DEEPSEEK FOR ACADEMIC WRITING: ODL TERTIARY STUDENTS’ ACCEPTANCE THROUGH THE TECHNOLOGY ACCEPTANCE MODEL (TAM)

Abstract

Intelligence (AI) writing tools are increasingly being adopted in higher education to support students in producing structured and high-quality academic texts. Despite these technological advances, many students in Open and Distance Learning (ODL) programs struggle with organising ideas, maintaining clarity, and adhering to academic writing conventions without sufficient guidance. Therefore, this study aims to examine ODL tertiary students’ perceptions of DeepSeek for academic writing through the lens of the Technology Acceptance Model (TAM) and to explore the challenges they encounter when using the platform. A qualitative design was employed, involving ten postgraduate TESL students from a Malaysian public university in Selangor. Data were collected through semi-structured interviews, open-ended questionnaires, and WhatsApp discussions, and were analysed thematically. Findings revealed that participants perceived DeepSeek as useful for improving writing clarity, refining language, and generating ideas, and found it accessible and intuitive, fostering positive attitudes and strong intentions to continue using it. Nonetheless, challenges such as citation inaccuracies, over-reliance, and occasional misinterpretation of outputs were reported. The study concludes that AI writing tools like DeepSeek can enhance distance education writing instruction, offering practical insights for educators, instructional designers, and developers seeking to optimise technology-supported academic learning.