AI-Assisted Writing and Student Proficiency: Argumentation and Problem-Solving Skills of Undergraduate Students in Bengkulu, Indonesia
DOI:
https://doi.org/10.53899/spjrd.v31i1.1305Keywords:
AI-assisted writing tools, writing proficiency, argumentative skills, problem-solving skillsAbstract
Previous research on AI-assisted writing tools has predominantly used quantitative methodologies, emphasizing students’ performance and learning outcomes. It largely overlooks students’ qualitative experiences, particularly with respect to argumentation and problem-solving skills. To address this gap, the present study investigates the influence of AI-facilitated writing tools on writing proficiency, with a specific focus on problem-solving and argumentation skills among 10 Indonesian undergraduates using Grammarly, ChatGPT, and QuillBot. Employing a qualitative exploratory design, data were collected through semi-structured interviews and analyzed using thematic analysis to identify patterns in cognitive and metacognitive engagement. Argumentation was assessed through students’ accounts of refining claims, evaluating the logical relevance of supporting ideas, and identifying fallacies. Problem-solving skills were defined as the ability to address rhetorical challenges and revise structural inconsistencies. Findings revealed that AI tools significantly supported students in developing clear arguments, recognizing logical fallacies, and resolving writing-related challenges. Participants indicated that AI-facilitated tools contributed to the development of higher-order writing skills and promoted critical thinking and metacognitive awareness, alongside improvements in argumentation and problem-solving features. These findings indicate that, when mediated by effective pedagogy, AI-assisted writing tools can function as cognitive scaffolding in academic writing, supporting independent thought and sound reasoning. The research advocates for the integration of AI technologies into writing instruction, emphasizing the necessity of pedagogical balance to enhance deep learning by fostering independent metacognitive sensitivity. The study highlights the significance of employing AI technologies as supportive resources within balanced instructional strategies, rather than as replacements for traditional teaching methods.
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