Authors - Rowena Ocier Sibayan, Hazel C. Tagalog, Salvacion M. Domingo Abstract - Artificial intelligence (AI)–based writing tools are increasingly integrated into higher education as part of institutional technological‑intelligence infrastructures, providing automated feedback that can improve students’ writing quality and efficiency. This study evaluates AI writing tools as intelligent decision‑support systems and examines their impact on academic performance, student learning behavior, and institutional decisions about AI integration in higher education. A convergent parallel mixed‑methods design was adopted, combining quantitative analysis of writing performance with qualitative insights into student experiences. Data were collected from 100 undergraduate students with prior exposure to AI writing tools; quantitative measures included pre‑ and post‑intervention writing scores, rubric‑based assessments, and usage frequency, while qualitative data were gathered through structured questionnaires and reflective responses. Findings reveal statistically significant, large improvements in writing confidence, perceived clarity, and assignment performance, with mean grades increasing from 68.5% to 73.2%. Students also reported greater perceived independence in writing, although qualitative data indicate variability in engagement, ranging from critical use of AI feedback to more passive reliance. Concerns about data privacy showed minimal change and remained an area of uncertainty, underscoring the importance of governance and risk management in institutional AI deployments. The study concludes that AI writing tools enhance measurable writing outcomes but do not automatically foster deeper cognitive development. Their effectiveness depends on how students interpret and engage with AI feedback, underscoring the need for pedagogically guided and ethically responsible integration of AI in higher education.
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