## 4 Results
### \"Research Panel\" Results  
A timeline graph of the \"Research Panel\" results was prepared to illustrate the relative density of positive and negative reactions during different sections of the lesson (Figure 6). Four types of reactions are indicated by colored lines on their respective rows. A fifth \"Screenshot\" row contains images from the VR view in the Teams video recording; the time of capture is from the middle of each image on the time axis. Light grey vertical bars indicate points marked as \"Milestones\" by the observing researcher. Milestones are transition points in the lesson which are included on the graph to indicate a possibly heightened propensity to provide feedback since the trainer was instructed to ask for feedback during milestones. Light yellow vertical bars indicate points marked as \"Important moments\" by the observing researcher. Examples of important moments include particularly interesting discussions or important safety explanations. The timeline graph demonstrates a high rate of \"Research Panel\" usage among the learners and a dominant positive valence of the reactions. The reaction \"Technical problem\" was used only once by a single participant before actual training had begun, therefore it is not included in the figure. The \"Like\" reaction was the most used one--it was used by eight participants, with a median of 10.5 times per learner (min = 1 and max = 74). The \"Now I understand\" reaction was used by seven participants, with a median of 19 times per learner (min = 1, max = 57). The reactions of negative valence--\"Dislike\" and \"I am confused\" were used by two and three participants, respectively. The \"Dislike\" was used a minimum of two and a maximum of 18 times, while \"I am confused\" was used a minimum of one and a maximum of 14 times. These reactions can demonstrate unclear moments of the training session. Measuring technical problems during the lesson using an online tool, such as the \"Research Panel\", is most likely subject to sampling bias because any technical issues that affect the lesson, for example, network issues or operating system instability, may also  
Figure 6: The timeline of reactions collected during the remote training session. affect the panel. Nevertheless, including a \"technical problem\" reaction may still be useful for revealing some issues that do not also affect the \"Research Panel\" itself. In addition to the predetermined reactions, learners could also provide free-form text feedback during the lesson, shown in Table 1. The participants could attach a reaction to their free-form feedback by clicking the reaction button before or after submitting their text. Free-form feedback was associated with the same learner's reactions occurring up to 60 s before or 20 s after text submission (in case of multiple reactions, the latest one was chosen). All free-form feedback is categorized in Table 1, sorted by time in ascending order inside each category. As seen in the table, the free-form text feedback was considerably heterogeneous. P3 mentioned that the tempo was too low for them and that they are \"_Almost sleeping_\", whereas P5 said that there was not enough time to read the text in the VR text popups. This could be explained partly by the lesson being too fast in some parts and too slow in others, or it could simply indicate different individual needs and preferences. P4 disliked some unnecessary hand movements. P6 made comments related to both good and bad camera positioning; perhaps a preset reaction could be added to the \"Research Panel\" for indicating poor camera positioning. P1 gave positive feedback when virtual objects were highlighted; example screenshots of this can be seen at approximately 48 and 72 min on the timeline (Figure 6). Automatic object highlighting in motion is an important benefit of VR lessons, although highlighting could be performed in post-production for traditional training videos as well.