Abstract

Previous research suggests that heavily accented speech can hinder student learning, particularly for those from non-English speaking backgrounds. This study delves into the potential benefits of voice-modded lectures, which utilize AI-based speech synthesis to alter pronunciation accents for student learning. Conducted within the Faculty of Science and Engineering's Introductory Statistics unit, which caters to over a thousand students per session from diverse STEM and non-STEM disciplines, this research evaluates student engagement and feedback. By examining the perceived usefulness of voice-modded content, we aim to enhance accessibility and comprehension. Our findings will shed light on the potential of voice-modding technology to significantly improve educational experiences and foster inclusivity in higher education.