# Development and Evaluation of Training Scenarios for the Use of Immersive Assistance Systems
## 3 Methodology
### Design of Experiment
The participant was able to see the live stream of the HL2 view on a monitor. The participant also had the opportunity to ask questions directly. This type of training also attempted to anticipate previous technological experience, age, and level of education. * Optimised Training (OT): in this scenario, various methods were combined in a favourable way. The interaction paradigm was again conveyed to the test person interactively via the 'Tips' application. In accordance with Table 1, the basic hardware features were explained via video tutorials. The subtasks of the operating system were trained via annotated video tutorials. In addition, the participant was given the opportunity to practise the content once again via guided learning by doing. The subtasks of the AR application were first trained in a face-to-face session. HL2 was then handed over to the participant, and the content was expanded via guided learning by doing. The supervisor, meanwhile, accompanied the participant on the AR stream. Operational progress (OP) is calculated from the number of subtasks the respondent was able to complete successfully up to the termination criterion; refer to Equation (1). Quitting was defined as a termination criterion (refer to the accuracy of the system [45]). \[\text{OP}=\text{count of accomplished sub-tasks/total of sub-tasks}, \tag{1}\]  
Total Operational Time (TOT) describes the full amount of time a participant needs to complete all subtasks successfully. Refer to Equation (2) and the metric for evaluations of AR systems [45]. \[\text{TOT}=\text{total time to accomplish sub-tasks}, \tag{2}\]  
Total Operational Time with Penalties (TOTP) is the total time taken by the subject to complete the last successful subtask plus the penalty times for each unsuccessful subtask; refer to Equation (3). The penalty time per subtask is defined as the 75 th percentile, which is calculated across all subjects for each subtask; see Equation (4). \[\text{TOTP}=\text{total time of accomplished sub-tasks a}+\text{sum of penalties for not} \tag{3}\]  
\[\text{completed subtasks }_{\text{(1-a)}},\]  
\[\text{Penalty }_{\text{k}}=\text{Percentile }(0.75)\text{ of operational time for sub-task }_{\text{k}}\text{ about} \tag{4}\]  
all participants,Performance: The two dependent variables, OP and TOT, and their respective extension, TOTP, are common metrics for the evaluation of immersive systems; refer to the meta-review by [PERSON] et al. [45] and [PERSON] et al. [46]. To evaluate the quality of service, as a superordinate metric as discussed by [PERSON] et al. [47], the performance can be derived based on the speed-accuracy trade-off [48] according to Equation (5). This index is derived analogously to the visibility index by [PERSON] et al. [42]. Accordingly, the effective performance is rated as high if a high OP is achieved by taking a low TOTP. \[\text{Performance}=\text{OP}/\text{TOTP}, \tag{5}\]  
UTAUT2 questionnaire (UTAUT2): The UTAUT2 questionnaire is used to determine the effects of QoT on the acceptance dimensions. Behavioural intention (BI) is used as the dependent variable and as an indicator of acceptance of the immersive system [49]. In accordance with the UTAUT2 questionnaire [43], further acceptance factors are also taken into account, including the following: the effects of the training error on performance expectancy (PE), effort expectancy (EE), hedonic motivation (HM), social influence (SI), habit (HT), and facilitating conditions (FC) are to be analysed. The UTAUT2 item 'price value' was consciously not asked. In the industrial context, monetary considerations do not play a role for the user because they rarely make financial decisions. NASA TLX questionnaire (NASA TLX [44]): The NASA TLX questionnaire is surveyed to determine the impact of QoT on the workload. The perceived workload comprises the mean value of the corresponding subscales: mental demand (MD), physical demand (PD), temporal demand (TD), performance (P), effort (E), and frustration (F).