In his 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.
%0 Conference Paper
%1 scherer_multimodal_2012
%A Scherer, Stefan
%A Weibel, Nadir
%A Morency, Louis-Philippe
%A Oviatt, Sharon
%B Proceedings of the 1st International Workshop on Multimodal Learning Analytics
%C New York, NY, USA
%D 2012
%I ACM
%K analytics, learning multimodal speech, writing
%P 1:1--1:8
%R 10.1145/2389268.2389269
%T Multimodal Prediction of Expertise and Leadership in Learning Groups
%U http://doi.acm.org/10.1145/2389268.2389269
%X In his 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.
%@ 978-1-4503-1515-9
@inproceedings{scherer_multimodal_2012,
abstract = {In his 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.},
added-at = {2019-02-18T07:11:07.000+0100},
address = {New York, NY, USA},
author = {Scherer, Stefan and Weibel, Nadir and Morency, Louis-Philippe and Oviatt, Sharon},
biburl = {https://www.bibsonomy.org/bibtex/2110d9f0aa0f3d9c72b55e57244aaaf59/weibel},
booktitle = {Proceedings of the 1st {International} {Workshop} on {Multimodal} {Learning} {Analytics}},
doi = {10.1145/2389268.2389269},
file = {ACM Full Text PDF:/Users/weibel/Zotero/storage/SCLRR59V/Scherer et al. - 2012 - Multimodal Prediction of Expertise and Leadership .pdf:application/pdf},
interhash = {631d97ad229bd0f6a3a4cf8e52c658cf},
intrahash = {110d9f0aa0f3d9c72b55e57244aaaf59},
isbn = {978-1-4503-1515-9},
keywords = {analytics, learning multimodal speech, writing},
note = {Workshop Paper},
pages = {1:1--1:8},
publisher = {ACM},
series = {{MLA} '12},
timestamp = {2019-02-18T07:11:07.000+0100},
title = {Multimodal {Prediction} of {Expertise} and {Leadership} in {Learning} {Groups}},
url = {http://doi.acm.org/10.1145/2389268.2389269},
urldate = {2018-12-06},
year = 2012
}