The Implementation and Empirical Analysis of Adaptive Virtual Mentor: Mobile Technology Empowers Introverts’ Business Communication Skills
Year: 2025
Type: article
Abstract: Effective communication is a key element in professional success, yet individuals with introverted tendencies often face difficulties in developing these skills, which limits their opportunities for growth in the work environment. This research aims to develop Adaptive Virtual Mentor (AVM), a mobile application designed to help introverted individuals improve their business communication skills (BSC). This application utilizes speech recognition technology supported by deep neural networks (DNNs) and recurrent neural networks (RNNs). DNNs are tasked with improving accuracy in recognizing user speech patterns, while RNNs are instrumental in maintaining the context of the conversation and providing timely and relevant feedback in real-time. A quasi-experiment was conducted involving introverted individuals through structured training using this application. The results of the study showed that participants experienced an improvement in communication skills after the training. Potential further developments include refining the adaptive algorithm and adding new features that allow this application to be applied in a variety of other professional contexts. Future research could explore the application of this technology on a wider scale, as well as evaluate its impact on improving productivity and performance in diverse workplaces.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $280
Award: G2519718815
OpenAlex ID: W4409816793