ABSTRACT
Augmented reality (AR) can represent a contextualised scientific inquiry environment in which students may explore the real world and develop science process skills via interacting with rich information from virtual systems. However, it remains a challenge for most students to complete scientific inquiry tasks without proper support. Research evidence has suggested the potential of reflective scaffolding when applying scientific inquiry. Accordingly, we designed a contextualised reflective mechanism-based AR learning model to assist students in completing scientific inquiry tasks. Guided by the proposed model, we designed four stages of scientific inquiry learning: conceptual understanding, reflective cognition, in-depth inquiry, and knowledge building. A quasi-experiment and lag sequential analysis were conducted by recruiting 81 sixth-grade students to examine the effects of the proposed model on their scientific inquiry learning performances, higher order thinking, and behavioural patterns. The experimental results reveal that the proposed approach improved students’ inquiry learning performances and higher order thinking tendency (problem-solving tendency and metacognitive awareness). Moreover, the evidence from this study also suggests that the students who learned with the proposed approach exhibited more observation, comparison, exploration, and reflection behavioural patterns in the field trip than those who learned without the contextualised reflective mechanism. Implications are discussed.
Acknowledgements
The authors express their gratitude to the anonymous reviewers and editors for their helpful comments about this paper.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Funding
Notes on contributors
Xiao-Fan Lin
Dr. Xiao-Fan Lin is an associate professor in South China Normal University, Guangzhou, China. His interests fall into mobile science learning and augmented reality learning.
Gwo-Jen Hwang
Dr. Gwo-Jen Hwang is a chair professor at the Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology. His research interests include mobile learning, digital game-based learning, flipped classrooms and AI in education.
Jing Wang
Miss. Jing Wang is a postgraduate student in South China Normal University, Guangzhou, China. Her research interests focus on AR-based learning.
Yue Zhou
Miss. Yue Zhou is a postgraduate student in South China Normal University, Guangzhou, China. Her research interests focus on mobile-assisted AI education.
Wenyi Li
Miss. Wenyi Li is an instruction designer in Guangdong Provincial Engineering and Technologies Research Centre for Smart Learning. Her research interests focus on mobile learning.
Jiachun Liu
Miss. Jiachun Liu is a graduate student in South China Normal University, Guangzhou, China. Her research interests focus on mobile-assisted science learning.
Zhong-Mei Liang
Ms. Zhong-Mei Liang is an instruction designer in Zhixin South Road Primary School. Her research interests focus on mobile-assisted science learning.