Development of a Multilingual Language Learning Web Application
Nguyen, Phat (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025051311211
https://urn.fi/URN:NBN:fi:amk-2025051311211
Tiivistelmä
This thesis details the development, implementation, and evaluation of a multilingual language learning web application designed to address the limitations of existing tools, particularly the lack of contextual grammatical information needed for languages like Finnish. The primary objective was to create a user-friendly, AI-powered platform that enhances vocabulary acquisition and retention through context-aware learning.
The application was built using the MERN stack (MongoDB, Express.js, React.js, Node.js) and leverages the OpenAI API for natural language processing tasks such as translation, grammar explanation, and automated flashcard generation. Key features include AI-generated flashcards providing detailed context, a spaced repetition system (SRS) to optimize memory recall based on user performance, integrated gamification elements (XP, levels, streaks, badges) to enhance user motivation and engagement, and personalization features like AI-assisted flashcard refinement and adaptive testing. Development followed an iterative methodology inspired by Agile principles, incorporating continuous testing and refinement.
Evaluation through a user survey (N=32) indicated high overall satisfaction (8.0/10) and usability (8.2/10). The AI-powered flashcards and spaced repetition system were perceived as effective tools for vocabulary learning and retention (average ratings 7.6-7.9/10). Gamification features showed moderate success in engaging users (7.1-7.2/10), while personalization features, though functional, were identified as areas requiring further development.
This project successfully demonstrates the integration of AI, spaced repetition, and gamification to create a comprehensive language learning tool that emphasizes contextual understanding, addressing a notable gap in the current EdTech landscape. While the evaluation shows promising results, the lack of formal statistical significance testing is noted as a limitation.
The application was built using the MERN stack (MongoDB, Express.js, React.js, Node.js) and leverages the OpenAI API for natural language processing tasks such as translation, grammar explanation, and automated flashcard generation. Key features include AI-generated flashcards providing detailed context, a spaced repetition system (SRS) to optimize memory recall based on user performance, integrated gamification elements (XP, levels, streaks, badges) to enhance user motivation and engagement, and personalization features like AI-assisted flashcard refinement and adaptive testing. Development followed an iterative methodology inspired by Agile principles, incorporating continuous testing and refinement.
Evaluation through a user survey (N=32) indicated high overall satisfaction (8.0/10) and usability (8.2/10). The AI-powered flashcards and spaced repetition system were perceived as effective tools for vocabulary learning and retention (average ratings 7.6-7.9/10). Gamification features showed moderate success in engaging users (7.1-7.2/10), while personalization features, though functional, were identified as areas requiring further development.
This project successfully demonstrates the integration of AI, spaced repetition, and gamification to create a comprehensive language learning tool that emphasizes contextual understanding, addressing a notable gap in the current EdTech landscape. While the evaluation shows promising results, the lack of formal statistical significance testing is noted as a limitation.