Student’s Attitudes and Motivations Toward Using ChatGPT Feedback for Personalised Learning

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.

Institutions

Publication Details

Journal
Asian Journal of Assessment in Teaching and Learning
Published
2025-12-19
DOI
https://doi.org/10.37134/ajatel.vol15.2.3.2025
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Student’s Attitudes and Motivations Toward Using ChatGPT Feedback for Personalised Learning

Asian Journal of Assessment in Teaching and Learning
Artificial Intelligence in Healthcare and Education
article

Student’s Attitudes and Motivations Toward Using ChatGPT Feedback for Personalised Learning

article en

Abstract

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.

Asian Journal of Assessment in Teaching and LearningVol. 15(2)
Curtin University Sarawak (MY), Universiti Brunei Darussalam (BN), Swinburne University of Technology Sarawak Campus (MY)
Curtin University, Malaysia, Curtin University of Technology
Openalex Percentile: Top 64%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.