AI Dependency in Literary Studies:
A Survey of Undergraduate English Language Students' Usage Patterns and Self-Perceptions
Abstract
Technological advancement of Artificial Intelligence (AI) in education is shifting traditional teaching and learning approaches to suit individual’s needs in diverse fields of study including literature. Literature as a subject is representative of human cognitive and emotional capacity to interpret literary works. However, the integration of AI in understanding literary texts to produce literary analysis has raised the concerns on ‘human touch’ or human interpretation beside academic integrity and ethical consideration. This study investigated the utilisation patterns, perceptions, and academic dependency of Artificial Intelligence (AI) tools during literary analysis. The main objective is to examine how tertiary students engage with AI tools -specifically whether they use AI as a cognitive substitute or as a collaborative scaffold - when interpreting literary texts. Using a quantitative survey design, data were analysed using descriptive statistics (frequencies and percentages). The sample comprised 88 undergraduate students majoring in English Language Studies (rather than English Literature) at a Malaysian public university. Descriptive findings revealed universal adoption among respondents, with 100% having used AI tools for literature tasks (50.0% occasionally, 34.1% frequently). Generative AI (49.7% of selections) and Grammar/Style Checkers (39.1%) were the most utilised tools. Students predominantly delegated lower-order structural tasks (e.g., explaining concepts, 20.2%; summarising elements, 18.2%), while retaining primary authority over higher-order interpretation. Most students viewed AI's ideal role as a "Tutor" (40.9%) or "Co-Pilot" (33.0%). These findings suggest that English Language Studies undergraduates engage in self-regulated cognitive offloading rather than uncritical dependency, providing empirical insights into strategic AI integration in literary studies.
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