Novices Make More Noise! The D&K Effect 2.0?

Jan Schneider, Khaleel Asyraaf Mat Sanusi, B.H. Limbu, Marcel Schmitz, Daniel Schiffner

Research output: Chapter in Book/Conference proceedings/Edited volumeChapterScientificpeer-review

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Abstract

This paper presents an approach that helps distinguish expert and novice performance easily by observing the sensor data without having to understand nor apply models to the sensor signal. The method consists of plotting the sensor data and identifying irregularities. We corroborate, with the help of sensors, that expert performances are smoother, contain fewer irregularities, and have consistently uniform patterns than novice performances. In this paper, we present six different cases pointing out this assertion, namely bachata and salsa dances, tennis swings, football penalty kicks, badminton, and running.
Original languageEnglish
Title of host publicationCrossMMLA 2023
Subtitle of host publicationLeveraging Multimodal Data for Generating Meaningful Feedback
EditorsDaniele Di Mitri , Namrata Srivastava , Roberto Martinez-Maldonado, Mutlu Cukurova
PublisherCEUR-WS
Pages43-48
Number of pages6
Volume3439
Publication statusPublished - 2023
EventCrossMMLA 2023: Leveraging Multimodal Data for Generating Meaningful Feedback - Arlington, United States
Duration: 13 Mar 202317 Mar 2023
https://crossmmla.org/

Publication series

NameCEUR Workshop procedings
PublisherCEUR
Volume3439
ISSN (Electronic)1613-0073

Workshop

WorkshopCrossMMLA 2023
Abbreviated titleCrossMMLA 2023
Country/TerritoryUnited States
CityArlington
Period13/03/2317/03/23
Internet address

Keywords

  • Expertise
  • Deliberate practice
  • Sensors

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