Role of Artificial Intelligence-based Machine Learning in Improving the Quality of Students’ Academic Writing

Abstract

This research aims to explore how the use of artificial intelligence (AI) as machine learning for students can improve the quality of academic writing in higher education. This research focuses on the rise of AI as a learning companion in compiling or editing to complete assignments and improve the quality of student academic writing. This study uses a mix method approach with an embedded design type. Quantitative data was collected through questionnaires distributed to 120 students, while qualitative data was obtained through interviews, observations, and analysis of documents regarding students’ experiences using AI. Quantitative data analysis was carried out by the One-Way ANOVA test, while qualitative data was analyzed using the Robert K. Yin approach. The results of the study show that the use of AI in academic writing contributes significantly to increasing student productivity. The use of AI as machine learning can also improve grammar, clarify the structure of writing, and improve the accuracy of student citations and academic references. However, the study also found that AI still has limitations in understanding complex argumentative contexts. The results of this study are expected to provide a deeper understanding of the impact of AI in higher education and provide recommendations for academic institutions in integrating AI as an effective learning tool for students.

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