Factorial Structure and Measurement Invariance of the General Atitudes Toward Artificial Intelligence Scale for University Students
The study aims to investigate the factorial structure (FS) and measurement invariance (MI) of the General Attitudes Toward Artificial Intelligence Scale (GAAIS) on a sample of students from Taif University. The instrument used was the GAAIS developed by [1] and translated by the researcher. The sca...
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| Format: | Article |
| Language: | English |
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Qubahan
2025-04-01
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| Series: | Qubahan Academic Journal |
| Online Access: | https://journal.qubahan.com/index.php/qaj/article/view/1672 |
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| Summary: | The study aims to investigate the factorial structure (FS) and measurement invariance (MI) of the General Attitudes Toward Artificial Intelligence Scale (GAAIS) on a sample of students from Taif University. The instrument used was the GAAIS developed by [1] and translated by the researcher. The scale was administered to a sample of 461 university students. The study results indicated that the scale's structure aligned with the confirmatory factor analysis model, with fit indices demonstrating good fit: (χ^2⁄df=611.77⁄169=3.62), Good of fit Index (GFI) = 0.855, Tucker-Lewis index (TLI) = 0.837, and Root Mean square of Approximation (RMSEA) = 0.075. These results confirm the construct validity and the scale's suitability for the data. The composite reliability coefficients were 0.828 and 0.869, and Cronbach’s alpha reliability coefficients were 0.832 and 0.869 for the positive sub-dimensions (opportunities, benefits, societal and personal utility, and positive emotions) and the negative sub-dimensions (fears and negative emotions), respectively. Additionally, the study confirms configural, metric, scalar, and residual invariance across the male and female study groups. The results confirmed that the scale has high reliability and validity and is unbiased regarding the gender variable. The study also confirms the suitability of the instrument for measuring general attitudes toward artificial intelligence (AI) among university students.
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| ISSN: | 2709-8206 |