Cloud-Based Learning Analytics Platform for English Learning: Developing the Grammarlyze Mobile Application Using Firebase Realtime Database

Abstract

Purpose – This study was conducted to address the growing need for a flexible and interactive English language learning platform by leveraging cloud computing technology. Specifically, it aims to develop an Android-based English learning application, Grammarlyze, and examine how Firebase can be effectively utilized to manage and store learning materials in real time, thereby improving accessibility and user experience compared to conventional learning media.
Methods – The study employed the Waterfall development method, consisting of requirement analysis, system design, implementation, testing, and maintenance. The application was developed using Android Studio with Java, while Firebase Realtime Database and Firebase Storage served as the cloud backend for managing text and video learning materials. System testing was conducted using black-box testing to evaluate feature functionality.
Findings – The results show that all core features of the Grammarlyze application functioned as expected. Black-box testing confirmed that 100% of the tested features, including material access, navigation, and data synchronization, were valid. Firebase enabled real-time data management, efficient storage, and seamless retrieval of learning content, contributing to a stable and responsive learning application.
Research limitations – This study is limited to basic English learning materials and does not yet include automated evaluation features such as quizzes or adaptive feedback. The findings also limited to functional testing and do not measure learning outcomes quantitatively.
Originality – This research provides practical evidence of Firebase implementation as a cloud platform for English learning applications, offering a scalable and efficient model that can extended in future studies to include advanced learning analytics and assessment features.