Factor structure of artificial intelligence use in university teaching pedagogy

Emilio Flores-Mamani; Arcelia-Olga Rojas-Salazar; Pedro-Basilio Tapia-Espinoza; Constantino-Miguel Nieves-Barreto; Juan Inquilla-Mamani; Ányela-Yésica Flores-Yapuchura; Gilberto Vilca-Cutipa

doi:10.30935/cedtech/19132

Emilio Flores-Mamani ¹ ^* , Arcelia-Olga Rojas-Salazar ², Pedro-Basilio Tapia-Espinoza ¹, Constantino-Miguel Nieves-Barreto ², Juan Inquilla-Mamani ¹, Ányela-Yésica Flores-Yapuchura ², Gilberto Vilca-Cutipa ¹

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CONT ED TECHNOLOGY, Volume 18, Issue 4, Article No: ep682

https://doi.org/10.30935/cedtech/19132

Submitted: 22 March 2026, Published Online: 12 August 2026

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Abstract

The use of artificial intelligence (AI) in higher education pedagogy has gained increasing relevance; however, there remains a shortage of psychometrically validated instruments capable of assessing, in a multidimensional and context-specific manner, faculty adoption of these technologies. The aim of this study was to identify the factorial structure and evaluate the psychometric properties of an instrument designed to measure AI use among university faculty. The instrument was developed based on the unified theory of acceptance and use of technology and was administered to a convenience sample of 330 university instructors. Exploratory factor analysis revealed a robust seven-factor structure explaining 66.90% of the total variance, allowing the refinement and optimization of the instrument from 50 to 30 items. The final scale demonstrated excellent overall internal consistency (Cronbach’s alpha = 0.913). It is concluded that the developed instrument is a valid and reliable tool for higher education institutions to assess and diagnose faculty levels of AI adoption, thereby facilitating the design of context-specific institutional policies and effective professional development programs in AI-enhanced pedagogy.

Keywords: artificial intelligence, university pedagogy, exploratory factor analysis, reliability

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Citation

Flores-Mamani, E., Rojas-Salazar, A.-O., Tapia-Espinoza, P.-B., Nieves-Barreto, C.-M., Inquilla-Mamani, J., Flores-Yapuchura, Á.-Y., & Vilca-Cutipa, G. (2026). Factor structure of artificial intelligence use in university teaching pedagogy. Contemporary Educational Technology, 18(4), Article ep682. https://doi.org/10.30935/cedtech/19132

Flores-Mamani, E., Rojas-Salazar, A.-O., Tapia-Espinoza, P.-B., Nieves-Barreto, C.-M., Inquilla-Mamani, J., Flores-Yapuchura, Á.-Y., and Vilca-Cutipa, G. (2026). Factor structure of artificial intelligence use in university teaching pedagogy. Contemporary Educational Technology, 18(4), ep682. https://doi.org/10.30935/cedtech/19132

Flores-Mamani E, Rojas-Salazar AO, Tapia-Espinoza PB, et al. Factor structure of artificial intelligence use in university teaching pedagogy. CONT ED TECHNOLOGY. 2026;18(4), ep682. https://doi.org/10.30935/cedtech/19132

Flores-Mamani, Emilio, Arcelia-Olga Rojas-Salazar, Pedro-Basilio Tapia-Espinoza, Constantino-Miguel Nieves-Barreto, Juan Inquilla-Mamani, Ányela-Yésica Flores-Yapuchura, and Gilberto Vilca-Cutipa. "Factor structure of artificial intelligence use in university teaching pedagogy". Contemporary Educational Technology 2026 18 no. 4 (2026): ep682. https://doi.org/10.30935/cedtech/19132

Flores-Mamani, Emilio et al. "Factor structure of artificial intelligence use in university teaching pedagogy". Contemporary Educational Technology, vol. 18, no. 4, 2026, ep682. https://doi.org/10.30935/cedtech/19132

Flores-Mamani E, Rojas-Salazar AO, Tapia-Espinoza PB, Nieves-Barreto CM, Inquilla-Mamani J, Flores-Yapuchura ÁY, et al. Factor structure of artificial intelligence use in university teaching pedagogy. CONT ED TECHNOLOGY. 2026;18(4):ep682. https://doi.org/10.30935/cedtech/19132