4.3.1 Course content and requirements Video editing is a kind of nonlinear editing, mainly
around the propaganda subject, different videos are edited into a complete video. Video clip material is very important, but on the basis of mastering basic skills and learning editing tools well, ideas and inspiration in the process of production are more important. Four teaching courses with 2 class hours (1 class hour for theory and 1 class hour for practice) were randomly selected. The content and requirements are shown in Table 2.
Table 2
Course Content and Requirements
Time | Content | Requirements |
September 2021 | Extreme sports | Familiarize yourself with editing tools and settings such as the Rate Stretch Tool, the Razor Tool, and the Clip Speed/Duration when making video productions. |
December 2021 | Page curl, dissolve and shrink class transitions | Master the method of adding and editing video transition effects; understand the role of common video transition effects. |
March 2022 | keyframe animation | Learn how to create keyframe animations; apply video effects. |
June 2022 | Video Keying and Compositing | Master the relevant knowledge of video synthesis; understand the alpha channel; master the use of color keying and keying effects; master the use of mask keying and keying effects. |
4.3.2 Method The four courses selected in this study were all taught online by the same teacher. Before each class, students were given a "Student Fatigue Scale" and required to complete it within 5 minutes. Then the theory teaching for 1 hour, and then according to the teaching content, the examination questions are arranged, requiring students to complete the independent hand in within 1 hour. To understand the learning effect of students.
4.3.3 Assessment results
4.3.3.1 Assessment results of different fatigue degrees In spring, summer, autumn and winter, the results showed that fatigue had a great influence on the learning effect. The students without fatigue had the best test scores, and the more severe the fatigue, the worse the test scores, and the difference was statistically significant (P < 0.001). Table 3.
Table 3
Assessment Results of Students With Ddifferent Degrees of Fatigue (‾x ± s)
Time | No fatigue | Mild | Moderate | Severe | Statistical processing |
September | 88.54 ± 5.95 | 86.90 ± 7.33 | 80.98 ± 8.64 | 71.00 ± 6.89 | χ2 = 2979.0 P༜0.001 |
December | 87.93 ± 6.71 | 84.99 ± 9.03 | 80.07 ± 8.60 | 74.63 ± 6.02 |
March | 88.87 ± 5.45 | 85.35 ± 7.23 | 83.38 ± 7.90 | 80.19 ± 5.80 |
June | 90.32 ± 4.28 | 86.61 ± 5.73 | 82.19 ± 5.83 | 78.32 ± 7.12 |
4.3.3.2 Assessment results of different learning foundations According to the examination results of students in the second half of 2021 and the first half of 2022, we divided each class into two groups, A and B, with group A performing better and group B performing worse. After the online teaching in 2022 and June, the scores of students in groups A and B were statistically analyzed to understand the influence of fatigue on students with different learning foundations. The results showed that fatigue had A slight effect on group A students, but there was no statistical significance (P > 0.05). Fatigue had a significant impact on group B (P < 0.001). See Table 4.
Table 4
Test Scores of Different Basic Students (‾x ± s)
Grouping | Group A(157 people) | Group B(158 people) |
normal(55) | fatigue(102) | Statistical processing | normal(56) | fatigue(102) | Statistical processing |
Score | 92.80 ± 3.56 | 91.99 ± 4.11 | t = 1.232 p༞0.05 | 83.59 ± 8.24 | 70.15 ± 6.28 | t = 4.866 p༜0.001 |
4.4 Multivariate analysis In this study, the influence of student fatigue on learning effect, and the dependent variables such as fatigue degree, gender and time are continuous variables, so multiple regression was used to analyze. The analysis results are shown in Table 5. The standardized residual distribution diagram (PP diagram) is shown in Fig. 6.
Table 5
Regression Analysis Results
Variable Name | Coefficient | Standard Error | t | p |
Constant | 90.208 | 5.951 | 15.158 | 0.000 |
Degree | -2.906 | 0.735 | -3.956 | 0.001 |
Gender | -4.380 | 1.643 | -2.666 | 0.015 |
Season | 1.266 | 1.006 | 1.259 | 0.223 |
Analysis of variance F = 8.115, P = 0.000. The adjusted fitting degree of the regression model R2 = 0.481, indicating that the fitting degree is good, and the independent variable can explain the change of the dependent variable. Through the diagnostic analysis of regression model, VIF < 5, there is no multicollinearity; The residuals are normally distributed (PP figure). Durbin - Watson = 1.812. To sum up, it shows that the analysis results are accurate and reliable with high credibility.
The regression results showed that the degree of fatigue was negatively correlated with the test scores, and the degree of fatigue of the independent variable was − 2.906, P = 0.001. The more serious the fatigue, the greater the impact on the academic performance. The gender coefficient was − 4.380, t =-2.666, P = 0.015. The performance of boys was less affected by fatigue, and the performance was higher than that of girls. Season had no significant effect on academic performance (P = 0.659). Based on the above analysis, the quantitative relationship (regression equation) between fatigue related factors and academic performance is as follows:
Academic Performance = 90.208-2.906× Fatigue Grade།4.380×Sex (Boy 1, Girl 2)
4.5 Suggestions and measures According to the results of this study, the common causes of students' fatigue and their preventive measures should include correct learning attitude, rational view of honor, reducing excessive expectations; Develop good study and living habits, and ensure 7 to 8 hours of sleep every day; Abandon smoking, drinking, indulge in cards, games, play and other bad habits; Set up correct values, love view, do have ambition, ideal, have the pursuit of modern youth; Appropriate participation in recreational and sports activities, edify sentiment, enhance physical fitness; Reasonable diet, adjust nutrition balance; Pay attention to environmental hygiene and maintain a good learning environment; Timely diagnosis and treatment of diseases to avoid pathological fatigue.
Fatigue is a common health condition for everyone, and excessive or chronic fatigue can lead to various diseases [25]. It is suggested that colleges and universities should pay attention to students' fatigue, monitor students' fatigue status through "Student Fatigue Scale" regularly or irregularly every year, and take corresponding preventive measures according to the causes of fatigue, so as to reduce the impact of students' fatigue on study and health. The incidence of fatigue in college students should be controlled below 30%, and the occurrence of severe fatigue should be avoided as far as possible.