AI-Related Competence, Innovation, Perceived Threats, Ethics, and Job Satisfaction: A Comparative Study of Pre-Service and In-Service Teachers

Abstract

Artificial intelligence (AI) has become a key driver of transformation in educational contexts, influencing both teaching and learning processes as well as the digital competencies required by teachers and students. In this context, understanding how AI is perceived, used, and valued is essential for guiding educational innovation in a critical and sustainable way. This study examines digital competence in artificial intelligence and its relationship with educational innovation, perceived threats, and job satisfaction, comparing university students and in-service teachers. The research adopts a quantitative approach based on a questionnaire administered to 355 participants. The results indicate that students demonstrate higher levels of technical skills, innovative vision, and more positive attitudes toward the educational use of AI, whereas teachers adopt a more cautious stance, mainly due to a lack of specific training and the absence of clear institutional guidelines. Significant differences are also found regarding perceived threats, with students showing greater awareness of risks such as plagiarism, algorithmic bias, and the potential erosion of critical thinking. In contrast, no significant differences are identified in ethics or job satisfaction. In conclusion, the study reveals a competence gap between both groups and highlights the need to redesign initial teacher education and promote continuous professional development in AI. Finally, it emphasizes the importance of integrating artificial intelligence into education from a critical, ethical, and human-centered perspective.