p>After completing the data collection, responses were extracted as an MS Excel™ sheet and then entered into SPSS™ version 23.0 for data analysis. Descriptive statistics were conducted using frequencies, percentages, and calculations of scales’ means. Assumptions to run inferential statistics were also conducted and met. Then, a t-test was used to compare the mean scores of the two main dependent variables, satisfaction and self-confidence, between the two groups. ANOVA was used to compare the mean scores among three groups or more. Finally, Pearson’s product moment correlation was used to test the relationships between satisfaction, self-confidence, and computer skills (Bowers, 2019).
Sample Characteristics
One hundred thirty-eight bachelor’s degree students at the faculty of nursing at one private university in Jordan out of the 350 students invited to participate in the survey. The response rate was calculated to be 39.4%. The results show that students' mean age was 22 years (SD = 3.2), and more female students participated in the survey than males (n = 81, 58.7%). Students belonged to different academic levels, and second-year students were the largest participants in this survey (n = 51, 37%). Since two tracks are available for nursing students in Jordan to enroll in nursing programs, students in this survey mainly enrolled by the direct admission track after secondary school (78.3%, n = 108). Regarding computer skills, nursing students rated themselves to be at a “good” level (M = 5, SD = 1.3) in computer skills using a 1 to 7 self-rating scale (Table 1).
Characteristic
|
N (%)
|
Table 1
Demographical characteristics
Age M (SD)
|
22 (3.2)
|
Range
|
19–33
|
Gender
|
|
Male
|
57 (41.3)
|
Female
|
81 (58.7)
|
Academic level
|
|
1st Year
|
18 (13.0)
|
2nd Year
|
51 (37.0)
|
3rd Year
|
45 (32.6)
|
4th Year
|
24 (17.4)
|
Enrollment Type
|
|
Direct admission
|
108 (78.3)
|
LPN to RN
|
30 (21.7)
|
Using simulation in clinical teaching
|
|
Yes
|
129 (93.5)
|
No
|
9 (6.5)
|
Using simulation in theory teaching
|
|
Yes
|
90 (65.2)
|
No
|
48 (34.8)
|
Computer skills M (SD)
|
5 (1.3)
|
Range
|
1–7
|
M = Mean, SD = Standard Deviation, N = Count. |
[Insert Table 1 here]
Based on the distributions of the reported scores, the results showed that most of the students (93.5%, n = 129) believed that simulation training at the clinical training laboratories was preferred over online remote training using videos and online simulation modules. Despite the percentage drops in learning the needed theoretical knowledge using simulation training (65%, n = 90), it is still the preferred teaching method compared to the online remote module (35%, n = 48) (Table 1).
Levels Of Satisfaction And Self-confidence
Table 2shows that the students' total satisfaction with simulation learning was just above the midpoint of the scale (M = 3.1, SD = 1.3). The students reported the highest rating for “enjoying” how the instructors taught them using the simulation in both methods and reported the lowest rating for the variety of learning materials and activities used through simulation in general for both methods.
Table 2: Satisfaction and self-confidence in simulation learning
[Insert Table 2 here]
Regarding the students’ total self-confidence in simulation learning, Table 2 demonstrates that it was also above the midpoint of the scale (M = 3.0, SD = 1.2). The highest rating was for the statement that students rely on the instructors to tell them what they need to learn of any simulation activity during class time, while the lowest student rating was for their confidence in developing the needed knowledge and skills to perform the necessary tasks in real clinical settings.
Students’ Characteristics And Simulation Learning
The results showed no statistically significant difference between male and female students regarding satisfaction in simulation (t = 0.27, df = 111.9, p = 0.74) or self-confidence in simulation (t = 0.48 df = 109.5, p = 0.64). Regarding the type of admission, the results demonstrated that there is no significant difference between students who are new admissions to the program and LPN to RN students in their levels of satisfaction with simulation learning (t=-1.5, df = 136, p = 0.13) or their levels of self-confidence in simulation learning (t=-1.59, df = 136, p = 0.12). Similarly, the academic level showed no statistically significant difference among the different year levels in their satisfaction with simulation learning (F = 2.1, df = 3, p = 0.1). However, there was a statistically significant difference among the students at the different year levels in their levels of self-confidence in simulation learning (F = 9.5, df = 3, p < 0.001). Post hoc analysis shows that the higher the year level, the higher the level of self-confidence is reported, where 4th -year students have the highest self-confidence mean (3.4 (SD = 0.97)) (Table 3).
Table 3: Demographics and simulation learning
[Insert Table 3 here]
Despite the significant correlation between computer skills and satisfaction using simulation learning (r = 0.28, p < 0.001) and with self-confidence in simulation learning (r = 0.21, p < 0.05), it was reported as a weak positive correlation in Table 4. A strong positive correlation was reported between satisfaction and self-confidence in using simulation in learning (r = 0.71, P < 0.001). In other words, as students' self-confidence in using simulation in learning increases, their satisfaction with using it will increase as well, and vice versa.
|
Satisfaction (r)
|
Self-confidence (r)
|
Table 4
Correlation between satisfaction, Self-confidence, and computer skills
Computer skills (r)
|
0.28 (p = 0.001)
|
0.21 (0.02)
|
Satisfaction (r)
|
1
|
0.71 (p < 0.001)
|
Self-confidence (r)
|
0.71 (p < 0.001)
|
1
|
[Insert Table 4 here]