Determinant factors in the teaching-learning process of software development: An AI-Assisted analysis
The objective of this study is to determine which factors influence the teaching and learning process of programming related subjects. Methodologically, a data collection instrument was applied using a purposive non-probability sampling technique to a sample of 39 students in a face-to-face and online learning environment. Data processing was performed using artificial intelligence tools. The results reveal that 85% of the subjects show positive aptitudes driven by vocation and a cognitive exhaustion index of 72%. This finding highlights that mental overload makes vocational interest insufficient, since abstract thinking is necessary for the coding process. The contribution of this work is to offer a diagnostic tool for the creation of pedagogical strategies that improve academic performance by mitigating mental exhaustion without affecting student motivation.