Conference paper 2023

Learning Effectiveness of Nursing Students in OSCE Video Segmentation Combined with Digital Scoring

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Conference · Vol. 14099 LNCS · pp. 409-418
Abstract

With the development of technology and the prevalence of the Internet, video learning has become a common learning tool in various settings, such as classrooms and homes. However, the continuous appearance of information in videos can lead to a transient effect that affects the effectiveness of learning. The segmentation effect involves dividing continuous videos into meaningful segments to reduce learners’ cognitive load. This study aims to investigate the effectiveness of digital segmentation combined with digital scoring in enhancing learning effectiveness s for nursing students in a long-term care course, as well as to examine gender differences. The study combined digital image segmentation with digital scoring and nursing objective structured clinical examination (OSCE) to explore whether nursing students’ learning effectiveness s were improved, and to further understand gender differences. The study involved 30 senior nursing students (15 males and 15 females) from a technology university in Taiwan. The results showed that nursing students’ learning effectiveness s were enhanced by integrating digital video segmentation feedback into nursing objective structured clinical examinations, and there were no significant gender differences. Both male and female nursing students were able to strengthen their nursing learning effectiveness s and improve their clinical skill knowledge performance. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Author Keywords

Segmentation learning effectiveness Clinical simulation E-OSEC

Index Keywords

E-learning Students Student learning Multimedia systems Learning effectiveness Nursing segmentation Gender-differences clinical examination Computer graphics Image enhancement Image segmentation Clinical simulation E-OSEC Internet video Nursing students Video segmentation
Author Affiliations
Graduate School of Technological and Vocational Education, National Yunlin University of Science and Technology, Douliou, Yunlin, Taiwan
Funding & Acknowledgements
Ministry of Science and Technology, Taiwan, MOST
Grant: 111–2628-H-224-001-MY3, MOST 110–2511-H-224-003-MY3
Acknowledgments. This research is partially supported by the Ministry of Science and Technology, Taiwan,R.O.C., under grant nos. MOST 110–2511-H-224-003-MY3 and MOST 111–2628-H-224-001-MY3.
Ministry of Science and Technology, Taiwan, MOST
Acknowledgments. This research is partially supported by the Ministry of Science and Technology, Taiwan,R.O.C., under grant nos. MOST 110–2511-H-224-003-MY3 and MOST 111–2628-H-224-001-MY3.
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