# Online Blended Learning in Small Private Online Course
## 5 Online Blended Learning Based on Network Experiment Courses
### Assignment of Tasks in Peer Grading
(**b**) We did not add autograder in the peer grading in the autumn of 2019. ### Verify the Improvement of the Effect of Network Experiment Teaching

In the context of the computer network online experiment platform, by optimizing the teaching mode of the network experiment, and enhancing the depth and breadth of the experimental learning content through online blended learning, the students' experimental learning can be improved, as can the teaching effect of the computer network experiment. We compared the results of an online experiment exam after the online experiment platform was employed in actual teaching in 2015 with the results from previous years. (Figure 11). Through analyses and comparisons of the network experimental teaching data from 2010 to 2018, we see that the use of online blended learning methods offers a wider range of experimental teaching content, more depth, greater difficulty, better teaching effects, and significant increases in the percentage of excellent and good results. The \"fail\" percentage dropped significantly. Through the analysis of students' final exam grades, we see that blended learning methods can effectively improve students' learning. ## 7 Conclusions

The online blended learning method combining computer network experiments and online SPOC course learning enables students to carry out hardware-based online experimental learning anytime and anywhere, and effectively improves the teaching level and learning effect. It also addresses the difficulty in making appointments and the spatial and temporal limits for students when performing experiments, and provides students with a free and flexible experimental environment; that is, they can exercise their hands-on ability and deepen their understanding of theoretical knowledge. Moreover, the online blended learning method proposed in this paper not only enables students to conduct online experiments and learn in an actual teaching environment; it also

Figure 11: Comparison of exam grades. (**a**) Statistical comparison of undergraduates’ experimental exam grades. (**b**) Statistical comparison of postgraduates’ experimental exam grades. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Autograder**} & **Number of** & **Number of** & **Mean** & **Standard** & **RMSE** \\ \hline Autumn—2019 & yes & 198 & 750 & 4.91 & 5.72 & 7.54 \\ Autumn—2020 & no & 198 & 750 & 8.87 & 10.97 & 14.11 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Experimental results of the game process with and without autograder. enables us to analyze the learning trajectories of students on experimental courses, analyze their mastery of knowledge points, and provide them with targeted guidance. For example, fine-grained learning behavior data can also be obtained. Through continuous quantitative analyses of micro-teaching activity data, the cultivation of students' professional abilities can be tracked. This can effectively improve the quality of teaching. The blended learning method not only provides students with flexible and diverse learning, but also effectively promotes the improvement of teaching quality, which facilitates analysis and research on the relationship between various elements within the applied sciences. The blended learning method proposed in this paper can also be applied to other courses by converting the traditional teaching environment to online teaching, and analyzing the learning behaviors of students. However, some problems may also be encountered in the specific cases of implementation, such as how to evaluate the learning more effectively. To solve these problems, we require further literature and material studies. This paper was completed by a number of authors, each of whom contributed: Conceptualization, Y.H. ; methodology, W.W.; software, Y.L. ; data curation, L.Z. ; writing--original draft preparation, Y.H. ; writing--review and editing, Y.H. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Key R&D Pro- gram of China (Funding No.