Nowadays, there has been a significant increase in the number of papers regarding the integration of real-world experiences into academic programs by stimulating interactions between students and teachers. Moreover, recent advancements in Artificial Intelligence (AI) have significantly impacted teacher professional development in higher education worldwide. For instance, in Spain, initiatives like the AI Classroom Professional Development program focus on the integration of practical applications, including AI-driven personalized learning plans and automated administrative tasks, which allow teachers to focus more on interactive and creative teaching methods. Similarly, in Chile programs emphasize the use of AI tools to improve classroom experiences and student outcomes, and AI-powered platforms are used to track student progress and provide real-time feedback.

By combining large volumes of data with machine learning algorithms, AI optimizes resources and enables the creation of more personalized experiences. However, implementing AI in education comes with challenges such as pedagogical knowledge and the need for specialized expertise.

In this paper, we describe the Teaching Through Interactions (TTI) framework for understanding and improving involvement in the classroom using an AI tool among teachers and students. This work aims to show how an AI tool can enhance the understanding of student learning experiences in higher education by analyzing their interactions and providing personalized feedback. Its purpose is two-fold:
(1) to identify the nature and extent of the interactions between students and teachers,
(2) to evaluate the effects of these interactions on student involvement using an AI tool to improve teaching and learning. Based on a comparative case study at six Chilean and Spanish higher education institutions, a questionnaire was applied to students and teachers to record their experiences and interactions.

To address this research, we analyzed the voices of 120 students and 10 teachers on use cases of possible AI systems in online learning. Focusing on the perspectives of these participants is crucial because they provide direct insights into the practical applications and challenges of AI in educational settings. Marketing students were chosen because this discipline is highly relevant to the service sector, which benefits significantly from AI-driven insights. By studying marketing students, we can better understand how AI tools can be integrated into educational programs to enhance learning experiences and prepare students for real-world applications.

Findings show that participants adopting AI systems in online learning can improve learner–teacher interaction. However, although AI systems have been positively recognized for providing personalized support in large-scale settings and for improving the feeling of connection, there were concerns about responsibility and agency issues. These findings have implications for the design of AI systems to ensure explainability, and careful data collection and presentation. The analysis of these interactions between students and teachers reveal that students prefer conducive environments and continuous check-ins on their progress in the classroom. Additionally, this paper shows evidence into academic practices and describes several recommendations to improve professors’ and students’ interaction behaviors and experiences.

Keywords: Artificial Intelligence, experiential learning, Higher Education, Spain, Chile.