Designing a computer-based assessment system for evaluating writing proficiency in the Indonesian language

Abstract

Writing is a fundamental language skill that students must master in school-based learning. This study aims to develop a computer-based assessment system for evaluating Indonesian opinion articles, addressing the challenges teachers face in manual writing assessments. Utilizing the initial phases of research and development (R&D) with the ADDIE model, this study conducted a needs analysis through literature reviews, interviews, and questionnaires. Findings indicate the necessity of a computer-based writing assessment system incorporating both machine and human raters. The machine rater evaluates mechanical aspects and vocabulary (word count) using pre-processing techniques in Natural Language Processing (NLP), supported by an Indonesian vocabulary database and punctuation programming. Meanwhile, the human rater, an Indonesian language teacher, conducts assessments via an interactive interface. Testing by four teachers on 40 students revealed that 97.6% of teachers responded positively to the system’s assessment process. This research is particularly relevant in the post-COVID-19 era, highlighting the positive role of technology in advancing language education and information technology. The system can be adapted for assessing other language skills, such as reading, and for large-scale applications like the Indonesian language proficiency test.