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Psychometric properties of an instrument to assess the level of knowledge about artificial intelligence in university professors

By
Camilo Andrés Silva-Sánchez ,
Camilo Andrés Silva-Sánchez

Universidad Andrés Bello, Facultad de Enfermería. Santiago de Chile, Chile

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Abstract

Introduction: Knowledge of AI in university professors allows them to integrate these technological tools into their teaching strategies and thus improve the quality of learning.
Goal: Determine the sustainable factorial structure of the dimension of relations of an instrument to assess the level of knowledge of artificial intelligence in university professors.
Methods: A cross-sectional, metric validating study was carried out. A sample of 83 university professors was chosen. An instrument on artificial intelligence for university professors was applied, said instrument being composed of 15 questions divided into three sections. A psychometric analysis was conducted in order to assess its validity and reliability.
Results: The results show that Part 1 has an alpha coefficient of 0.77, Part 2 has an alpha coefficient of 0.65, and Part 3 has an alpha coefficient of 0.83. The alpha coefficients for each subscale (0.77 for Part 1, 0.65 for Part 2 and 0.83 for Part 3) indicate that the instrument has good internal consistency and the questions within each subscale relate to one another. Ratio χ2/gl of 2.1 indicates good fit of the model, and the GFI, NFI and CFI values are close to 1, which indicates good fit of the model.
Conclusions: The results of this study support the validity, reliability and sustainable factorial structure of the instrument on artificial intelligence for university professors, which makes it an adequate tool to assess the level of knowledge of AI in university professors.

How to Cite

1.
Silva-Sánchez CA. Psychometric properties of an instrument to assess the level of knowledge about artificial intelligence in university professors. Metaverse Basic and Applied Research [Internet]. 2022 Dec. 26 [cited 2024 May 27];1:14. Available from: https://mr.saludcyt.ar/index.php/mr/article/view/14

The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.

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