EXPLORING PREDICTORS OF AI ADOPTION IN IMPROVING LEGAL TEXT COMPREHENSION: AN EMPIRICAL STUDY OF UNIVERSITY ENGLISH MAJORS

Abstract

As artificial intelligence (AI) becomes increasingly integrated into higher education, its role in supporting specialized academic reading warrants closer examination. This study investigates the predictors influencing the adoption of AI tools for legal text comprehension among legal English majors at Hanoi Law University. Using an explanatory mixed-methods design, quantitative data were collected from 168 students through a researcher-developed questionnaire, followed by semi-structured interviews with 15 volunteers to deepen interpretation. The quantitative results indicate that students face considerable challenges with legal English, particularly in navigating complex terminology and lengthy argumentative structures. Although they view AI-generated explanations as helpful, their trust in the accuracy and neutrality of AI remains limited. Qualitative findings reinforce these patterns, revealing that students value AI primarily as a supplementary aid rather than a dependable interpretive tool. Moreover, teacher encouragement, peer influence, and students’ digital readiness emerged as meaningful predictors of adoption, while concerns related to privacy, academic integrity, and over-reliance were strongly articulated. As such, the study highlights a cautious yet constructive engagement with AI in legal English learning. The findings underscore the need for guided, responsible integration of AI tools to balance technological support with the development of independent legal reasoning skills.

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