Impacts of integrating the repertory grid into an augmented reality-based learning design on students’ learning achievements, cognitive load and degree of satisfaction

ABSTRACT

Augmented reality (AR) offers potential advantages for intensifying environmental context awareness and augmenting students’ experiences in real-world environments by dynamically overlapping digital materials with a real-world environment. However, some challenges to AR learning environments have been described, such as participants’ cognitive overload and the ways to provide assistance in constructing the presented learning materials. In this study, a mindtool-based AR learning system was developed, based on the repertory grid method and the contiguity principle of multimedia learning, for assisting students in constructing their knowledge in a natural science course. Furthermore, an experiment was carried out on an elementary school natural science course to compare the influences of this method with those of the conventional AR learning system on students’ learning effectiveness. The experimental results show that the designated approach effectively promoted the students’ learning achievements, and no significant difference existed between the mindtool-based AR learning system and the conventional AR learning system in terms of students’ cognition load and satisfaction degree; moreover, both the experimental group and the control group perceived low cognition load during the learning activity and rated their own AR learning systems as being highly satisfactory.

KEYWORDS:

• Augmented reality
• repertory grid
• mindtool
• contiguity principle
• cognition load

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Dr Po-Han Wu is currently an Assistant Professor at the Department of Mathematics and Information Education, National Taipei University of Education. His research interests include e-learning, information technology-applied instructions, ubiquitous learning, digital game-learning, knowledge engineering and expert systems.

Dr Gwo-Jen Hwang is currently a Chair Professor at the Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan. His research interests include mobile and ubiquitous learning, digital game-based learning, web-based learning and artificial intelligence in education.

Ms Mei-Ling Yang is a graduate student at the Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan. Her research interests include mobile learning and digital game-based learning.

Mr Chih-Hung Chen is a Ph.D. candidate at the Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, Taiwan. His research interests include mobile and ubiquitous learning, digital game-based learning and science education.

Additional information

Funding

This study is supported in part by the Ministry of Science and Technology of the Republic of China under contract number [MOST-105-2511-S-011-008-MY3].