Back to Search Start Over

Investigating the Relationship between Dialogue States and Partner Satisfaction during Co-Creative Learning Tasks

Authors :
Griffith, Amanda E.
Katuka, Gloria Ashiya
Wiggins, Joseph B.
Boyer, Kristy Elizabeth
Freeman, Jason
Magerko, Brian
McKlin, Tom
Source :
International Journal of Artificial Intelligence in Education. Sep 2023 33(3):543-582.
Publication Year :
2023

Abstract

Collaborative learning offers numerous benefits to learners, largely due to the dialogue that is unfolding between them. However, there is still much to learn about the structure of collaborative dialogue, and especially little is known about co-creative dialogues during learning. This paper reports on a study with learners engaged in co-creative tasks where the learners wrote code to create a song and while engaging in textual dialogue as they did so. After gathering the textual dialogue and the actions within the interface, we learned a hidden Markov model (HMM) to reveal co-creative states. The seven-state model revealed four states primarily composed of coding actions that included browsing the curriculum documents, working in the code editor, compiling the code successfully, and receiving a compile error. The remaining three states are primarily composed of dialogue that can be characterized as social, aesthetic, and technical dialogue. Next, we analyzed the relationships between the co-creative states revealed by the HMM and students' partner satisfaction scores from a post-survey. The results reveal the relative frequency of actions in certain states and some transitions between states were predictive of partner satisfaction. For example, partner satisfaction was negatively associated with the "Compilation Error" state and with the relative frequency of transitions from the "Curriculum Browsing" state to the "Code Editing" state. Partner satisfaction was also negatively associated with the relative frequency of transitions from the "Aesthetic Dialogue" state to the "Technical Dialogue" state and the "Code Editing" state. This line of investigation reveals how co-creative processes are associated with partner satisfaction, and holds the potential to inform scaffolding for collaborative learning.

Details

Language :
English
ISSN :
1560-4292 and 1560-4306
Volume :
33
Issue :
3
Database :
ERIC
Journal :
International Journal of Artificial Intelligence in Education
Publication Type :
Academic Journal
Accession number :
EJ1388630
Document Type :
Journal Articles<br />Reports - Research
Full Text :
https://doi.org/10.1007/s40593-022-00302-5