AI-Driven Analysis: A Case Study on Assessing Argumentation Proficiency and Skill Development Through Sequential Submissions

Abstract

This paper examines argumentation proficiency in essay writing, utilizing AI to investigate EFL students' development of argumentative skills across sequential submissions. Argumentation is crucial in academic writing, but assessing and grading it can be incredibly challenging due to its subjective nature. This study uses AI technology to evaluate students' argumentative essays in the College of Business and Science. AI-powered assessment is employed for two primary aims: assessing argumentation proficiency and identifying the progression of argumentative skills of the selected participants. Seventy-four students participated in the research through three assignments during the fall semester of 2024: an argumentative essay assignment, an argumentative essay test, and an argumentative-based research paper. An AI-based tool was used for argument analysis to provide detailed feedback across the selected argumentative submissions. The study results pointed out that the average grades at the end of the semester improved, and over half of the students improved their overall performance. Students' argumentative writing skills improved, as evidence indicates AI assessments enhance EFL outcomes and deepen understanding of students’ potential. It also highlights how new learning technologies can foster critical thinking and communication skills. The study recommends developing advanced AI tools to analyze and monitor skill growth across submissions, providing precise feedback for improved writing.