Min Liu1, Jiaojiao Zuo1, Yanling Tao2, Liping Zhao3, Shasha Wu4, Li Feng5, Limei Liao6. 1. University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China. 2. Organ Transplantation Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China. 3. Department of Pediatric Surgery, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China. 4. Department of Infectious Disease, Mianyang Central Hospital, Mianyang 621000, China. 5. Department of Emergency, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China. 6. University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China. Electronic address: limeiliao@sina.cn.
Abstract
BACKGROUND: Sustained attention is a key variable affecting nursing students' academic performance during online learning process. However, factors contributing to sustained attention remain to be determined. AIMS: To analyze the path relationships among the influencing factors for nursing students' sustained attention in online learning using a structural equation model. DESIGN: A cross-sectional survey was administered. METHODS: Nursing students from 35 nursing schools in China were invited to participate in this survey study. Once participating in nursing programs and receiving online learning, they were eligible for the study. The data were collected online via the Questionnaire Star platform from March 29 to April 19, 2020. A structural equation modelling (SEM) approach was utilized to analyze the relationships between sustained attention and influencing factors (situational interest, anxiety, cognitive load, technology efficacy and professional identity). Furthermore, multi-group SEM analysis was conducted to examine whether the model equally fitted nursing students in different levels of programs. RESULTS: A total of 1089 nursing students completed the questionnaires. The majority (77.3%) were female and the mean age (SD) was 21.9 (4.4) years. A half (50.3%) were enrolled in the undergraduate programs. Results suggested that situational interest (β = 0.19, 95% CI: 0.14, 0.24) and anxiety (β = -0.70, 95% CI: -0.76, -0.64) directly affected sustained attention. Both technology efficacy (β = 0.22, 95% CI: 0.15, 0.28) and professional identity (β = 0.20, 95% CI: 0.14, 0.26) had conferred indirect effects on sustained attention through academic emotions (i.e., situational interest and anxiety). The cognitive load directly affected sustained attention (β = -0.15, 95% CI: -0.20, -0.09) and indirectly affected sustained attention through anxiety (β = -0.32, 95% CI: -0.37, -0.26). There was no significant difference in the model fit among nursing students in various programs, including diplomatic, associate and bachelor's degree and above programs (∆χ2 = 27.228, p = 0.611). CONCLUSIONS: Technology efficacy, professional identity, situational interest, anxiety and cognitive load are identified as the main elements affecting nursing students' sustained attention. This model is equally suitable for nursing students in different levels of nursing programs. During the process of online learning, students' attributes, emotions and cognition should be considered to help students achieve learning goals in nursing education.
BACKGROUND: Sustained attention is a key variable affecting nursing students' academic performance during online learning process. However, factors contributing to sustained attention remain to be determined. AIMS: To analyze the path relationships among the influencing factors for nursing students' sustained attention in online learning using a structural equation model. DESIGN: A cross-sectional survey was administered. METHODS: Nursing students from 35 nursing schools in China were invited to participate in this survey study. Once participating in nursing programs and receiving online learning, they were eligible for the study. The data were collected online via the Questionnaire Star platform from March 29 to April 19, 2020. A structural equation modelling (SEM) approach was utilized to analyze the relationships between sustained attention and influencing factors (situational interest, anxiety, cognitive load, technology efficacy and professional identity). Furthermore, multi-group SEM analysis was conducted to examine whether the model equally fitted nursing students in different levels of programs. RESULTS: A total of 1089 nursing students completed the questionnaires. The majority (77.3%) were female and the mean age (SD) was 21.9 (4.4) years. A half (50.3%) were enrolled in the undergraduate programs. Results suggested that situational interest (β = 0.19, 95% CI: 0.14, 0.24) and anxiety (β = -0.70, 95% CI: -0.76, -0.64) directly affected sustained attention. Both technology efficacy (β = 0.22, 95% CI: 0.15, 0.28) and professional identity (β = 0.20, 95% CI: 0.14, 0.26) had conferred indirect effects on sustained attention through academic emotions (i.e., situational interest and anxiety). The cognitive load directly affected sustained attention (β = -0.15, 95% CI: -0.20, -0.09) and indirectly affected sustained attention through anxiety (β = -0.32, 95% CI: -0.37, -0.26). There was no significant difference in the model fit among nursing students in various programs, including diplomatic, associate and bachelor's degree and above programs (∆χ2 = 27.228, p = 0.611). CONCLUSIONS: Technology efficacy, professional identity, situational interest, anxiety and cognitive load are identified as the main elements affecting nursing students' sustained attention. This model is equally suitable for nursing students in different levels of nursing programs. During the process of online learning, students' attributes, emotions and cognition should be considered to help students achieve learning goals in nursing education.