Mapping the Research Landscape of AI-Driven Formative Assessment for Argumentation Skill Development in Higher Education: A Bibliometric Study
TL;DR
This study uses bibliometric analysis of 109 Scopus-indexed publications (1992–2025) with VOSviewer and Biblioshiny to map its evolution, key contributors, major themes, and future directions.
Abstract
The integration of AI into formative assessments to enhance students’ argumentation skills in higher education has gained growing attention over the past 30 years. However, research in this area remains fragmented. This study uses bibliometric analysis of 109 Scopus-indexed publications (1992–2025) with VOSviewer and Biblioshiny to map its evolution, key contributors, major themes, and future directions. Findings reveal a 6.5% annual growth rate, indicating sustained academic interest. Major contributions come from the USA, Germany, Switzerland, and the UK. Thematic clusters include: (1) AI and argumentation in education, (2) Instructional systems and e-learning, (3) Automated feedback and LLM-based tools like ChatGPT, and (4) NLP methods. Despite progress, significant gaps remain, such as limited attention to process-based assessments, underrepresentation of multilingual and collaborative settings, and concerns over the fairness of automated feedback. The study calls for interdisciplinary research, culturally responsive design, and longitudinal studies to fully leverage AI in advancing 21st-century argumentation skills.