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Title: Connecting the dots towards collaborative AIED: Linking group makeup to process to learning
We model collaborative problem solving outcomes using data from 37 triads who completed a challenging computer programming task. Participants individually rated their group’s performance, communication, cooperation, and agreeableness after the session, which were aggregated to produce group-level measures of subjective outcomes. We scored teams on objective task outcomes and measured individual students’ learning outcomes with a posttest. Groups with similar personalities performed better on the task and had higher ratings of communication, cooperation, and agreeableness. Importantly, greater deviation in teammates’ perception of group performance and higher ratings of communication, cooperation, and agreeableness negatively predicted individual learning. We discuss findings from the perspective of group work norms and consider applications to intelligent systems that support collaborative problem solving.  more » « less
Award ID(s):
1745442
PAR ID:
10088202
Author(s) / Creator(s):
;
Date Published:
Journal Name:
The 19th International Conference on Artificial Intelligence in Education
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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