Learning Strategies with Artificial Intelligence Tools in Distance Education: a Cross-sectional Analysis in Teachers Attending a Master's Degree Program

Abstract

The objective of this study was to identify the relationship between the use of Artificial Intelligence tools by teachers pursuing a master’s degree in Basic Education at the Bolivarian University of Ecuador and their academic performance in learning activities in contact with the teacher, autonomous and practical-experimental. A quantitative methodology with cross-sectional design and correlational scope was applied, using structured questionnaires to 314 teachers. The results showed a frequent use of tools such as ChatGPT, Grammarly and DeepL, and a significant positive correlation between their use and academic performance in the different types of learning. It is concluded that the autonomous and diversified integration of Artificial Intelligence strengthens the formative process in graduate distance education, consolidating itself as a key pedagogical resource.