Psychometric validation of the artificial intelligence anxiety scale: A confirmatory factor analysis for academic research.
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| Title: | Psychometric validation of the artificial intelligence anxiety scale: A confirmatory factor analysis for academic research. |
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| Authors: | Alshaibani, Mariam Hejab1, Al-Rahmi, Waleed Mugahed2 waleed.alrahmi@dau.edu.sa, Tawafak, Ragad M.3 |
| Source: | Contemporary Educational Technology. Oct2025, Vol. 17 Issue 4, p1-16. 16p. |
| Subject Terms: | *Artificial intelligence, *Research skills, *Preparedness, *Ethical problems, University research, Psychometrics, Confirmatory factor analysis, Psychological distress |
| Geographic Terms: | Saudi Arabia |
| Abstract: | This study introduces and validates the artificial intelligence anxiety scale (AIAS), a novel instrument designed to measure researchers' anxieties when employing artificial intelligence (AI) tools in academic writing. As AI technologies rapidly infiltrate scholarly work, however, the primary concern grows about their ethical implications, impact on traditional research skills, and the lack of institutional readiness issues that remain underexplored in existing literature. Addressing this critical gap, the AIAS offers a novel framework grounded in real-world academic concerns. Using an inductive approach, data were collected from 219 faculty members and graduate students at Taif University, Saudi Arabia, revealing four core dimensions of AI-related anxiety: (1) concerns about the accuracy of AI outputs, (2) fear of committing plagiarism, (3) lack of institutional guidelines, and (4) fear of losing research skills. Exploratory and confirmatory factor analyses confirmed the existence of these factors, and reliability testing indicated robust internal consistency. By offering the first validated tool specifically tailored to measure AI-related anxiety in academic contexts, this study provides a significant resource for researchers and institutions. Its application can guide universities in devising training and support initiatives to ensure the ethical and practical integration of AI, thereby sustaining the integrity of traditional research competencies and enhancing the overall quality and credibility of academic endeavors. [ABSTRACT FROM AUTHOR] |
| Copyright of Contemporary Educational Technology is the property of Bastas Publications 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 |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 190739395 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Psychometric validation of the artificial intelligence anxiety scale: A confirmatory factor analysis for academic research. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Alshaibani%2C+Mariam+Hejab%22">Alshaibani, Mariam Hejab</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Al-Rahmi%2C+Waleed+Mugahed%22">Al-Rahmi, Waleed Mugahed</searchLink><relatesTo>2</relatesTo><i> waleed.alrahmi@dau.edu.sa</i><br /><searchLink fieldCode="AR" term="%22Tawafak%2C+Ragad+M%2E%22">Tawafak, Ragad M.</searchLink><relatesTo>3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Contemporary+Educational+Technology%22">Contemporary Educational Technology</searchLink>. Oct2025, Vol. 17 Issue 4, p1-16. 16p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Research+skills%22">Research skills</searchLink><br />*<searchLink fieldCode="DE" term="%22Preparedness%22">Preparedness</searchLink><br />*<searchLink fieldCode="DE" term="%22Ethical+problems%22">Ethical problems</searchLink><br /><searchLink fieldCode="DE" term="%22University+research%22">University research</searchLink><br /><searchLink fieldCode="DE" term="%22Psychometrics%22">Psychometrics</searchLink><br /><searchLink fieldCode="DE" term="%22Confirmatory+factor+analysis%22">Confirmatory factor analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+distress%22">Psychological distress</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Saudi+Arabia%22">Saudi Arabia</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study introduces and validates the artificial intelligence anxiety scale (AIAS), a novel instrument designed to measure researchers' anxieties when employing artificial intelligence (AI) tools in academic writing. As AI technologies rapidly infiltrate scholarly work, however, the primary concern grows about their ethical implications, impact on traditional research skills, and the lack of institutional readiness issues that remain underexplored in existing literature. Addressing this critical gap, the AIAS offers a novel framework grounded in real-world academic concerns. Using an inductive approach, data were collected from 219 faculty members and graduate students at Taif University, Saudi Arabia, revealing four core dimensions of AI-related anxiety: (1) concerns about the accuracy of AI outputs, (2) fear of committing plagiarism, (3) lack of institutional guidelines, and (4) fear of losing research skills. Exploratory and confirmatory factor analyses confirmed the existence of these factors, and reliability testing indicated robust internal consistency. By offering the first validated tool specifically tailored to measure AI-related anxiety in academic contexts, this study provides a significant resource for researchers and institutions. Its application can guide universities in devising training and support initiatives to ensure the ethical and practical integration of AI, thereby sustaining the integrity of traditional research competencies and enhancing the overall quality and credibility of academic endeavors. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Contemporary Educational Technology is the property of Bastas Publications 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: 10.30935/cedtech/17309 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 1 Subjects: – SubjectFull: Artificial intelligence Type: general – SubjectFull: Research skills Type: general – SubjectFull: Preparedness Type: general – SubjectFull: Ethical problems Type: general – SubjectFull: University research Type: general – SubjectFull: Psychometrics Type: general – SubjectFull: Confirmatory factor analysis Type: general – SubjectFull: Psychological distress Type: general – SubjectFull: Saudi Arabia Type: general Titles: – TitleFull: Psychometric validation of the artificial intelligence anxiety scale: A confirmatory factor analysis for academic research. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Alshaibani, Mariam Hejab – PersonEntity: Name: NameFull: Al-Rahmi, Waleed Mugahed – PersonEntity: Name: NameFull: Tawafak, Ragad M. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 1309517X Numbering: – Type: volume Value: 17 – Type: issue Value: 4 Titles: – TitleFull: Contemporary Educational Technology Type: main |
| ResultId | 1 |
