Browsing by Author "Zhu Ordoñez, Erick Daniel"

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    Sistema de tutoría docente basado en IA generativa supervisada.
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas Electrónica e Industrial. Carrera de Software., 2026-07-08) Zhu Ordoñez, Erick Daniel; Fernández Peña, Félix Oscar; Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas Electrónica e Industrial. Carrera de Software.
    In higher education, students often receive late or intermittent feedback, and teachers rarely have timely information about their groups’ learning. This work develops a teacher-supervised generative AI tutoring system, which provides students with support aligned to the content of each lesson and gives teachers a consolidated view of their group’s progress. The system exposes a REST API through which the intelligent tutor and the feedback features were integrated into NousAI, which brings together three complementary proposals. The proposal articulates three components: an intelligent tutor contextualized by learning object, weekly feedback for the teacher at the learning-object and module levels, and weekly feedback for the student by module. Supervision rests with the teacher, who decides which learning objects are published and accesses feedback that takes into account students’ actions. Validation applied the System Usability Scale questionnaire to a sample of students and a qualitative questionnaire to five teachers. Perceived usability exceeded the adopted reference value, with a mean of 71.09 out of 100 from 154 valid responses and a 95 % confidence interval between 68.34 and 73.84. Usability proved solid (72.79) against a lower learnability (64.29), which concentrates the greatest room for improvement. Teachers expressed unanimous willingness to keep using it, with confidence in the information generated by the model as the main reservation.