ORIGINAL RESEARCH article
Front. Psychol.
Sec. Educational Psychology
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1560088
This article is part of the Research TopicDemystifying Academic Writing in Higher Education: A Process View on Academic Textual ProductionView all 8 articles
Componential Modeling of Argumentative Essay Writing from Multiple Online Sources: A Bayesian Network Approach
Provisionally accepted
- 1San Francisco State University, San Francisco, United States
- 2University of North Florida, Jacksonville, Florida, United States
- 3University of Maryland, College Park, College Park, Maryland, United States
- 4University of Illinois at Urbana-Champaign, Champaign, Illinois, United States
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Writing argumentative essays using multiple sources is a critical skill for college students, yet it remains a significant challenge. Despite previous research acknowledging this difficulty, the specific dynamics of the argumentative essay writing process and where breakdowns occur remain unclear. In this study, we modeled the componential process underlying argumentative essay writing from multiple documents to understand the interactions among components that result in quality argumentation. College students wrote argumentative essays on a controversial topic after reading multiple documents. The data were fitted to two competing theory-based Bayesian networks, a method highly suited to the modeling of cognitive processes identified with argumentative writing. The best-fitting model showed that the argumentative essay task is both initiated and sustained by higher-order integration components. This model lends support to the description of the process of argumentation writing from multiple documents put forth by the stage-based Integrated Framework of Multiple Texts. Further, we found that the process of argumentation falters due to students' inability to frame counterarguments and their non-optimal critical analysis. This research not only enriches our understanding of the mechanics of argumentative writing from multiple sources, but the innovative Bayesian approach could lead to further refinement of the model by future researchers.
Keywords: Argumentation, Writing, Bayesian network analysis (BN), Multiple source use, college students, Essay Writing
Received: 13 Jan 2025; Accepted: 16 Apr 2025.
Copyright: © 2025 Singh, Sun, Alexander and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Anisha Singh, San Francisco State University, San Francisco, United States
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.