## 3 Materials and Methods
### Remote User Study with Experts
#### 3.3.1 Data Collection and Analysis Methods  
Mixed research methods were used for the case study, collecting both quantitative and qualitative data. The data, with a focus on a qualitative approach, were collected via pre- and post-surveys. The pre-survey consisted of a consent form collection and a background data collection form, including age, gender, job role, experience, and self-evaluation of maintenance skills. The post-survey consisted of 14 statements (on a 5-point Likert scale, where 1 = Strongly Disagree and 5 = Strongly Agree), open-ended and other questions to evaluate: (1) online training experience in general and occurred technical problems, (2) the content of VR-based lessons, (3) trainer's activities and interactions with learners, and (4) usefulness of VR-based training. The survey quantitative data, due to the relatively small sample size, were used as a supportive data set to observe the main trends--therefore, they were analyzed with a descriptive statistics, showing minimum, maximum, median, and standard deviation values of the responses. Additionally, since ordinal Likert scale was used for data collection, non-parametric one-sample Wilcoxon Signed Rank Test was performed over all the statements individually in parallel. However, it was formality rather than a necessity; we expected no significance due to the small number of participants. Null hypothesis for each statement was based on known median: H0 = the median of responses is equal to hypothesized median. To counteract the multiple comparisons problem, we have applied Bonferroni correction, resulting in \(p\)-value threshold of 0.05/14 = 0.0035. In addition, quantitative data were collected in a form of instant reactions via the \"Research Panel\" tool, shown in Figure 4. The panel was specially designed for the study to gather subjective time-relevant reactions and feedback, which would help to evaluate learners' experiences in certain moments of the learning process. The concept of the \"Re  
Figure 3: Asymmetric set-up. search Panel\" was based on Facebook instant reactions [42], which would be a familiar way of leaving instant feedback throughout the remote training experience. The panel was used by the learners and by the observing researcher; the entries of both panels could be synchronized to gain a better insight into the remote session flow. For learners, the panel consisted of five reaction buttons: one to report a technical problem, a set of negative-positive valence reactions to evaluate learning effects (\"I am confused\" and \"Now I understand\"), and a set of negative-positive valence reactions to express overall satisfaction (\"Dislike\" and \"Like\"); a text field was available to leave clarifying or general comments. Learners were instructed to actively leave their reactions or comments about the training session whenever they wanted. In addition, the trainer promoted the use of reactions in between different parts of the training module. For the researcher, the panel consisted of four reactions and a text field for comments to track and record the overall flow of the session (\"Milestone\", \"Problem\", \"Important moment\" and \"User's reaction\"). The Teams session was video recorded, and the \"Research Panel\" data were synchronized to the recording using timestamps to allow further combined analysis. We created a novel synchronization mechanism for Teams video recordings by taking advantage of the automatic image thumbnail creation feature in Teams. By checking for the user agent of the Teams image thumbnailing backend, the \"Research Panel\" page masquerades as an image whenever it is accessed by Teams for thumbnail creation purposes. The timestamp of this HTTP request is logged, and a specific color image is returned, which can be detected on the video recording when Teams shows the link thumbnail. This creates a shared synchronization point on the video and the \"Research Panel\" server.