Two-group, matched pretest, post-test, and follow-up test designs were created for a quasi-experimental study.
The sample size calculations were performed using G*Power 3.1. A power (1-β) of 0.84 fests, NOVA was selected: repeated measures were used, and an err prob value was 0.05, the effect size was 0.25, the number of groups was 2, and the number of measurements was 3. Based on the per-experimental data, we established a correlation among the rep measures of 0.50. Consequently, the total sample size consisted of 96 people, 48 of whom were in the experimental group and the remaining 48 were in the control group.
A convenience sample approach was adopted to total of 96 junior year nursing students were recruited who came from Huzhou University, Zhejiang Province in China. The inclusion criteria were as follows: ① Students in the second semester of junior year on nursing profession; ② voluntary selection course; ③ Informed consent, willing to cooperate. The exclusion criteria were as follows: ① Students were not interested; ② Research objects who are participating in other teaching reform.Recruited students were randomly assigned with odd and even numbers by computer, and the odd number was the intervention group and the even number was the control group. Their were 48 people, respectively.
Control group students were given the traditional skill training course. Traditional skill training course forms of teaching organization include teacher demonstration, student practice, and one-way technical examination. Based on principle of ethical equality, relevant training was conducted after experiment according to the needs of students in control group.
Curriculum content breaks through curriculum boundaries and integrates teaching content. According to the independence and team nature of technology application, integration nursing experiment technology 30 items (Fig. 1).
The curriculum designs a three-module, online and offline mixed teaching mode. The curriculum is 64 class hours in total, 16 class hours online and 48 class hours offline. One class hours is 45 minutes. Module one, first week, online and offline 2 class hours each, curriculum introduction, learning methods training; Module two, 12 weeks, every two weeks is a unit module (online 2 class hours, offline 6 class hours), a total of 6 Unit modules. Implementation of online problem-oriented skills self-learning, classroom skills guidance and training, multi-station nursing skill examination. Module three, 3 weeks, online 2 class hours, offline 10 class hours, implement online team skills self-learning, classroom team multi-station nursing skill examination guidance and exercises, team multi-station nursing skill examination and nursing practice module (Fig. 2).
Online teaching adopts "four ones" task-oriented approach: one hour of video learning, one-quarter of an hour of online practice, one minute of discussion and interaction, and one thousand words of operation process writing. Solve online students' problems of learning, what to think, and what to do. Offline teaching adopts multiple teaching methods, it contains group cooperative learning, group scenario simulation, group discussion. After class realizes on the online teaching platform to publish learning tasks, clarify that what teachers teach, what to guide, what to do, and what students discuss, practice, and examination, completion of individual or cooperative skill exercises, nursing service practice and problem feedback online (Fig. 3).
Online teaching is organized and managed by a teacher, who posts online videos, tasks, assignments and interactions. Offline teaching organization in class adopts the form of group cooperative learning. Firstly, before the class starts, the whole class will be stratified randomly into 4 groups according to the random number table method, each with 12 people. Secondly, after the end of each lesson, each group leader extracted the name of each group from an ‘ABCD’ label ,teacher A guided group A, teacher B guide group B, teacher C guide group C and teacher D guide group D.The matching of teachers and student groups is determined by lottery for each lesson. All 4 teachers conducted collective lesson preparation and training before class.
Course assessment adopts the form of combining online and offline. The curriculum design includes thirty learning tasks, seven multi-station nursing skill examinations and three nursing social practices. Online course assessment according to published tasks online, after teachers' review, calculates the total score with platform big data. Offline course assessment using the skill learning and multi-station nursing skill examination individual and team. Each multi-station nursing skill examination includes 3 stations, individual multi-station nursing skill examination 6 minutes a station, team multi-station nursing skill examination 10 minutes a station.
A general demographic information, including age, gender, the situation of the only child and family location.
Metacognitive awareness inventory
Metacognitive awareness inventory (MAI) was developed by Schraw (1994). The scale consisted of 52 items and 2 dimensions: regulation of cognition and knowledge of cognition. Regulation of cognition includes 5 sub-categories: planning, information management, monitoring, debugging, and evaluation.Knowledge of cognition includes 3 sub-categories: declarative knowledge, procedural knowledge, and conditional knowledge. Each item was scored on a 5-point Likert scale that ranged from 1 to 5. Total score ranged from 52 to 260.The higher the score, the stronger the metacognitive awareness.To revise the MAI for the population of nursing students in China, we conducted a factor analysis to examine the indicator relations in the measurement model. Based on model modification suggestions from factor analysis, we used the total knowledge of cognition scores in the proposed model in the study. In our study, the total scale and sub-scales of Cronbach’s alphas were 0.93, and 0.81 – 0.95.
Data collection and management
All students completed the survey with informed consent. Data were collected over three stages in one semester via self-report.The metacognitive awareness inventory (MAI) was used to evaluate at start of the course (T0) , end of the course (T1) , 1 month after the end of the course (T2). All investigators participated in one-day training before the survey, who was independent of research team. The same investigators completed collection, inspection and analysis of the scales with a recovery rate of 100% (Fig. 4 ).
SPSS version 22.0 was used for data analysis. Descriptive analysis was used to describe the collected demographic data and MAI scores at T0, T1 and T2. The T test and χ2 test were applied to compare the demographic information data and MAI variables of the two groups. ANOVA was conducted to determine the effect of the time factors, group factors, and the interaction effects of 2 factors on the effectiveness of the MAI. A p-value of less than 0.05 was considered statistically significant. A simple effect test was used to examine the difference between 3 time points within each group and the difference among groups within each time point. Cohen’s d was used to calculated the effect sizes at post-intervention, mainly using the mean and combined standard deviation of conditional measures (less than 0.33 as considered small, 0.33–0.55 as moderate, and effect size of 0.56 – 1.2 was large) .