Student vs. ChatGPT in Rogerian Argument: A Diction 7.2 and Qualitative Content Analysis

While research on AI-generated writing is expanding, there are no studies that have systematically compared AI-generated and student-written Rogerian arguments. This study employed a mixed-methods approach to investigate the rhetorical abilities of university students and ChatGPT 4.0 in crafting Rogerian arguments. Using Diction 7.2 software, the research analyzed rhetorical elements such as optimism, commonality, and key subcategories. Additionally, a qualitative content analysis assessed how effectively each text engaged with opposing perspectives. Diction 7.2 analysis provided standardized scores based on a normative database of over 50,000 texts, allowing for a comparative evaluation of rhetorical tone and language patterns. Findings indicated that while ChatGPT demonstrated greater consistency in leveling and commonality, students outperformed AI in personalizing their rhetoric, demonstrating empathy, and reducing ideological polarization. ChatGPT’s use of inclusive and cooperative language was consistent but formulaic, whereas students displayed greater rhetorical adaptability and audience awareness. These findings highlight the pedagogical importance of Rogerian argument instruction in fostering student writers’ ability to engage meaningfully with opposing views. The study also underscores AI’s limitations in achieving the rhetorical depth, emotional intelligence, and contextual awareness necessary for modeling effective argumentation.