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Help Seekers vs. Help Accepters: Understanding Student Engagement with a Mentor Agent

Conference Paper/Proceedings
Help Seekers vs. Help Accepters: Understanding Student Engagement with a Mentor Agent
Publication Year:
2023
Publication Source:
Artificial Intelligence In Education, Aied 2023
Volume:
13916
Funding Type:
ECR:Core
Author(s):
van Stee, Elena G.; Heath, Taylor; Baker, Ryan S.; Andres, J. M. Alexandra L.; Ocumpaugh, Jaclyn
Supporting Project(s):

Help from virtual pedagogical agents has the potential to improve student learning. Yet students often do not seek help when they need it, do not use help effectively, or ignore the agent's help altogether. This paper seeks to better understand students' patterns of accepting and seeking help in a computer-based science program called Betty's Brain. Focusing on student interactions with the mentor agent, Mr. Davis, we examine the factors associated with patterns of help acceptance and help seeking; the relationship between help acceptance and help seeking; and how each behavior is related to learning outcomes. First, we examine whether students accepted help from Mr. Davis, operationalized as whether they followed his suggestions to read specific textbook pages. We find a significant positive relationship between help acceptance and student post-test scores. Despite this, help accepters made fewer positive statements about Mr. Davis in the interviews. Second, we identify how many times students proactively sought help from Mr. Davis. Students who most frequently sought help demonstrated more confusion while learning (measured using an interaction-based ML-based detector); tended to have higher science anxiety; and made more negative statements about Mr. Davis, compared to those who made few or no requests. However, help seeking was not significantly related to post-test scores. Finally, we draw from the qualitative interviews to consider how students understand and articulate their experiences with help from Mr. Davis.