TY - GEN
T1 - Developing an in-application shared view metric to capture collaborative learning in a multi-platform astronomy simulation
AU - Diederich, Morgan
AU - Kang, Jina
AU - Kim, Taehyun
AU - Lindgren, Robb
N1 - Funding Information:
First, we would like to formally recognize other members of our research team, Emma Mecier, James Planey, Chris Hart, and Nathan Kimball. Through their research efforts and contributions of the qualitative coding and the design of the simulation, their research has enriched this works significantly. Further, this project was sponsored by the National Science Foundation Grant no:1822796
Publisher Copyright:
© 2021 ACM.
PY - 2021/4/12
Y1 - 2021/4/12
N2 - There has been recent interest in the design of collaborative learning activities that are distributed across multiple technology devices for students to engage in scientific inquiry. Emerging research has begun to investigate students' collaborative behaviors across different device types and students' shared attention by tracking eye gaze, body posture, and their interactions with the digital environment. Using a 3D astronomy simulation that leverages a VR headset and tablet computers, this paper builds on the ideas described in eye-gaze studies by developing and implementing a metric of shared viewing across multiple devices. Preliminary findings suggest that a higher level of shared view could be related to increased conceptual discussion, as well as point to an early-stage pattern of behavior of decreased SV to prompt facilitator intervention to refocus collaborative efforts. We hope this metric will be a promising first step in further understanding and assessing the quality of collaboration across multiple device platforms in a single shared space. This paper provides an in depth look at a highly exploratory stage of a broader research trajectory to establish a robust, effective way to track screen views, including providing resources to teachers when students engage in similar learning environments, and providing insight from log data to understand how students effectively collaborate.
AB - There has been recent interest in the design of collaborative learning activities that are distributed across multiple technology devices for students to engage in scientific inquiry. Emerging research has begun to investigate students' collaborative behaviors across different device types and students' shared attention by tracking eye gaze, body posture, and their interactions with the digital environment. Using a 3D astronomy simulation that leverages a VR headset and tablet computers, this paper builds on the ideas described in eye-gaze studies by developing and implementing a metric of shared viewing across multiple devices. Preliminary findings suggest that a higher level of shared view could be related to increased conceptual discussion, as well as point to an early-stage pattern of behavior of decreased SV to prompt facilitator intervention to refocus collaborative efforts. We hope this metric will be a promising first step in further understanding and assessing the quality of collaboration across multiple device platforms in a single shared space. This paper provides an in depth look at a highly exploratory stage of a broader research trajectory to establish a robust, effective way to track screen views, including providing resources to teachers when students engage in similar learning environments, and providing insight from log data to understand how students effectively collaborate.
KW - Astronomy education
KW - Immersive virtual reality
KW - Log data
KW - Science education
KW - Shared view
UR - http://www.scopus.com/inward/record.url?scp=85103883510&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85103883510&partnerID=8YFLogxK
U2 - 10.1145/3448139.3448156
DO - 10.1145/3448139.3448156
M3 - Conference contribution
AN - SCOPUS:85103883510
T3 - ACM International Conference Proceeding Series
SP - 173
EP - 183
BT - LAK 2021 Conference Proceedings - The Impact we Make
PB - Association for Computing Machinery
T2 - 11th International Conference on Learning Analytics and Knowledge: The Impact we Make: The Contributions of Learning Analytics to Learning, LAK 2021
Y2 - 12 April 2021 through 16 April 2021
ER -