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Multimodal Assessment of Teaching Behavior in Immersive Rehearsal Environment-TeachLivE

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Roghayeh BarmakiAuthors Info & Claims

ICMI '15: Proceedings of the 2015 ACM on International Conference on Multimodal Interaction

Pages 651 - 655

https://doi.org/10.1145/2818346.2823306

Published: 09 November 2015 Publication History

Abstract

Nonverbal behaviors such as facial expressions, eye contact, gestures, and body movements in general have strong impacts on the process of communicative interactions. Gestures play an important role in interpersonal communication in the classroom between student and teacher. To assist teachers with exhibiting open and positive nonverbal signals in their actual classroom, we have designed a multimodal teaching application with provisions for real-time feedback in coordination with our TeachLivE test-bed environment and its reflective application; ReflectLivE. Individuals walk into this virtual environment and interact with five virtual students shown on a large screen display. The recent research study is designed to have two settings (7-minute long each). In each of the settings, the participants are provided lesson plans from which they teach. All the participants are asked to take part in both settings, with half receiving automated real-time feedback about their body poses in the first session (group 1) and the other half receiving such feedback in the second session (group 2). Feedback is in the form of a visual indication each time the participant exhibits a closed stance. To create this automated feedback application, a closed posture corpus was collected and trained based on the existing TeachLivE teaching records. After each session, the participants take a post-questionnaire about their experience. We hypothesize that visual feedback improves positive body gestures for both groups during the feedback session, and that, for group 2, this persists into their second unaided session but, for group 1, improvements occur only during the second session.

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Cited By

Kwan TYiu KYau YLam PLi SWong K(2022)A Review on the Application of Virtual Reality in Professional and Vocational Training2022 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)10.1109/TALE54877.2022.00031(149-154)Online publication date: Dec-2022
https://doi.org/10.1109/TALE54877.2022.00031
Garcia-Gutiérrez SEsteban-Aizpiri CLafuente IBarrio IQuiros RQuintana JUranga AGarcía-Gutiérrez SLafuente IQuintana JOrive MGonzalez NAnton AVillanueva AMuñoz CLegarreta MQuirós RYandiola PEgurrola MAramburu AArtaraz AChasco LBronte OGarcía PJodar AFernandez VEsteban CMas NPulido EBengoetxea IMartínez ABilbao AGorostiza IArriaga IZapiarain JParraza NIriberri MZalacain RRuiz LSerrano LCouto AAteka OCano AIbarra MMillan EBacigalupe MLetona JArcelay ABerraondo ICastells XPosso MPerestelo LAcosta GGonzñalez CRedondo MPadilla MMuñoz Ade Madariaga R(2022)Machine learning-based model for prediction of clinical deterioration in hospitalized patients by COVID 19Scientific Reports10.1038/s41598-022-09771-z12:1Online publication date: 2-May-2022
https://doi.org/10.1038/s41598-022-09771-z
Jennifer J(2022)Feature elimination and comparison of machine learning algorithms in landslide susceptibility mappingEnvironmental Earth Sciences10.1007/s12665-022-10620-581:20Online publication date: 5-Oct-2022
https://doi.org/10.1007/s12665-022-10620-5
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Index Terms

Multimodal Assessment of Teaching Behavior in Immersive Rehearsal Environment-TeachLivE
1. Information systems
  1. Information systems applications
    1. Multimedia information systems

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Published In

cover image ACM Conferences

ICMI '15: Proceedings of the 2015 ACM on International Conference on Multimodal Interaction

November 2015

678 pages

ISBN:9781450339124

DOI:10.1145/2818346

General Chairs:
Zhengyou Zhang
Microsoft Research, USA
,
Phil Cohen
VoiceBox Technologies, USA
,
Program Chairs:
Dan Bohus
Microsoft Research, USA
,
Radu Horaud
INRIA Grenoble Rhone-Alpes, France
,
Helen Meng
Chinese University of Hong Kong, China

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

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Published: 09 November 2015

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ICMI '15

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SIGCHI

ICMI '15: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION

November 9 - 13, 2015

Washington, Seattle, USA

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ICMI '15 Paper Acceptance Rate 52 of 127 submissions, 41%;

Overall Acceptance Rate 453 of 1,080 submissions, 42%

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Cited By

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https://doi.org/10.1109/TALE54877.2022.00031
Garcia-Gutiérrez SEsteban-Aizpiri CLafuente IBarrio IQuiros RQuintana JUranga AGarcía-Gutiérrez SLafuente IQuintana JOrive MGonzalez NAnton AVillanueva AMuñoz CLegarreta MQuirós RYandiola PEgurrola MAramburu AArtaraz AChasco LBronte OGarcía PJodar AFernandez VEsteban CMas NPulido EBengoetxea IMartínez ABilbao AGorostiza IArriaga IZapiarain JParraza NIriberri MZalacain RRuiz LSerrano LCouto AAteka OCano AIbarra MMillan EBacigalupe MLetona JArcelay ABerraondo ICastells XPosso MPerestelo LAcosta GGonzñalez CRedondo MPadilla MMuñoz Ade Madariaga R(2022)Machine learning-based model for prediction of clinical deterioration in hospitalized patients by COVID 19Scientific Reports10.1038/s41598-022-09771-z12:1Online publication date: 2-May-2022
https://doi.org/10.1038/s41598-022-09771-z
Jennifer J(2022)Feature elimination and comparison of machine learning algorithms in landslide susceptibility mappingEnvironmental Earth Sciences10.1007/s12665-022-10620-581:20Online publication date: 5-Oct-2022
https://doi.org/10.1007/s12665-022-10620-5
Yalamanchili BSamayamantula SAnne K(2022)Neural network-based blended ensemble learning for speech emotion recognitionMultidimensional Systems and Signal Processing10.1007/s11045-022-00845-933:4(1323-1348)Online publication date: 20-Aug-2022
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Alwahaby HCukurova MPapamitsiou ZGiannakos M(2022)The Evidence of Impact and Ethical Considerations of Multimodal Learning Analytics: A Systematic Literature ReviewThe Multimodal Learning Analytics Handbook10.1007/978-3-031-08076-0_12(289-325)Online publication date: 9-Oct-2022
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