A Critical Analysis of GAI Learning Research: From Theory to Implementation Risks
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| Title: | A Critical Analysis of GAI Learning Research: From Theory to Implementation Risks |
|---|---|
| Language: | English |
| Authors: | Inna Artemova |
| Source: | Online Learning. 2025 29(4):390-417. |
| Availability: | Online Learning Consortium, Inc. P.O. Box 1238, Newburyport, MA 01950. Tel: 888-898-6209; Fax: 888-898-6209; e-mail: olj@onlinelearning-c.org; Web site: https://olj.onlinelearningconsortium.org/index.php/olj/index |
| Peer Reviewed: | Y |
| Page Count: | 28 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Artificial Intelligence, Technology Uses in Education, Educational Research, Risk, Developmentally Appropriate Practices, Cultural Differences, Socioeconomic Status, Learning Processes |
| ISSN: | 2472-5749 2472-5730 |
| Abstract: | While existing literature documents the benefits and concerns of Generative Artificial Intelligence (GAI) for learning processes, it largely overlooks fundamental learning theories such as Cognitive Load Theory, Constructivism, Activity Theory, and Bloom's Taxonomy. This study employs a scoping review methodology to identify current research gaps from the perspective of these theories, examining potential risks associated with uncritical GAI usage in learning environments. The results demonstrate that the current discourse focuses on operational aspects, while the learning fundamentals are largely overlooked. The identified risks include the bypassing of essential cognitive processing, fostering illusions of understanding, disrupting social and collective learning dynamics, compromising authentic motivation, and interfering with knowledge transfer and application. These risks manifest differently across various learner profiles, from K-12 students to professionals, with implications extending beyond individual learning outcomes to organizational effectiveness and information quality in broader societal contexts. The findings indicate the necessity for a structured, level-appropriate approach to GAI implementation in educational and professional settings. Future research should investigate long-term impacts of GAI on learning outcomes across different educational levels and diverse cultural and socioeconomic contexts, focusing on developing strategies that mitigate risks and support, rather than circumvent, essential learning processes identified by major learning theories. This research offers a theoretically grounded perspective that can inform more nuanced policy approaches to balance technological advancement with educational effectiveness across diverse global contexts. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1490383 |
| Database: | ERIC |
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| Items | – Name: Title Label: Title Group: Ti Data: A Critical Analysis of GAI Learning Research: From Theory to Implementation Risks – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Inna+Artemova%22">Inna Artemova</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Online+Learning%22"><i>Online Learning</i></searchLink>. 2025 29(4):390-417. – Name: Avail Label: Availability Group: Avail Data: Online Learning Consortium, Inc. P.O. Box 1238, Newburyport, MA 01950. Tel: 888-898-6209; Fax: 888-898-6209; e-mail: olj@onlinelearning-c.org; Web site: https://olj.onlinelearningconsortium.org/index.php/olj/index – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 28 – Name: DatePubCY Label: Publication Date Group: Date Data: 2025 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Research%22">Educational Research</searchLink><br /><searchLink fieldCode="DE" term="%22Risk%22">Risk</searchLink><br /><searchLink fieldCode="DE" term="%22Developmentally+Appropriate+Practices%22">Developmentally Appropriate Practices</searchLink><br /><searchLink fieldCode="DE" term="%22Cultural+Differences%22">Cultural Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Socioeconomic+Status%22">Socioeconomic Status</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Processes%22">Learning Processes</searchLink> – Name: ISSN Label: ISSN Group: ISSN Data: 2472-5749<br />2472-5730 – Name: Abstract Label: Abstract Group: Ab Data: While existing literature documents the benefits and concerns of Generative Artificial Intelligence (GAI) for learning processes, it largely overlooks fundamental learning theories such as Cognitive Load Theory, Constructivism, Activity Theory, and Bloom's Taxonomy. This study employs a scoping review methodology to identify current research gaps from the perspective of these theories, examining potential risks associated with uncritical GAI usage in learning environments. The results demonstrate that the current discourse focuses on operational aspects, while the learning fundamentals are largely overlooked. The identified risks include the bypassing of essential cognitive processing, fostering illusions of understanding, disrupting social and collective learning dynamics, compromising authentic motivation, and interfering with knowledge transfer and application. These risks manifest differently across various learner profiles, from K-12 students to professionals, with implications extending beyond individual learning outcomes to organizational effectiveness and information quality in broader societal contexts. The findings indicate the necessity for a structured, level-appropriate approach to GAI implementation in educational and professional settings. Future research should investigate long-term impacts of GAI on learning outcomes across different educational levels and diverse cultural and socioeconomic contexts, focusing on developing strategies that mitigate risks and support, rather than circumvent, essential learning processes identified by major learning theories. This research offers a theoretically grounded perspective that can inform more nuanced policy approaches to balance technological advancement with educational effectiveness across diverse global contexts. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2025 – Name: AN Label: Accession Number Group: ID Data: EJ1490383 |
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| RecordInfo | BibRecord: BibEntity: Languages: – Text: English PhysicalDescription: Pagination: PageCount: 28 StartPage: 390 Subjects: – SubjectFull: Artificial Intelligence Type: general – SubjectFull: Technology Uses in Education Type: general – SubjectFull: Educational Research Type: general – SubjectFull: Risk Type: general – SubjectFull: Developmentally Appropriate Practices Type: general – SubjectFull: Cultural Differences Type: general – SubjectFull: Socioeconomic Status Type: general – SubjectFull: Learning Processes Type: general Titles: – TitleFull: A Critical Analysis of GAI Learning Research: From Theory to Implementation Risks Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Inna Artemova IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 2472-5749 – Type: issn-electronic Value: 2472-5730 Numbering: – Type: volume Value: 29 – Type: issue Value: 4 Titles: – TitleFull: Online Learning Type: main |
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