How Can High-Frequency Sensors Capture Collaboration? A Review of the Empirical Links between Multimodal Metrics and Collaborative Constructs

Bertrand Schneider; Gahyun Sung; Edwin Chng; Stephanie Yang

doi:10.3390/s21248185

Back

How Can High-Frequency Sensors Capture Collaboration? A Review of the Empirical Links between Multimodal Metrics and Collaborative Constructs

Journal article

Open access

Peer reviewed

How Can High-Frequency Sensors Capture Collaboration? A Review of the Empirical Links between Multimodal Metrics and Collaborative Constructs

Bertrand Schneider, Gahyun Sung, Edwin Chng and Stephanie Yang

Sensors (Basel, Switzerland), Vol.21(24), p.8185

12/08/2021

DOI: 10.3390/s21248185

PMCID: PMC8706197

PMID: 34960278

Files and links (1)

url

https://doi.org/10.3390/s21248185View

Published (Version of record) Open Access

Abstract

This paper reviews 74 empirical publications that used high-frequency data collection tools to capture facets of small collaborative groups—i.e., papers that conduct Multimodal Collaboration Analytics (MMCA) research. We selected papers published from 2010 to 2020 and extracted their key contributions. For the scope of this paper, we focus on: (1) the sensor-based metrics computed from multimodal data sources (e.g., speech, gaze, face, body, physiological, log data); (2) outcome measures, or operationalizations of collaborative constructs (e.g., group performance, conditions for effective collaboration); (3) the connections found by researchers between sensor-based metrics and outcomes; and (4) how theory was used to inform these connections. An added contribution is an interactive online visualization where researchers can explore collaborative sensor-based metrics, collaborative constructs, and how the two are connected. Based on our review, we highlight gaps in the literature and discuss opportunities for the field of MMCA, concluding with future work for this project.

Review

Details

Title: Subtitle: How Can High-Frequency Sensors Capture Collaboration? A Review of the Empirical Links between Multimodal Metrics and Collaborative Constructs
Creators: Bertrand Schneider - Harvard University
Gahyun Sung - Harvard University
Edwin Chng - Harvard University
Stephanie Yang - Harvard University
Resource Type: Journal article
Publication Details: Sensors (Basel, Switzerland), Vol.21(24), p.8185
Publisher: MDPI AG
DOI: 10.3390/s21248185
PMID: 34960278
PMCID: PMC8706197
ISSN: 1424-8220
eISSN: 1424-8220
Language: English
Date published: 12/08/2021
Academic Unit: Psychological and Quantitative Foundations
Record Identifier: 9984701728402771

Metrics

6 Record Views

16 Times Cited - Web of Science

See more details