Personal, Academic and Professional Characteristics Associated with Perceptions of Artificial Intelligence Among Practising and Prospective Teachers

The increasing integration of artificial intelligence (AI) into education has highlighted the importance of understanding how practising and prospective teachers perceive its pedagogical, technological, socio-emotional and ethical implications. This study examined associations between personal, academic and professional characteristics and four dimensions of educational AI perception, drawing conceptually on UNESCO's AI Competency Framework for Teachers and the European Framework for the Digital Competence of Educators (DigCompEdu). A quantitative, non-experimental, cross-sectional research design was employed, involving 1,292 participants from Andalusia, Spain, comprising 1,078 university students preparing for teaching careers and 214 professionally active or non-active teachers. Data were collected using the 39-item ACISE-IA questionnaire, which examines socio-emotional and affective perceptions, positive attitudes towards educational AI, perceived digital competence, and critical perception and ethical responsibility. Statistical analyses included Pearson's correlations, independent-samples t-tests and one-way analysis of variance (ANOVA). Age and teaching experience demonstrated statistically significant but relatively weak negative associations with selected dimensions of educational AI perception, while academic achievement exhibited negligible positive correlations (r = 0.065–0.077). Statistically significant differences were also identified across academic disciplines, employment categories and academic years, although their magnitude and direction varied. University students generally reported more favourable socio-emotional perceptions and attitudes towards AI than the combined teacher group, whereas differences in perceived digital competence and ethical responsibility were not statistically significant. Academic-year comparisons revealed non-linear patterns, particularly among master's students. The findings demonstrate that educational AI perceptions vary across personal, academic and professional characteristics, although these factors explain only a limited proportion of the observed differences. The results highlight the importance of considering socio-emotional, attitudinal, technological and ethical dimensions when developing teacher education and professional development opportunities. Further research employing representative samples and multivariable analytical approaches is required to clarify these relationships and inform context-sensitive strategies for responsible AI integration.