research-article

Fallacies of Agreement: A Critical Review of Consensus Assessment Methods for Gesture Elicitation

Author:

Theophanis TsandilasAuthors Info & Claims

ACM Transactions on Computer-Human Interaction (TOCHI), Volume 25, Issue 3

Article No.: 18, Pages 1 - 49

https://doi.org/10.1145/3182168

Published: 28 June 2018 Publication History

Abstract

Discovering gestures that gain consensus is a key goal of gesture elicitation. To this end, HCI research has developed statistical methods to reason about agreement. We review these methods and identify three major problems. First, we show that raw agreement rates disregard agreement that occurs by chance and do not reliably capture how participants distinguish among referents. Second, we explain why current recommendations on how to interpret agreement scores rely on problematic assumptions. Third, we demonstrate that significance tests for comparing agreement rates, either within or between participants, yield large Type I error rates (>40% for α =.05). As alternatives, we present agreement indices that are routinely used in inter-rater reliability studies. We discuss how to apply them to gesture elicitation studies. We also demonstrate how to use common resampling techniques to support statistical inference with interval estimates. We apply these methods to reanalyze and reinterpret the findings of four gesture elicitation studies.

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Index Terms

Fallacies of Agreement: A Critical Review of Consensus Assessment Methods for Gesture Elicitation
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
    1. Redundancy
  2. Embedded and cyber-physical systems
    1. Embedded systems
    2. Robotics
2. Networks
  1. Network properties
    1. Network reliability

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Published In

cover image ACM Transactions on Computer-Human Interaction

ACM Transactions on Computer-Human Interaction Volume 25, Issue 3

June 2018

217 pages

ISSN:1073-0516

EISSN:1557-7325

DOI:10.1145/3231919

Editor:
Ken Hinckley
Microsoft Research

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Copyright © 2018 ACM.

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Publication History

Published: 28 June 2018

Accepted: 01 January 2018

Revised: 01 August 2017

Received: 01 March 2017

Published in TOCHI Volume 25, Issue 3

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León GIsenberg PBreiter A(2024)Eliciting Multimodal and Collaborative Interactions for Data Exploration on Large Vertical DisplaysIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.332315030:2(1624-1637)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1109/TVCG.2023.3323150
Cheng YWu ZXiao R(2024)Exploring Methods to Optimize Gesture Elicitation Studies: A Systematic Literature ReviewIEEE Access10.1109/ACCESS.2024.338726912(64958-64979)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3387269
He YSun QCheng PHou SZhou L(2024)Priming users with babies’ gestures: Investigating the influences of priming with different development origin of image schemas in gesture elicitation studyInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2024.103288189(103288)Online publication date: Sep-2024
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Munzlinger EBatista Narcizo FWitzner Hansen DVucurevich T(2024)Universal Hand Gesture Interaction Vocabulary for Cross-Cultural Users: Challenges and ApproachesHCI International 2024 Posters10.1007/978-3-031-61932-8_8(56-69)Online publication date: 1-Jun-2024
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Hosseini MIhmels TChen ZKoelle MMüller HBoll S(2023)Towards a Consensus Gesture Set: A Survey of Mid-Air Gestures in HCI for Maximized Agreement Across DomainsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581420(1-24)Online publication date: 19-Apr-2023
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