TY - GEN
T1 - Characterizing joint attention dynamics during collaborative problem-solving in an immersive astronomy simulation
AU - Zhou, Yiqiu
AU - Kang, Jina
N1 - Publisher Copyright:
© 2022 Copyright is held by the author(s).
PY - 2022
Y1 - 2022
N2 - The complex and dynamic nature of collaboration makes it challenging to find indicators of productive learning and quality collaboration. This exploratory study developed a collaboration metric to capture temporal patterns of joint attention (JA) based on log files generated as students interacted with an immersive astronomy simulation using augmented reality headsets and tablets. JA is defined as the ability to coordinate attention, which thus plays an important role in collaborative problem-solving to build the common ground for knowledge co-construction. We first developed a JA metric consisting of six distinct but closely relevant states as a measure of the collaboration process. We then conducted descriptive statistics to compare frequency and temporal pattern of JA states across three learning performance groups. Our results showed that high-learning-gain groups demonstrated visual coordination behaviors more frequently and utilized this collaboration strategy in the early stage. We then investigated sequences of these JA states, focusing on one key behavior: long and consistent shared view as a proxy for collaboration. This sequential analysis revealed two different collaboration profiles: attention follow-leader and turn takers, suggesting the existence of asymmetrical participation. Our findings indicate the potential of JA metric to predict overall collaboration quality, identify undesirable collaboration behaviors, and serve as an early warning to provide just-in-time guidance.
AB - The complex and dynamic nature of collaboration makes it challenging to find indicators of productive learning and quality collaboration. This exploratory study developed a collaboration metric to capture temporal patterns of joint attention (JA) based on log files generated as students interacted with an immersive astronomy simulation using augmented reality headsets and tablets. JA is defined as the ability to coordinate attention, which thus plays an important role in collaborative problem-solving to build the common ground for knowledge co-construction. We first developed a JA metric consisting of six distinct but closely relevant states as a measure of the collaboration process. We then conducted descriptive statistics to compare frequency and temporal pattern of JA states across three learning performance groups. Our results showed that high-learning-gain groups demonstrated visual coordination behaviors more frequently and utilized this collaboration strategy in the early stage. We then investigated sequences of these JA states, focusing on one key behavior: long and consistent shared view as a proxy for collaboration. This sequential analysis revealed two different collaboration profiles: attention follow-leader and turn takers, suggesting the existence of asymmetrical participation. Our findings indicate the potential of JA metric to predict overall collaboration quality, identify undesirable collaboration behaviors, and serve as an early warning to provide just-in-time guidance.
KW - Collaborative Problem-Solving
KW - Immersive Learning Environments
KW - Joint Attention
KW - Shared View
UR - http://www.scopus.com/inward/record.url?scp=85165648161&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85165648161&partnerID=8YFLogxK
U2 - 10.5281/zenodo.6852988
DO - 10.5281/zenodo.6852988
M3 - Conference contribution
AN - SCOPUS:85165648161
T3 - Proceedings of the 15th International Conference on Educational Data Mining, EDM 2022
BT - Proceedings of the 15th International Conference on Educational Data Mining, EDM 2022
PB - International Educational Data Mining Society
T2 - 15th International Conference on Educational Data Mining, EDM 2022
Y2 - 24 July 2022 through 27 July 2022
ER -