# Natural Virtual Reality User Interface to Define Assembly Sequences for Digital Human Models
## 4 Discussion  
The TCT results show that using the VATS, with its direct manipulation in a virtual environment, is significantly faster than using the existing IPS IMMA WIMP interface. This coincides with the work of [33], which states that when you implement a direct manipulation interface, users can transfer their already learnt skills quickly to the new interface. Thus, a well-implemented direct manipulation interface achieves, in this use case, better results. Additionally, the VATS provides only the information which is necessary to conduct the specific task. The user interface of IPS IMMA, as a user interface for experts, offers additional features, that are not necessary, to do the examined use case. In the VATS, on the interaction side, we only implemented grabbing, moving, and releasing objects. The \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Mean Values** & \(\mathbf{p}\) **(T-Test Mean Values/Mean of** **Questionnaire Scale)** \\ \hline Improves Interface & 4.34 & \textless{}0.01 \\ \hline Higher Efficiency & 4.69 & \textless{}0.01 \\ \hline Less time consuming & 5.41 & \textless{}0.01 \\ \hline Higher intuitiveness & 5.17 & \textless{}0.01 \\ \hline Increases the use & 4.66 & \textless{}0.01 \\ \hline Sequence definition is easier & 5.1 & \textless{}0.01 \\ \hline System accuracy & 3.41 & 0.77 \\ \hline System supports user & 5.17 & \textless{}0.01 \\ \hline Tracking is precise enough & 3 & 0.06 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Results of the final questionnaire about the VATS and the results of the \(t\)-test between the mean value of the results and the mean value of the scale. The \(p\) values with a grey background indicate the significant results of the \(t\)-test. Figure 11: Results of the NASA-TLX for each dimension. WIMP interface of IPS IMMA, e.g., allows for unconstrained certain degrees of freedom when grasping an object or using one hand as a support hand. Furthermore, the placement of grip positions on a 2D desktop is a challenge for every user, including experts, as they must switch between different perspectives to place the grip type on the right position and also adjust the orientation. However, by being able to grasp the object with the own hand in an immersive virtual environment, this problem is eliminated. Thus, our hypothesis that users can conduct the task faster with the VATS can be accepted. On the other hand, the error rate with the VATS is higher than with the WIMP interface. We expect this for two reasons. For the WIMP interface, the participants had a precise manual of which actions they had to perform to conduct the task. They also had the opportunity to check this manual while doing the task. On the other hand, we presented the users a precise description of how to use the VATS before they put on the head-mounted display. Thus, they could not look up the instructions again while using the VATS. Additionally, none of the participants used the VATS before and knew how the interaction works, while users are highly familiar with WIMP interfaces and using mouse and keyboard in general. But, the amount of errors declined from 12 in the first round until four in the eighth round. As we create the same information with the VATS as with the WIMP, it is still possible to make smaller adjustments, like changing the grip type with the WIMP interface. This hybrid approach enables users to eliminate the errors. The VATS also enables users to learn to define an assembly sequence faster. The results show that the participants only needed three trials to learn to define the assembly sequence with the VATS. There were no significant improvements in time after the third trial. Using the WIMP interface, the participants had significant improvements in the TCT until the seventh trial. The questionnaire for the suitability of learning also shows these results. In each dimension, the VATS has a significantly better score.