Enhancing Spoken Communication Skills in Engineering Education Through AI-Driven Technologies: A Comprehensive Analysis and Implementation Framework

Abstract

Engineering graduates require strong communication abilities, yet many face difficulties developing speaking skills due to insufficient practice opportunities, lack of personalized feedback, and linguistic challenges. This research explores how artificial intelligence technologies can transform spoken communication training for engineering students through innovative educational solutions.

The study investigates the application of speech recognition systems, natural language processing tools, and conversational AI platforms in delivering immediate feedback on speaking performance, including pronunciation accuracy, fluency patterns, grammatical correctness, and message coherence. These AI-powered systems facilitate interactive communication exercises, realistic conversation scenarios, and customized learning experiences that overcome traditional instructional limitations.

The technology enables flexible, self-directed learning while reducing presentation anxiety and encouraging regular practice sessions. Analysis of existing AI educational applications reveals significant improvements in student confidence levels, speaking clarity, and overall communication effectiveness. Automated speech analysis provides instantaneous pronunciation guidance, while AI conversational partners offer secure environments for practicing professional communication scenarios.

Results demonstrate that incorporating AI technologies into engineering curricula successfully addresses the disconnect between technical competence and communication skills. The research advocates for systematic integration of AI-based communication modules within academic programs to enhance graduate readiness for professional and international communication requirements.