Multimodal prediction of expertise and leadership in learning groups

Stefan Scherer, Nadir Weibel, Sharon Oviatt, Louis Philippe Morency

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

31 Citations (Scopus)

Abstract

In this study, we investigate low level predictors from audio and writing modalities for the separation and identification of socially dominant leaders and experts within a study group. We use a multimodal dataset of situated computer assisted group learning tasks: Groups of three high-school students solve a number of mathematical problems in two separate sessions. In order to automatically identify the socially dominant student and expert in the group we analyze a number of prosodic and voice quality features as well as writing-based features. In this preliminary study we identify a number of promising acoustic and writing predictors for the disambiguation of leaders, experts and other students. We believe that this exploratory study reveals key opportunities for future analysis of multimodal learning analytics based on a combination of audio and writing signals.

Original languageEnglish
Title of host publicationProceedings of the 1st International Workshop on Multimodal Learning Analytics, MLA'12
DOIs
Publication statusPublished - 7 Dec 2012
Externally publishedYes
EventInternational Workshop on Multimodal Learning Analytics, MLA 2012 - Santa Monica, CA, United States of America
Duration: 26 Oct 201226 Oct 2012
Conference number: 1st

Publication series

NameProceedings of the 1st International Workshop on Multimodal Learning Analytics, MLA'12

Conference

ConferenceInternational Workshop on Multimodal Learning Analytics, MLA 2012
CountryUnited States of America
CitySanta Monica, CA
Period26/10/1226/10/12

Keywords

  • Multimodal learning analytics
  • Speech
  • Writing

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