Academic Journal
Metacognitive Scaffolding in the Age of GenAI: A Behavioral Analysis of Student–Chatbot Interactions During Course Selection.
| Τίτλος: | Metacognitive Scaffolding in the Age of GenAI: A Behavioral Analysis of Student–Chatbot Interactions During Course Selection. |
|---|---|
| Συγγραφείς: | Zhang, Cuilian, Wei, Wei, Hu, Xiao |
| Πηγή: | Education Sciences; Jun2026, Vol. 16 Issue 6, p824, 23p |
| Θεματικοί όροι: | Concept mapping, Metacognition, Curriculum, Human-computer interaction, Educational planning, Generative artificial intelligence, Cognitive maps (Psychology), Behavioral assessment |
| Περίληψη: | Course selection presents a persistent challenge for students who often have difficulty articulating clear goals, integrating multiple considerations, and aligning academic choices with personal and professional aspirations. This study investigates whether concept mapping, as a metacognitive scaffolding tool, may shape how students interact with Generative AI (GenAI) systems during academic decision-making. In a randomized controlled experiment, 180 undergraduates at a polytechnic university in China were assigned to either a GenAI-only condition or a GenAI + Concept Map condition. After excluding 3 outlier participants, 177 students were included in the final analysis. Controlling for prior academic performance via ANCOVA, students with concept-map support showed different interaction patterns: they had a longer maximum consecutive-question chain within a session (GPA-adjusted means: 11.92 vs. 9.07 questions), formulated longer questions (15.27 vs. 11.93 words), and spent more time per conversation session on average (8.05 vs. 6.77 min). An analysis of conversation content showed that the concept-map group discussed a wider range of course selection factors (covering 4.46 vs. 3.66 main dimensions and 8.70 vs. 6.36 detailed factors). Epistemic Network Analysis further suggested that concept-map users linked different factors more frequently in their conversations, connecting academic requirements with career development, intrinsic interests, and external recognition in their discourse. Notably, these group differences remained after controlling for GPA in the ANCOVA models. These findings suggest that metacognitive scaffolding may reshape the way students engage with GenAI, with concept-map users shifting from brief exchanges to extended conversations covering multiple integrated factors related to their academic choices. [ABSTRACT FROM AUTHOR] |
| Copyright of Education Sciences is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: Metacognitive Scaffolding in the Age of GenAI: A Behavioral Analysis of Student–Chatbot Interactions During Course Selection. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Cuilian%22">Zhang, Cuilian</searchLink><br /><searchLink fieldCode="AR" term="%22Wei%2C+Wei%22">Wei, Wei</searchLink><br /><searchLink fieldCode="AR" term="%22Hu%2C+Xiao%22">Hu, Xiao</searchLink> – Name: TitleSource Label: Source Group: Src Data: Education Sciences; Jun2026, Vol. 16 Issue 6, p824, 23p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Concept+mapping%22">Concept mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Metacognition%22">Metacognition</searchLink><br /><searchLink fieldCode="DE" term="%22Curriculum%22">Curriculum</searchLink><br /><searchLink fieldCode="DE" term="%22Human-computer+interaction%22">Human-computer interaction</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+planning%22">Educational planning</searchLink><br /><searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+maps+%28Psychology%29%22">Cognitive maps (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Behavioral+assessment%22">Behavioral assessment</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Course selection presents a persistent challenge for students who often have difficulty articulating clear goals, integrating multiple considerations, and aligning academic choices with personal and professional aspirations. This study investigates whether concept mapping, as a metacognitive scaffolding tool, may shape how students interact with Generative AI (GenAI) systems during academic decision-making. In a randomized controlled experiment, 180 undergraduates at a polytechnic university in China were assigned to either a GenAI-only condition or a GenAI + Concept Map condition. After excluding 3 outlier participants, 177 students were included in the final analysis. Controlling for prior academic performance via ANCOVA, students with concept-map support showed different interaction patterns: they had a longer maximum consecutive-question chain within a session (GPA-adjusted means: 11.92 vs. 9.07 questions), formulated longer questions (15.27 vs. 11.93 words), and spent more time per conversation session on average (8.05 vs. 6.77 min). An analysis of conversation content showed that the concept-map group discussed a wider range of course selection factors (covering 4.46 vs. 3.66 main dimensions and 8.70 vs. 6.36 detailed factors). Epistemic Network Analysis further suggested that concept-map users linked different factors more frequently in their conversations, connecting academic requirements with career development, intrinsic interests, and external recognition in their discourse. Notably, these group differences remained after controlling for GPA in the ANCOVA models. These findings suggest that metacognitive scaffolding may reshape the way students engage with GenAI, with concept-map users shifting from brief exchanges to extended conversations covering multiple integrated factors related to their academic choices. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Education Sciences is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/educsci16060824 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 824 Subjects: – SubjectFull: Concept mapping Type: general – SubjectFull: Metacognition Type: general – SubjectFull: Curriculum Type: general – SubjectFull: Human-computer interaction Type: general – SubjectFull: Educational planning Type: general – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Cognitive maps (Psychology) Type: general – SubjectFull: Behavioral assessment Type: general Titles: – TitleFull: Metacognitive Scaffolding in the Age of GenAI: A Behavioral Analysis of Student–Chatbot Interactions During Course Selection. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhang, Cuilian – PersonEntity: Name: NameFull: Wei, Wei – PersonEntity: Name: NameFull: Hu, Xiao IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 22277102 Numbering: – Type: volume Value: 16 – Type: issue Value: 6 Titles: – TitleFull: Education Sciences Type: main |
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