Integration Of Languagetool Api For Automated Spelling And Grammar Assessment In English Writing

Abstract

English writing proficiency is a fundamental academic competency and a key indicator of students' language mastery in higher education. Theoretically, this complexity is grounded in the Complexity, Accuracy, and Fluency (CAF) framework, with the accuracy aspect specifically emphasizing adherence to grammatical and spelling rules. However, the manual assessment processes typically employed by instructors are often hindered by heavy technical workloads, high operational costs, and potential inter-rater inconsistency, ultimately limiting the frequency and depth of formative feedback provided to students. While commercial Automated Writing Evaluation (AWE) tools offer a partial solution, many operate as opaque "black box" systems reliant on proprietary third-party APIs, raising concerns regarding data reliability, institutional privacy, and a lack of pedagogical transparency for learners. This research seeks to address these issues by developing a transparent, self-hosted writing assessment prototype using the Design Science Research (DSR) framework. The system is built on the Laravel 12 framework—chosen for its modularity and security—and integrates the open-source LanguageTool API to provide rule-based feedback on spelling and writing style. The prototype's performance was rigorously evaluated against a "gold standard" established by independent expert raters using a dataset of authentic student essays. Validation results demonstrate high reliability, with the system achieving significant accuracy in spelling and grammar detection. Furthermore, the system exhibits high technical efficiency with rapid response times. This research aims to produce a digital solution capable of further development that bridges the gap between traditional assessment methods and modern educational technology; the solution is also expected to effectively alleviate the technical workload of instructors while empowering students to become more independent through real-time instructional feedback based on language usage standards.