Psychometric Evidence and Associative Analysis of Dimensions of Familiarity, Frequency of Use and Satisfaction with AI Tools in University Research Training

Casimiro Urcos W.H.; Casimiro Urcos C.N.; Casimiro Urcos J.F.; Quinteros Osorio R.O. · International Journal of Learning, Teaching and Educational Research (2026) · DOI: 10.26803/ijlter.25.5.34

Resumen

The study examined the psychometric properties of the instrument and the associations between the dimensions of familiarity, frequency of use, and perceived satisfaction regarding the use of artificial intelligence (AI) tools in university research training. A quantitative approach was adopted, with a non-experimental, cross-sectional, and descriptive-correlational design, involving a final sample of 105 students. Data were collected using a 30-item questionnaire, and the analysis included exploratory factor analysis to assess construct validity, internal consistency estimation (Cronbach’s α and McDonald’s ω), and bivariate association analysis through Spearman correlations and chi-square tests. The results showed a predominance of low levels across the three dimensions, indicating a limited integration of these technological tools in university research training processes. The factor analysis confirmed a three-dimensional structure consistent with the theoretical model, explaining 72.8% of the variance, with high reliability (α = .974; ω = .974). Likewise, positive and statistically significant associations were found between the dimensions, with a particularly strong relationship between frequency of use and satisfaction (ρ = .925; p < .001). Overall, the findings suggest that the adoption of AI is still at an early stage, which highlights the need to strengthen AI literacy strategies that integrate technical, ethical, and methodological dimensions in higher education contexts. © The Authors.

Instituciones: Universidad Nacional de Educación Enrique Guzmán y Valle