Speaker
Description
This study examines how the use of artificial intelligence (AI) tools shapes academic procrastination, with a particular focus on the role of self-regulation in AI-mediated learning. As AI becomes increasingly embedded in educational contexts, it can function both as a cognitive support and as a shortcut that may alter students’ engagement with academic tasks. A mixed-method design was adopted. Quantitative data were collected from 180 undergraduate English-major students at a Vietnamese university using a structured questionnaire measuring AI use, AI-regulated self-regulation, and academic procrastination. An open-ended question was included to capture students’ experiences with AI in relation to task management and deadlines. The findings indicate that AI use is associated with both self-regulation and procrastination. More importantly, self-regulation mediates this relationship, suggesting that students’ ability to monitor and evaluate their use of AI determines whether it supports or undermines their learning. Qualitative responses further reveal that increased reliance on AI near deadlines may contribute to delayed task initiation, whereas more self-regulated learners use AI more selectively and strategically. This study contributes to ongoing discussions on technology-enhanced learning by reconceptualizing self-regulation in the age of AI and highlighting the need for AI-aware learning strategies in language education.
Biography
Nguyen Nhu Y is a lecturer at the Faculty of Foreign Languages, Phu Yen University, Vietnam. Her research focuses on self-regulation in learning and the impact of artificial intelligence (AI) on student learning behaviors. She is particularly interested in how AI reshapes students’ approaches to academic tasks, especially in relation to time management, cognitive engagement, and responsibility in learning. Her work examines how students use AI in real academic contexts and how such use influences their self-regulatory processes. Adopting a practice-oriented perspective, she aims to explore how AI can be integrated effectively into language education while supporting students’ independent learning. Her current research investigates the relationship between AI use, self-regulation, and academic procrastination among English-major students.
| Affiliate type | University |
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