Artificial Intelligence (AI) Usage and Its Influence to the Students’ Academic Writing: A Quantitative – Correlation Investigation

Abstract

This study dealt with the artificial intelligence (AI) usage and its influence on students’ academic writing. The primary goal of the study was to determine the level of artificial intelligence (AI) usage and students’ academic writing in terms of their respective indicators, the significant difference between artificial intelligence (AI) usage and students’, and what domains of artificial intelligence (AI) substantially influenced students’ academic writing. Also, this study utilized a quantitative-correlational design with 335 participants among Junior High School and Senior High School students in Lorenzo S. Sarmiento Sr. National High School. The average weighted mean, Pearson R, and multiple regression analysis were the statistical tools used in this study. Along with this, the results showed a high level of artificial intelligence (AI) usage in terms of satisfaction, AI literacy, relevance of AI, and confidence. Likewise, results showed a high level of students’ academic writing in terms of usefulness, ease of use, and attitude towards usage. In addition, there was a high correlation, and a significant relationship between artificial intelligence (AI) usage and its influence on the students’ academic writing. Hence, this led to the rejection of the null hypothesis. The domains of artificial intelligence (AI) usage that influenced students’ academic writing are the relevance of AI, confidence, and AI literacy. While satisfaction, as a domain of artificial intelligence (AI) usage, had no significant influence on students’ academic writing. Thus, educational institutions could harness the positive influence of artificial intelligence (AI) on students’ academic writing, creating a more technologically advanced, collaborative, and effective learning environment while encouraging students to participate in AI-assisted activities contributing to better progress and improved self-regulated learning as they interacted with AI tools and their peers in an academic setting.

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