the information provided by the different modalities is used to explain and predict high-level constructs such as students’ attention and engagement. This chapter not only presents the results of the analysis, but also describes the setting, hardware and software needed to replicate this analytical approach.

Original languageEnglish (US)
Title of host publicationIntelligent Systems Reference Library
PublisherSpringer Science and Business Media Deutschland GmbH
Pages131-156
Number of pages26
DOIs
StatePublished - Jan 1 2020

Publication series

NameIntelligent Systems Reference Library
Volume158
ISSN (Print)1868-4394
ISSN (Electronic)1868-4408

Fingerprint

Audio recordings
Video recording
Students
Hardware
classroom
learning
video
research approach
hardware
recording
coding
efficiency
student

ASJC Scopus subject areas

  • Computer Science(all)
  • Information Systems and Management
  • Library and Information Sciences

Cite this

Chan, M. C. E., Ochoa, X., & Clarke, D. (2020). Multimodal learning analytics in a laboratory classroom. In Intelligent Systems Reference Library (pp. 131-156). (Intelligent Systems Reference Library; Vol. 158). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-13743-4_8

Multimodal learning analytics in a laboratory classroom. / Chan, Man Ching Esther; Ochoa, Xavier; Clarke, David.

Intelligent Systems Reference Library. Springer Science and Business Media Deutschland GmbH, 2020. p. 131-156 (Intelligent Systems Reference Library; Vol. 158).

Research output: Chapter in Book/Report/Conference proceedingChapter

Chan, MCE, Ochoa, X & Clarke, D 2020, Multimodal learning analytics in a laboratory classroom. in Intelligent Systems Reference Library. Intelligent Systems Reference Library, vol. 158, Springer Science and Business Media Deutschland GmbH, pp. 131-156. https://doi.org/10.1007/978-3-030-13743-4_8
Chan MCE, Ochoa X, Clarke D. Multimodal learning analytics in a laboratory classroom. In Intelligent Systems Reference Library. Springer Science and Business Media Deutschland GmbH. 2020. p. 131-156. (Intelligent Systems Reference Library). https://doi.org/10.1007/978-3-030-13743-4_8
Chan, Man Ching Esther ; Ochoa, Xavier ; Clarke, David. / Multimodal learning analytics in a laboratory classroom. Intelligent Systems Reference Library. Springer Science and Business Media Deutschland GmbH, 2020. pp. 131-156 (Intelligent Systems Reference Library).
@inbook{166acbe469ca4c96b1db34d403c4de3a,
title = "Multimodal learning analytics in a laboratory classroom",
abstract = "Sophisticated research approaches and tools can help researchers to investigate the complex processes involved in learning in various settings. The use of video technology to record classroom practices, in particular, can be a powerful way for capturing and studying learning and related phenomena within a social setting such as the classroom. This chapter outlines several multimodal techniques to analyze the learning activities in a laboratory classroom. The video and audio recordings were processed automatically to obtain information rather than requiring manual coding. Moreover, these automated techniques are able to extract information with an efficiency that is beyond the capabilities of human-coders, providing the means to deal analytically with the multiple modalities that characterize the classroom. Once generated, the information provided by the different modalities is used to explain and predict high-level constructs such as students’ attention and engagement. This chapter not only presents the results of the analysis, but also describes the setting, hardware and software needed to replicate this analytical approach.",
author = "Chan, {Man Ching Esther} and Xavier Ochoa and David Clarke",
year = "2020",
month = "1",
day = "1",
doi = "10.1007/978-3-030-13743-4_8",
language = "English (US)",
series = "Intelligent Systems Reference Library",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "131--156",
booktitle = "Intelligent Systems Reference Library",
address = "Germany",

}

TY - CHAP

T1 - Multimodal learning analytics in a laboratory classroom

AU - Chan, Man Ching Esther

AU - Ochoa, Xavier

AU - Clarke, David

PY - 2020/1/1

Y1 - 2020/1/1

N2 - Sophisticated research approaches and tools can help researchers to investigate the complex processes involved in learning in various settings. The use of video technology to record classroom practices, in particular, can be a powerful way for capturing and studying learning and related phenomena within a social setting such as the classroom. This chapter outlines several multimodal techniques to analyze the learning activities in a laboratory classroom. The video and audio recordings were processed automatically to obtain information rather than requiring manual coding. Moreover, these automated techniques are able to extract information with an efficiency that is beyond the capabilities of human-coders, providing the means to deal analytically with the multiple modalities that characterize the classroom. Once generated, the information provided by the different modalities is used to explain and predict high-level constructs such as students’ attention and engagement. This chapter not only presents the results of the analysis, but also describes the setting, hardware and software needed to replicate this analytical approach.

AB - Sophisticated research approaches and tools can help researchers to investigate the complex processes involved in learning in various settings. The use of video technology to record classroom practices, in particular, can be a powerful way for capturing and studying learning and related phenomena within a social setting such as the classroom. This chapter outlines several multimodal techniques to analyze the learning activities in a laboratory classroom. The video and audio recordings were processed automatically to obtain information rather than requiring manual coding. Moreover, these automated techniques are able to extract information with an efficiency that is beyond the capabilities of human-coders, providing the means to deal analytically with the multiple modalities that characterize the classroom. Once generated, the information provided by the different modalities is used to explain and predict high-level constructs such as students’ attention and engagement. This chapter not only presents the results of the analysis, but also describes the setting, hardware and software needed to replicate this analytical approach.

UR - http://www.scopus.com/inward/record.url?scp=85063743390&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85063743390&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-13743-4_8

DO - 10.1007/978-3-030-13743-4_8

M3 - Chapter

T3 - Intelligent Systems Reference Library

SP - 131

EP - 156

BT - Intelligent Systems Reference Library

PB - Springer Science and Business Media Deutschland GmbH

ER -