Student’s Attitudes and Motivations Toward Using ChatGPT Feedback for Personalised Learning
DOI:
https://doi.org/10.37134/ajatel.vol15.2.3.2025Keywords:
Artificial Intelligence, Attitude, ChatGPT, Feedback, MotivationAbstract
This study investigates students’ attitudes and motivations in using ChatGPT-generated feedback to support their learning at the tertiary level. The study discerned the factors that influenced students' feedback usage and compared the way they learned from ChatGPT (Artificial Intelligence mediation) and Educators (skilled individuals) across three key stages of assessment – ideation, execution, and completion. The art of personalised learning is described using Vygotsky’s social constructivism, which articulates and explores the dynamic between the three different learning zones and the roles of ChatGPT and educators in personalised learning. Employing a mixed-method research design, the study collected quantitative data through online survey of 102 undergraduate students from across five disciplines (Arts and Communication, Commerce and Business, Information Technology, Engineering and Sciences, and Health and Applied Sciences) - at an Australian offshore campus in Sarawak, Malaysia. Qualitative insights were gathered through semi-structured interviews to explore recurring themes and patterns in participants’ perceptions and experiences. Findings revealed generally positive attitudes toward ChatGPT-generated feedback, and students’ motivation was influenced by personal learning goals, institutional policies on AI use, and assessment practices. The study provides insights to educators in redesigning effective measures to integrate hybrid human-AI feedback solutions into the course curriculum and assessment based on students’ perspectives and characteristics, such as self-regulation, attitude, and motivation.
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