## 5 Discussion  
The initial finding (Tables 4 and 5) showed that regardless of the teaching method (traditional or traditional with VR support), both groups (EG and CG) learned after participating in classes on production sequencing. However, upon evaluating the group results (Table 6), it was determined that the EG achieved a statistically significant learning outcome (5.9747), which was 29.2% higher than the CG (4.6229). The application of VR in teaching-learning processes generated a real opportunity for more significant student learning, corroborating similar previous studies [(58; 59; 34)]. A follow-up assessment was conducted on the groups' knowledge retention three weeks after the initial knowledge tests [(66)], revealing a decrease in the average scores for both groups. The control group (CG) achieved a score of 4.3988, while the experimental group (EG) achieved a score of 5.2841. Statistical analysis yielded a \(p\)-value of 0.0028, which indicates significant differences between the groups. The data provide strong evidence that the EG has greater knowledge of production sequencing compared to the CG after three weeks, consistent with previous studies [(67; 68)]. Furthermore, regarding knowledge retention, Table 8 illustrates a 4.8% decrease for the CG (from 4.6229 to 4.3988) and an 11.6% decrease for the EG (from 5.9747 to 5.2841). The EG lost more knowledge than the CG after three weeks. Even if the causes are outside the scope of the present study, it prompts further investigation into potential hypotheses, such as specific environmental factors or lapses in focus during the retention test. Finally, what can be seen from the results of the experiment is that students learn regardless of the teaching method applied. However, integrating VR into teaching and learning fosters a cognitive  
Figure 4: Keywords reported in qualitative questions by participants in the experimental group. environment [1, 2] conducive to deeper learning and enhanced knowledge retention over a three-week period. Further research and experimentation are required to explore the varying levels of knowledge retention among different groups. In evaluating the satisfaction, engagement, and attractiveness indexes for EG, all average results exceeded 6.0 on a Likert scale of 1-7. The highest average (6.8) was about the class being more enjoyable with VR, and the lowest average (6.2) was about feeling a greater desire to participate through understanding the content developed in class. Table 9 presents the data from the questionnaires that assessed levels of satisfaction, engagement, and attractiveness. More than 90% of the responses had indices between 6 and 7. These results present positive and relevant impacts on student satisfaction, engagement, and attractiveness rates, as indicated by similar studies [17, 34, 36, 69, 70, 71, 72, 73]. A recent assessment utilized qualitative analysis of participants' essay responses (EG). The findings revealed that VR-based classes lead to a deeper understanding of the subject matter, offering a more realistic, dynamic, and engaging learning experience compared to traditional teaching methods. These results are consistent with similar studies [34, 35, 36, 70]. The findings indicate that establishing a cognitive teaching and learning environment using VR leads to greater learning and knowledge retention among students compared to traditional teaching methods. Participants find it engaging and satisfying, making it a more attractive option. A critical aspect of these results is the careful construction of the VR environment with expert support and a well-planned experiment. The smooth execution of these steps, along with expert knowledge, is crucial for generating knowledge and creating opportunities to develop solutions to societal needs [80]. Educational settings that prioritize teaching and learning create more effective learning outcomes for students by fostering a cognitive environment, a deeper understanding of the subject matter, and a stronger connection to real-world applications.