Beyond expert knowledge toward idea innovation: potential and challenges of a generative AI-supported jigsaw method.
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| Title: | Beyond expert knowledge toward idea innovation: potential and challenges of a generative AI-supported jigsaw method. |
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| Authors: | Naganuma, Shotaro1 (AUTHOR) naganuma.shotaro.062@m.kyushu-u.ac.jp, Shibukawa, Sachika2 (AUTHOR) sshibukawa193@g.chuo-u.ac.jp, Minematsu, Tsubasa3 (AUTHOR) minematsu@ai.kyutech.ac.jp, Ohno, Aikana1 (AUTHOR) ohnoaikana@artsci.kyushu-u.ac.jp, Wakihama, Yukinori1 (AUTHOR) wakihama.yukinori.954@m.kyushu-u.ac.jp |
| Source: | International Journal of Educational Technology in Higher Education. 5/29/2026, Vol. 23 Issue 1, p1-31. 31p. |
| Subject Terms: | *Generative artificial intelligence, *Instructional systems design, *Higher education, *Cognitive ability, *Interdisciplinary education, *Group work in education, Originality |
| Abstract: | Recent societal issues require higher education institutions to engage students in interdisciplinary knowledge creation beyond knowledge acquisition. While the jigsaw method is expected to facilitate novice learners' engagement in interdisciplinary collaborative knowledge creation, authoritative expert materials limit learners' agency beyond the given knowledge. To overcome this constraint, this study proposes the Knowledge Expansive Jigsaw Method, which integrates Generative AI (GenAI) as a resource for expanding ideas beyond expert materials. Using a two-cycle design-based research approach with 70 freshmen using a conjecture map as our framework, we investigated how the implemented GenAI-supported jigsaw method promotes students' ideation processes. Specifically, students designed illustrations of the "Future classroom of our university in 2050." The instructional design introduced an expansion phase after a cognitive trigger and positioned GenAI as both a possibility engine and a co-designer. Students' discourse, GenAI usage records, and final presentations were analyzed using the Knowledge-Building Discourse Explorer (KBDeX) and rubric-based evaluation. KBDeX analysis confirmed the co-occurrence of AI-inspired and human-generated idea expansion across groups. Comparison of the outcomes did not demonstrate improvements after design refinement in Cycle 2; whereas outcomes in Cycle 1 were diverse, those in Cycle 2 converged at an emerging level. The results suggested both the potential—the proposed design consistently promoted idea expansion beyond expert knowledge—and the challenge—high-level idea innovation were rare under the GenAI-supported jigsaw method. Future studies should focus on refining AI systems, instructional designs toward idea innovation and analysis to identify and validate other promising processes critical for idea innovation. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Educational Technology in Higher Education is the property of Springer Nature 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.) | |
| Database: | Education Research Complete |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 194092190 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Beyond expert knowledge toward idea innovation: potential and challenges of a generative AI-supported jigsaw method. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Naganuma%2C+Shotaro%22">Naganuma, Shotaro</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> naganuma.shotaro.062@m.kyushu-u.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Shibukawa%2C+Sachika%22">Shibukawa, Sachika</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> sshibukawa193@g.chuo-u.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Minematsu%2C+Tsubasa%22">Minematsu, Tsubasa</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> minematsu@ai.kyutech.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Ohno%2C+Aikana%22">Ohno, Aikana</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ohnoaikana@artsci.kyushu-u.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Wakihama%2C+Yukinori%22">Wakihama, Yukinori</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wakihama.yukinori.954@m.kyushu-u.ac.jp</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Educational+Technology+in+Higher+Education%22">International Journal of Educational Technology in Higher Education</searchLink>. 5/29/2026, Vol. 23 Issue 1, p1-31. 31p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Instructional+systems+design%22">Instructional systems design</searchLink><br />*<searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br />*<searchLink fieldCode="DE" term="%22Cognitive+ability%22">Cognitive ability</searchLink><br />*<searchLink fieldCode="DE" term="%22Interdisciplinary+education%22">Interdisciplinary education</searchLink><br />*<searchLink fieldCode="DE" term="%22Group+work+in+education%22">Group work in education</searchLink><br /><searchLink fieldCode="DE" term="%22Originality%22">Originality</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Recent societal issues require higher education institutions to engage students in interdisciplinary knowledge creation beyond knowledge acquisition. While the jigsaw method is expected to facilitate novice learners' engagement in interdisciplinary collaborative knowledge creation, authoritative expert materials limit learners' agency beyond the given knowledge. To overcome this constraint, this study proposes the Knowledge Expansive Jigsaw Method, which integrates Generative AI (GenAI) as a resource for expanding ideas beyond expert materials. Using a two-cycle design-based research approach with 70 freshmen using a conjecture map as our framework, we investigated how the implemented GenAI-supported jigsaw method promotes students' ideation processes. Specifically, students designed illustrations of the "Future classroom of our university in 2050." The instructional design introduced an expansion phase after a cognitive trigger and positioned GenAI as both a possibility engine and a co-designer. Students' discourse, GenAI usage records, and final presentations were analyzed using the Knowledge-Building Discourse Explorer (KBDeX) and rubric-based evaluation. KBDeX analysis confirmed the co-occurrence of AI-inspired and human-generated idea expansion across groups. Comparison of the outcomes did not demonstrate improvements after design refinement in Cycle 2; whereas outcomes in Cycle 1 were diverse, those in Cycle 2 converged at an emerging level. The results suggested both the potential—the proposed design consistently promoted idea expansion beyond expert knowledge—and the challenge—high-level idea innovation were rare under the GenAI-supported jigsaw method. Future studies should focus on refining AI systems, instructional designs toward idea innovation and analysis to identify and validate other promising processes critical for idea innovation. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Educational Technology in Higher Education is the property of Springer Nature 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=194092190 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1186/s41239-026-00598-6 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 31 StartPage: 1 Subjects: – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Instructional systems design Type: general – SubjectFull: Higher education Type: general – SubjectFull: Cognitive ability Type: general – SubjectFull: Interdisciplinary education Type: general – SubjectFull: Group work in education Type: general – SubjectFull: Originality Type: general Titles: – TitleFull: Beyond expert knowledge toward idea innovation: potential and challenges of a generative AI-supported jigsaw method. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Naganuma, Shotaro – PersonEntity: Name: NameFull: Shibukawa, Sachika – PersonEntity: Name: NameFull: Minematsu, Tsubasa – PersonEntity: Name: NameFull: Ohno, Aikana – PersonEntity: Name: NameFull: Wakihama, Yukinori IsPartOfRelationships: – BibEntity: Dates: – D: 29 M: 05 Text: 5/29/2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 23659440 Numbering: – Type: volume Value: 23 – Type: issue Value: 1 Titles: – TitleFull: International Journal of Educational Technology in Higher Education Type: main |
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