Generative Ai in the Classroom: Balancing Innovation, Fear, and Necessity

Generative AI is rapidly reshaping educational environments, offering transformative possibilities for teaching, learning, and student engagement. As UNESCO DirectorGeneral Audrey Azoulay aptly remarked, “Education will be profoundly transformed by AI.” This transformation impacts not only how knowledge is accessed but also how learning experiences are personalized, how curricula are developed, and how educators are trained. Despite the growing integration of AI tools into education, particularly generative AI, several critical questions remain: How effectively is generative AI being used to support and enhance learning? Are students merely passive recipients of AI-generated content, or are they active participants in more meaningful, personalized learning experiences? What specific generative AI tools are currently being implemented in classrooms, and how do both educators and students perceive their impact and integration? This paper presents the findings of a comprehensive survey conducted at Esprit School of Engineering (ESE) and Esprit School of Business (ESB). The goal is to capture the perspectives of students and teachers on the application and perceived impact of generative AI tools in educational settings. Using a Likert scale, the survey evaluates attitudes toward usability, effectiveness, and the potential of these tools to enhance both teaching and learning outcomes. Additionally, the study explores whether generative AI helps create a more engaging and interactive learning environment. The primary objective of this research is to explore how generative AI is perceived and utilized in classrooms, as well as the barriers and facilitators that affect its adoption. We begin by reviewing the current landscape of generative AI in education, focusing on its most prevalent applications. We then detail the survey methodology and analyze the results, offering insights into both opportunities and challenges posed by these AI tools. Finally, we conclude by discussing the broader implications of our findings and providing recommendations for future AI integration in education.