<p>Recently, various computer networking courses have included additional laboratory classes in order to enhance students’ learning achievement. However, these classes need to establish a suitable laboratory where each student can connect network devices to configure and test functions within different network topologies. In this case, the Linux operating system can be used to operate network devices and the virtualization technique can include multiple OSs for supporting a significant number of students. In previous research, the virtualization application was successfully applied in a laboratory, but focused only on individual assignments. The present study extends previous research by designing the Networking Virtualization-Based Laboratory (NVBLab), which requires collaborative learning among the experimental students. The students were divided into an experimental group and a control group for the experiment. The experimental group performed their laboratory assignments using NVBLab, whereas the control group completed them on virtual machines (VMs) that were installed on their personal computers. Moreover, students using NVBLab were provided with an online synchronous discussion (OSD) feature that enabled them to communicate with others. The laboratory assignments were divided into two parts: Basic Labs and Advanced Labs. The results show that the experimental group significantly outperformed the control group in two Advanced Labs and the post-test after Advanced Labs. Furthermore, the experimental group’s activities were better than those of the control group based on the total average of the command count per laboratory. Finally, the findings of the interviews and questionnaires with the experimental group reveal that NVBLab was helpful during and after laboratory class.</p>
According to aptitude theory, the measures of aptitude include not only cognitive factors but also affective factors (i.e., emotions) and conative factors (i.e., motivation) that can influence students' learning achievement (LA). Therefore, this study employed structural equation modelling from experimental data of 96 college students to investigate the effects of affective factors and conative factors on LA using online social network (OSN) attention as a moderating factor. The results confirmed that there are significant differences between student engagement and LA for overall group and student engagement, affective scores, and LA for the high OSN attention group. There are no significant differences for the low OSN attention group. Moreover, learning achievement can better facilitate the effects of the affective and conative levels for students with high rather than low OSN attention. In conclusion, the moderation of OSN attention shows that there are relationships that differ significantly across the high and low OSN attention groups.
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