The artificial intelligence in the formation of software engineers in Sacred Domingo of the Tsáchilas

Abstract

This study examines the perceptions of 100 Software Engineering instructors at higher education institutions in Santo Domingo de los Tsáchilas regarding the adoption of Artificial Intelligence (AI) in their teaching. Through surveys and semi-structured interviews, five key factors were identified: teacher training, institutional and regulatory support, technological infrastructure, instructors’ attitudes and prior knowledge, and ethics and trust in AI. The Analytic Hierarchy Process (AHP) was employed to weight each factor’s importance, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to rank three implementation strategies: intensive training workshops, institutional policies, and teacher practice communities. Findings indicate that continuous training is viewed as most critical by instructors, and that intensive training workshops are perceived as the closest to the ideal solution. Implications for educational policy are discussed, and recommendations are offered to strengthen effective AI integration in software education.