Effects of integrating maternity VR-based situated learning into professional training on students’ learning performances

ABSTRACT

Educators have recognized the importance of providing a realistic learning environment which helps learners to not only comprehend learning content, but also to link the content to practical problems. Such an environment can hence foster problem-solving skills in nursing training. However, when learners interact in a virtual environment with rich learning resources, they might encounter difficulties if there is a lack of proper guidance, clinical sense, or a well thought-out instructional design process. Hence, this work developed a maternity VR-based situated learning system (MVR-SLS) based on the experiential learning theory to support professional courses in obstetrics. A quasi-experiment was conducted to verify the impacts of this method on learners' learning achievement, OSCE (Objective Structured Clinical Examination) competency, problem solving skills, learning engagement, and teaching effectiveness. The experimental results indicate that the new method improved learners' learning achievement, OSCE competency, problem-solving ability, and recognition of learning engagement. Moreover, the learners who learned with the new method showed more active learning behaviors compared to the learners in the control group. Findings of the present study offer concrete suggestions for implementing effective virtual reality (VR)-based learning strategies for medical and nursing textbooks.

KEYWORDS:

• Mobile learning
• situated learning
• nurse education
• higher education

Disclosure statement

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

Statements on open data, ethics and conflict of interest

The participants were protected by hiding their personal information during the research process. They knew that participation was voluntary and they could withdraw from the study at any time. There is no potential conflict of interest in this study. The data can be obtained by sending a request e-mail to the corresponding author.

Additional information

Funding

This work was supported by Ministry of Science and Technology of the Republic of China: [grant no MOST 111-2410-H-038-029-MY2 , MOST 111-2628-H-155 -001 -MY2].

Notes on contributors

Ching-Yi Chang

Dr. Ching-Yi Chang is a PhD, RN, and Assistant Professor of the School of Nursing, College of Nursing, Taipei Medical University. She is also a supervisor in the Department of Nursing, Shuang Ho Hospital, Taipei Medical University. Her research interests include mobile learning, digital game-based learning, flipped classroom and medical education, nursing education, and AI in education.

Patcharin Panjaburee

Dr. Patcharin Panjaburee is an Associate Professor of the Institute for Innovative Learning, Mahidol University, Thailand. Her research interest focuses on technology-enhanced learning such as digital game-based learning, adaptive web-based learning, expert systems, computer testing, and diagnostic systems.

Shao-Chen Chang

Dr. Shao-Chen Chang is an assistant professor in the Department of the International Bachelor Program in Informatics and the Department of Information Communication, Yuan Ze University. His research interests include mobile learning, digital game-based learning, and AI education.