Assessing Student Satisfaction Using Lectures Generated by Artificial Intelligence (AI)

The integration of Artificial Intelligence (AI) in education has gained significant momentum, particularly in online learning environments. This study evaluates the effectiveness of AI-generated voice-over lectures as an alternative to traditional human-narrated presentations in preparing students for the Federal Aviation Administration (FAA) Part 107 certification exam for small Unmanned Aircraft Systems (sUASs). Utilizing a mixed-methods approach, the research examines student performance, engagement, and satisfaction through quantitative analysis of exam scores and survey data, supplemented by qualitative insights from student interviews.The study employs a comparative design, assessing two groups: one receiving AI-generated instructional content and the other engaging with human-narrated lectures. Results indicate no significant difference in exam performance between the two groups, demonstrating that AI-generated lectures are as effective as traditional methods in supporting student learning outcomes. Survey responses reveal that students appreciate the accessibility and consistency of AI-driven instruction but highlight a preference for human interaction in certain aspects of learning. AI tools such as chatbots and digital notes offer supplementary benefits, particularly in providing quick clarifications, though they are perceived as less effective for in-depth explanations.The findings underscore the viability of AI-generated lectures in education, particularly for technical certification training. Future research should focus on optimizing AI instructional design to enhance personalization, engagement, and interaction, ensuring that AI-driven education continues to align with pedagogical best practices.