Deep neural networks for collaborative learning analytics: Evaluating team collaborations using student gaze point prediction

10/16/2020
by   Zang Guo, et al.
0

Automatic assessment and evaluation of team performance during collaborative tasks is key to the learning analytics and computer-supported cooperative work research. There is a growing interest in the use of gaze-oriented cues for evaluating the collaboration and cooperativeness of teams. However, collecting gaze data using eye-trackers is not always feasible due to time and cost constraints. In this paper, we introduce an automated team assessment tool based on gaze points and joint visual attention (JVA) information extracted by computer vision solutions. We then evaluate team collaborations in an undergraduate anatomy learning activity (N=60, 30 teams) as a test user-study. The results indicate that higher JVA was positively associated with student learning outcomes (r(30)=0.50,p<0.005). Moreover, teams who participated in two experimental groups, and used interactive 3-D anatomy models, had higher JVA (F(1,28)=6.65,p<0.05) and better knowledge retention (F(1,28) =7.56,p<0.05) than those in the control group. Also, no significant difference was observed based on JVA for different gender compositions of teams. The findings from this work offer implications in learning sciences and collaborative computing by providing a novel mutual attention-based measure to objectively evaluate team collaboration dynamics.

READ FULL TEXT
research
04/17/2019

Collaboration Analysis Using Deep Learning

The analysis of the collaborative learning process is one of the growing...
research
12/26/2022

Leveraging Collaboration for Multifaceted Design and Product Teams: A Financial Perspective

Collaboration is a key driving force for a team's success. In this case ...
research
12/06/2021

Designing a Dashboard for Student Teamwork Analysis

Classroom dashboards are designed to help instructors effectively orches...
research
09/18/2023

(Deployed Application) Promoting Research Collaboration with Open Data Driven Team Recommendation in Response to Call for Proposals

Building teams and promoting collaboration are two very common business ...
research
10/30/2018

The effect of multidisciplinary collaborations on research diversification

This work verifies whether research diversification by a scientist is in...
research
05/01/2020

Workgroup Mapping: Visual Analysis of Collaboration Culture

The digital transformation of work presents new opportunities to underst...

Please sign up or login with your details

Forgot password? Click here to reset