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Presentation Skills Estimation Based on Video and Kinect Data Analysis

Authors:

Vanessa Echeverría,

Allan Avendaño,

Katherine Chiluiza,

Aníbal Vásquez,

Xavier OchoaAuthors Info & Claims

MLA '14: Proceedings of the 2014 ACM workshop on Multimodal Learning Analytics Workshop and Grand Challenge

Pages 53 - 60

https://doi.org/10.1145/2666633.2666641

Published: 12 November 2014 Publication History

Abstract

This paper identifies, by means of video and Kinect data, a set of predictors that estimate the presentation skills of 448 individual students. Two evaluation criteria were predicted: eye contact and posture and body language. Machine-learning evaluations resulted in models that predicted the performance level (good or poor) of the presenters with 68% and 63% of correctly classified instances, for eye contact and postures and body language criteria, respectively. Furthermore, the results suggest that certain features, such as arms movement and smoothness, provide high significance on predicting the level of development for presentation skills. The paper finishes with conclusions and related ideas for future work.

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Cited By

Sung HNathan M(2024)Your body tells how you engage in collaboration: Machine‐detected body movements as indicators of engagement in collaborative math knowledge buildingBritish Journal of Educational Technology10.1111/bjet.1347355:5(1950-1973)Online publication date: 10-May-2024
https://doi.org/10.1111/bjet.13473
Thanyadit SHeintz MLaw E(2023)Tutor In-sight: Guiding and Visualizing Students’ Attention with Mixed Reality Avatar Presentation ToolsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581069(1-20)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581069
McConvey KGuha SKuzminykh A(2023)A Human-Centered Review of Algorithms in Decision-Making in Higher EducationProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580658(1-15)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580658
Show More Cited By

Index Terms

Presentation Skills Estimation Based on Video and Kinect Data Analysis
1. Computing methodologies
  1. Machine learning
    1. Machine learning algorithms
      1. Feature selection

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Information & Contributors

Information

Published In

cover image ACM Conferences

MLA '14: Proceedings of the 2014 ACM workshop on Multimodal Learning Analytics Workshop and Grand Challenge

November 2014

68 pages

ISBN:9781450304887

DOI:10.1145/2666633

Program Chairs:
Xavier Ochoa
ESPOL, Ecuador
,
Marcelo Worsley
Stanford University, USA
,
Katherine Chiluiza
ESPOL, Ecuador
,
Saturnino Luz
Trinity College Dublin, Ireland

Copyright © 2014 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

Publication History

Published: 12 November 2014

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Funding Sources

VLIR-UOS project
Secretaría de Educación Superior Ciencia Tecnología e Innovación

Conference

ICMI '14

Sponsor:

SIGCHI

ICMI '14: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION

November 12, 2014

Istanbul, Turkey

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MLA '14 Paper Acceptance Rate 3 of 3 submissions, 100%;

Overall Acceptance Rate 3 of 3 submissions, 100%

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Cited By

Sung HNathan M(2024)Your body tells how you engage in collaboration: Machine‐detected body movements as indicators of engagement in collaborative math knowledge buildingBritish Journal of Educational Technology10.1111/bjet.1347355:5(1950-1973)Online publication date: 10-May-2024
https://doi.org/10.1111/bjet.13473
Thanyadit SHeintz MLaw E(2023)Tutor In-sight: Guiding and Visualizing Students’ Attention with Mixed Reality Avatar Presentation ToolsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581069(1-20)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581069
McConvey KGuha SKuzminykh A(2023)A Human-Centered Review of Algorithms in Decision-Making in Higher EducationProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580658(1-15)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580658
Huang ZHe QMaher KDeng XLai YMa CQin SLiu YWang H(2023)SpeechMirror: A Multimodal Visual Analytics System for Personalized Reflection of Online Public Speaking EffectivenessIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.3326932(1-11)Online publication date: 2023
https://doi.org/10.1109/TVCG.2023.3326932
Gulati VDwivedi SKumar DWadhwa JDhingra DHemanth J(2023)An automated framework to evaluate soft skills using posture and disfluency detectionMachine Vision and Applications10.1007/s00138-023-01431-034:5Online publication date: 1-Sep-2023
https://doi.org/10.1007/s00138-023-01431-0
Thomas CJayagopi D(2022)Predicting Presentation Skill of a Speaker Using Automatic Speaker and Audience MeasurementIEEE Transactions on Learning Technologies10.1109/TLT.2022.317160115:3(350-363)Online publication date: 1-Jun-2022
https://doi.org/10.1109/TLT.2022.3171601
Zheng CHuang LLin HGuo YHuang L(2022)BERT-Based Automatic Scoring Model for Speech-Oriented Text Modality2022 IEEE 2nd International Conference on Electronic Technology, Communication and Information (ICETCI)10.1109/ICETCI55101.2022.9832254(100-105)Online publication date: 27-May-2022
https://doi.org/10.1109/ICETCI55101.2022.9832254
Hammad RBahja MKuhail M(2022)Bridging the Gap Between Informal Learning Pedagogy and Multimodal Learning AnalyticsThe Multimodal Learning Analytics Handbook10.1007/978-3-031-08076-0_7(159-179)Online publication date: 9-Oct-2022
https://doi.org/10.1007/978-3-031-08076-0_7
Chejara PPrieto LRuiz-Calleja ARodríguez-Triana MShankar SKasepalu R(2021)EFAR-MMLA: An Evaluation Framework to Assess and Report Generalizability of Machine Learning Models in MMLASensors10.3390/s2108286321:8(2863)Online publication date: 19-Apr-2021
https://doi.org/10.3390/s21082863
Vieira FCechinel CRamos VRiquelme FNoel RVillarroel RCornide-Reyes HMunoz R(2021)A Learning Analytics Framework to Analyze Corporal Postures in Students PresentationsSensors10.3390/s2104152521:4(1525)Online publication date: 22-Feb-2021
https://doi.org/10.3390/s21041525
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