Jantakan Kanjanawetang
Suranaree University of Technology, Thailand
Abstract:
Title: Effects of the augmented reality learning media on cognitive domain of learning about normal mechanisms of childbirth in Thai nursing students
Jantakan Kanjanawetang1, Ph.D, Pornsing Ninphai2, and Wuthinan Wamakan2
1Suranaree University of Technology, Thailand
2The Center for Educational Innovation and Technology, Thailand
Introduction: The vaginal childbirth mechanism is an unseen process, and as such has proven to be a difficult content for nursing students to understand by using traditional learning media. To enhance a cognitive domain of learning about process of normal vaginal childbirth, the augmented reality (AR) technology was used to create the three-dimensional learning media called “LOA&SUT”. It is a mobile application used to present eight steps of fetal changes during childbirth such as; descent, engagement, flexion, internal rotation, extension, restitution, external rotation, and expulsion.
Methods: A quasi-experimental research, one group with pretest and posttest, was conducted to examine the effects of the “LOA&SUT” on the cognitive domain of learning about normal mechanisms of childbirth in nursing students. The 10-item of multiple-choice test was designed to measure three levels of the cognitive domain; remembering, understanding, and analyzing, classified by Bloom Taxonomy. After finishing a lecture about normal mechanisms of childbirth with traditional media, video, models of pelvis and fetus, 78 Thai nursing students were given a pretest. Subsequently, the students were introduced and permitted to use the “LOA&SUT” as a self-directed learning media on their smartphones for 15 minutes. Then, a posttest with the same test was performed. The scores of each student between pretest and posttest were analyze using a paired t-test.
Results: The findings revealed that post-test scores on knowledge of the normal mechanism of childbirth (total score =10), after using the LOA&SUT (mean = 7.91, SD = 1.33) as a learning media, were higher than pretest scores (mean = 7.08, SD = 1.53) statistically (t = 5.690, p < .001). Considering each of cognitive domain of learning, it was found that posttest scores of remembering (mean = 1.78, SD = 0.45), understanding (mean = 2.49, SD = 1.02), and analyzing (mean = 2.81, SD = 0.87) domain were higher than the pretest scores of those (mean = 1.87, SD = 0.34; mean =2.86, SD=0.94; mean=3.18, SD=0.77) consequently. In case of satisfaction (total score is 5.00), Thai nursing students rated overall satisfaction with LOA & SUT at a high level (mean = 4.91), followed by modernity (mean = 4.99), ability to stimulate them interested in learning (mean = 4.84), and helping them to understand the content more easily (mean = 4.81).
Conclusion: The Thai nursing students indicate that the AR learning media, called the SUT&LOA, is contemporary, interesting, and fit into their learning style. They state that, the AR learning media is helpful for imagining, understanding, and remembering the process of the normal mechanism of childbirth, and better than the traditional media. Although, the AR learning media is appropriate for Thai nursing, midwife, and medical students, translating to other languages is recommended.
Audiences Take Away:
- The audience will receive an example of using AR, SUT & LOA learning materials about normal vaginal delivery.
- Research on the use of the SUT&LOA may influence the inspiration of the audiences to create a learning media that uses modern technology to solve learning problems in the classroom.
Biography:
Jantakan Kanjanawetang had completed PhD in nursing from Chulalongkorn University, Thailand. She is the deputy director of the Center for Innovation and Educational Technology, and the former associate dean of Nursing Institute, Suranaree University of Technology, Thailand. She has long experience on teaching maternal nursing and midwifery for nursing students for more than 20 years. In Thailand, she has registered a number of innovative patents on teaching and learning media innovations including mobile health application for pregnant women. This year, she receives the Outstanding Nursing Research and Innovation Award from the Nurses Association of Thailand.