To enhance collaborative learning and practice network knowledge with a virtualization laboratory and online synchronous discussion
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<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>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it