Literature review on co-located collaboration modeling using multimodal learning analytics—Can we go the whole nine yards?

S Praharaj, M Scheffel, H Drachsler… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Collaboration is one of the important 21st-century skills. It can take place in remote or co-
located settings. Co-located collaboration (CC) is a very complex process that involves …

How can high-frequency sensors capture collaboration? A review of the empirical links between multimodal metrics and collaborative constructs

B Schneider, G Sung, E Chng, S Yang - Sensors, 2021 - mdpi.com
This paper reviews 74 empirical publications that used high-frequency data collection tools
to capture facets of small collaborative groups—ie, papers that conduct Multimodal …

Robot-supported collaborative learning (RSCL): Social robots as teaching assistants for higher education small group facilitation

RB Rosenberg-Kima, Y Koren… - Frontiers in Robotics and AI, 2020 - frontiersin.org
Acknowledging the benefits of active learning and the importance of collaboration skills, the
higher education system has started to transform toward utilization of group activities into …

Co-Located Human–Human Interaction Analysis Using Nonverbal Cues: A Survey

C Beyan, A Vinciarelli, AD Bue - ACM Computing Surveys, 2023 - dl.acm.org
Automated co-located human–human interaction analysis has been addressed by the use of
nonverbal communication as measurable evidence of social and psychological phenomena …

Exploring AI techniques for generalizable teaching practice identification

FP García, Ó Cánovas, FJG Clemente - IEEE Access, 2024 - ieeexplore.ieee.org
Using automated models to analyze classroom discourse is a valuable tool for educators to
improve their teaching methods. In this paper, we focus on exploring alternatives to ensure …

Improved visual focus of attention estimation and prosodic features for analyzing group interactions

L Zhang, M Morgan, I Bhattacharya, M Foley… - 2019 International …, 2019 - dl.acm.org
Collaborative group tasks require efficient and productive verbal and non-verbal interactions
among the participants. Studying such interaction patterns could help groups perform more …

Multiparty visual co-occurrences for estimating personality traits in group meetings

L Zhang, I Bhattacharya, M Morgan… - Proceedings of the …, 2020 - openaccess.thecvf.com
Participants' body language during interactions with others in a group meeting can reveal
important information about their individual personalities, as well as their contribution to a …

A dataset of ambient sensors in a meeting room for activity recognition

H Kim, G Kim, T Lee, K Kim, D Lee - Scientific Data, 2024 - nature.com
As IoT technology advances, using machine learning to detect user activities emerges as a
promising strategy for delivering a variety of smart services. It is essential to have access to …

A multimodal robot-driven meeting facilitation system for group decision-making sessions

A Shamekhi, T Bickmore - 2019 international conference on multimodal …, 2019 - dl.acm.org
Group meetings are ubiquitous, with millions of meetings held across the world every day.
However, meeting quality, group performance, and outcomes are challenged by a variety of …

The unobtrusive group interaction (UGI) corpus

I Bhattacharya, M Foley, C Ku, N Zhang… - Proceedings of the 10th …, 2019 - dl.acm.org
Studying group dynamics requires fine-grained spatial and temporal understanding of
human behavior. Social psychologists studying human interaction patterns in face-to-face …