Applying Augmented reality to enhance physics laboratory experience: does learning anxiety matter?

ABSTRACT

Augmented reality (AR) recently shows great potential to facilitate students’ learning, especially their learning performance and motivation. However, few studies considered learners’ emotional factors such as learning anxiety, which may influence the learning results. This study aims to explore how different experimental conditions (AR & Non-AR) may affect the learning performance and motivation of students with different levels of learning anxiety. An AR-based magnetism experimental tool entitled “MagAR” was proposed to support junior high school students’ physics learning. The results indicated that, when compared to traditional experimental materials, AR can effectively improve students’ learning performance and motivation. Moreover, regardless of their anxiety, students in AR condition performed better on transfer test than those in Non-AR group. AR can also significantly motivate students with high anxiety. Besides, all students hold a positive attitude towards MagAR.

KEYWORDS:

• Augmented reality
• physics education
• learning anxiety
• motivation

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Hubei Educational Science Planning Project (grant number 2020GA005), Wuhan Pre Funded Science and Technology Project (grant number 2020010601012190), and National Natural Science Foundation of China (grant number 72174070).

Notes on contributors

Shufan Yu

Shufan Yu is a Ph.D. student at the School of Educational Information Technology at Central China Normal University (CCNU). His research interests include Augmented/Virtual Reality in education and human-computer interactive technology.

Qingtang Liu

Qingtang Liu is a professor at the School of Educational Information Technology at CCNU. His recent research interests include technology-enhanced learning, e-learning and teacher professional development.

Jingjing Ma

Jingjing Ma is a Ph.D. student in the School of Educational Information Technology at CCNU. Her research interests include Augmented/Virtual Reality in education.

Huixiao Le

Huixiao Le is a Ph.D. candidate in the Graduate School of Education at Peking University. His research interests include pedagogical agents and intelligent tutoring systems.

Shen Ba

Shen Ba is a Ph.D. candidate in the School of Educational Information Technology at CCNU. His research interests include pedagogical agents and learning analytics.