The role of learner trust in generative artificially intelligent learning environments.
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| Title: | The role of learner trust in generative artificially intelligent learning environments. |
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| Authors: | Goldshtein, Maria1 (AUTHOR) maria.goldshtein@asu.edu, Schroeder, Noah L.2 (AUTHOR), Chiou, Erin K.3 (AUTHOR) |
| Source: | Journal of Engineering Education. Apr2025, Vol. 114 Issue 2, p1-4. 4p. |
| Subject Terms: | *Generative artificial intelligence, *Engineering education, *Educators, *Educational outcomes, Trust, Language models, Generative pre-trained transformers |
| Abstract: | The article discusses the increasing integration of generative artificial intelligence (AI) tools, such as large language models (LLMs) and generative pre‐trained transformer (GPT) models, into educational settings. Researchers emphasize the importance of learners' trust as a critical factor in the successful implementation and use of generative AI in education. The study explores how trust influences learning outcomes and credibility in the context of generative AI tools, particularly in engineering education. As generative AI becomes more prevalent in educational settings, understanding and fostering relational trust with students, teachers, and other stakeholders is crucial for effective implementation and support. [Extracted from the article] |
| Copyright of Journal of Engineering Education is the property of Wiley-Blackwell 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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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 184801323 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: The role of learner trust in generative artificially intelligent learning environments. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Goldshtein%2C+Maria%22">Goldshtein, Maria</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> maria.goldshtein@asu.edu</i><br /><searchLink fieldCode="AR" term="%22Schroeder%2C+Noah+L%2E%22">Schroeder, Noah L.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chiou%2C+Erin+K%2E%22">Chiou, Erin K.</searchLink><relatesTo>3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Engineering+Education%22">Journal of Engineering Education</searchLink>. Apr2025, Vol. 114 Issue 2, p1-4. 4p. – 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="%22Engineering+education%22">Engineering education</searchLink><br />*<searchLink fieldCode="DE" term="%22Educators%22">Educators</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+outcomes%22">Educational outcomes</searchLink><br /><searchLink fieldCode="DE" term="%22Trust%22">Trust</searchLink><br /><searchLink fieldCode="DE" term="%22Language+models%22">Language models</searchLink><br /><searchLink fieldCode="DE" term="%22Generative+pre-trained+transformers%22">Generative pre-trained transformers</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The article discusses the increasing integration of generative artificial intelligence (AI) tools, such as large language models (LLMs) and generative pre‐trained transformer (GPT) models, into educational settings. Researchers emphasize the importance of learners' trust as a critical factor in the successful implementation and use of generative AI in education. The study explores how trust influences learning outcomes and credibility in the context of generative AI tools, particularly in engineering education. As generative AI becomes more prevalent in educational settings, understanding and fostering relational trust with students, teachers, and other stakeholders is crucial for effective implementation and support. [Extracted from the article] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Engineering Education is the property of Wiley-Blackwell 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=184801323 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/jee.70000 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 4 StartPage: 1 Subjects: – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Engineering education Type: general – SubjectFull: Educators Type: general – SubjectFull: Educational outcomes Type: general – SubjectFull: Trust Type: general – SubjectFull: Language models Type: general – SubjectFull: Generative pre-trained transformers Type: general Titles: – TitleFull: The role of learner trust in generative artificially intelligent learning environments. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Goldshtein, Maria – PersonEntity: Name: NameFull: Schroeder, Noah L. – PersonEntity: Name: NameFull: Chiou, Erin K. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10694730 Numbering: – Type: volume Value: 114 – Type: issue Value: 2 Titles: – TitleFull: Journal of Engineering Education Type: main |
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