GBA Berbasis GenAI sebagai Partner-Drafting Menulis Argumentasi Siswa SMA - Wira Manik; Losten Tamba; Dairi Sapta Rindu Simanjuntak; Priska Manalu; Aldo Tarigan (Jurnal Pendidikan: Media, Strategi, dan Metode, 2026)
The integration of artificial intelligence in language pedagogy provides a new opportunity to strengthen argumentative writing instruction. This study examines the effectiveness of a Genre-Based Approach (GBA) supported by Generative AI (GenAI) as a partner-drafting tool to improve the argumentative writing skills of twelfth-grade students at SMA Budi Murni 1 Medan. The study employed a quantitative approach with a quasi-experimental nonequivalent control group design. The sample was selected through cluster random sampling and consisted of class XII-1 with 34 students as the experimental group and class XII-2 with 34 students as the control group. Data were collected through argumentative writing pretests and posttests assessed using an analytical rubric covering content, organization, vocabulary, language use, and mechanics. The data were analyzed using an independent samples t-test and N-Gain. The findings showed a significant difference in writing performance between the experimental and control groups after treatment (p = 0.000 < 0.05). The experimental group achieved a posttest mean score of 84.26, while the control group achieved 74.41. The experimental group obtained an N-Gain of 0.58 or 58.41%, higher than the control group at 0.33 or 32.97%. These findings indicate that GenAI as a partner-drafting tool in the Joint Construction of Text phase effectively supports idea incubation, enriches diction, and organizes argumentative structure without removing students authorship autonomy.