Abstract
Student engagement with feedback has garnered increasing attention in higher education because of its positive association with student learning outcomes. However, there is little research on students’ contextual needs in different learning environments and the role students play in interpreting information and integrating various types of feedback (i.e., teacher, peer, and AI) in learning. This study conceptualises feedback as a learning process and investigates how different learning environments affect students' perceptions and motivations to use feedback. It also explores the relationship between AI-assisted feedback and learning outcomes in Engineering and non-engineering disciplines. Data was collected through an online survey and semi-structured interviews with purposive sampling among 100 respondents. The Feedback Ecological model (Yang, 2021) is used to explore the complex relationship between students and AI tools and unpack the contextual influences on student engagement with feedback at different stages in learning. Results showed that AI-assisted feedback is effective in bringing more feedback-driven learning opportunities but is unlikely to enhance their learning outcomes due to the lack of personalised interaction and relevant contextualisation of content.
Author Information
Ik Ying Ngu, Swinburne University of Technology Sarawak Campus, Malaysia
Marcelo Schellini, Universiti Brunei Darussalam, Brunei
John Sie Yon Lau, Curtin University Malaysia, Malaysia
Paper Information
Conference: SEACE2025
Stream: Higher education
This paper is part of the SEACE2025 Conference Proceedings (View)
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To cite this article:
Ngu I., Schellini M., & Lau J. (2025) Contextual Influences on Student Engagement With AI-Assisted Feedback ISSN: 2435-5240 The Southeast Asian Conference on Education 2025: Official Conference Proceedings (pp. 313-323) https://doi.org/10.22492/issn.2435-5240.2025.28
To link to this article: https://doi.org/10.22492/issn.2435-5240.2025.28
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