Conocimiento en IA, desempeño y autoeficiencia en docentes de educación secundaria y superior

The accelerated advancement of Artificial Intelligence (AI) has generated new challenges in the educational field, particularly regarding teacher preparedness to integrate these technologies into their pedagogical practice. The objective of this study was to evaluate the influence of AI knowledge levels on the professional performance and self-efficacy of secondary and higher education teachers. A quantitative approach was adopted, employing a non-experimental, cross-sectional, and correlational design. The sample consisted of 108 teachers in the Dominican Republic, selected through non-probabilistic sampling. A structured questionnaire was applied, which included sociodemographic variables, AI knowledge levels, and Likert-type scales to measure their impact on performance and teaching self-efficacy. The results indicated that 51% of participants had a basic knowledge of AI, while only 11% reached an advanced level. Nevertheless, 53.7% stated that the use of AI consistently improves their performance, and 47.2% considered that AI training significantly enhanced their self-efficacy. Chi-square tests revealed statistically significant relationships between AI knowledge and performance (p = 0.018), as well as teaching self-efficacy (p = 0.0007). In conclusion, the findings highlight the need to implement continuous and differentiated training programs that strengthen teachers’ technological competencies, foster their confidence in educational practice, and contribute to bridging the digital divide. Furthermore, it is suggested to design sustainable educational policies that enhance the positive impact of AI on teaching.