LinguaAI: An AI-Powered Mobile App to Personalize and Improve Second-Language Learning

Ricardo Moran Chang

Co-Presenters: Carlos Enrique Mosquera Hurtado

College: Hennings College of Science Mathematics and Technology

Major: BS.SCI/TEC/CS&ENG

Faculty Research Mentor: Ma, Yan  

Abstract:

LinguaAI is a proposed AI-powered mobile application designed to improve second-language learning by personalizing instruction, explanations, and practice to each learner’s needs. Many language-learning apps follow a fixed lesson path that does not adapt well to individual weaknesses, offers limited natural conversation, and provides feedback that is too general. LinguaAI addresses these gaps by using learner performance data (e.g., accuracy, time-on-task, repeated errors) to adjust review frequency, exercise difficulty, and grammar focus. The app will also provide step-by-step AI tutoring for grammar and vocabulary, interactive conversation practice with feedback on natural phrasing, and writing correction with explanations; optional pronunciation support may be included if resources allow.This research will develop a functional prototype (e.g., using React Native or Flutter) and evaluate it through a small pilot study with approximately 15–30 Kean University participants learning English, Spanish, or Chinese over 2–4 weeks. Effectiveness will be measured using pre- and post-assessments (vocabulary/grammar quiz, short writing prompt, and an optional speaking task), in-app learning analytics (time spent, accuracy, progress trends, and common error types), and brief surveys/interviews focused on clarity, confidence, motivation, and usability. The expected outcome is that real-time AI personalization and feedback will improve learning gains and learner confidence compared to traditional fixed-path apps, while also increasing motivation through a more “tutor-like” experience.