## 5 Discussion  
The primary motivation of this applied research was to explore how and to what extent affective factors, such as perceived immersion with the HMD-VR engine room simulator, shape maritime engineering students' perceived learning benefits, future behavioural intentions, and overall experience. The findings provide a valuable basis for further discussion, underscoring their practical implications for educators, software developers, and university decision-makers. The data-driven segmentation analysis displayed two distinct groups that emerged based on their levels of perceived immersion: _Contromists_ (22.6%) and _Immersionists_ (77.4%). These findings are compelling evidence that maritime engineering students' subjective perceptions of immersion are not homogeneous despite being exposed to an identical VR environment. To a certain extent, the findings of the present research reflect those \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Segments**} \\ \cline{2-9}  & \multicolumn{2}{c}{_Contromists_} & \multicolumn{2}{c}{_Immersionists_} & \multicolumn{1}{c}{**df**} & \multicolumn{1}{c}{**t**} & \multicolumn{1}{c}{\(\mathbf{\eta^{2}}\)} & \multicolumn{1}{c}{_p-Value_} \\ \cline{2-9}  & **M** & **SD** & **M** & **SD** & & & & \\ \hline Interaction naturalness with the & & & & & & & & \\ virtual environment & 3.00 & 0.47 & 3.94 & 0.43 & 82 & 8.21 & 0.45 & **<0.001** \\ Real-world experience consistency & 2.95 & 0.23 & 3.97 & 0.53 & 82 & 8.16 & 0.44 & **<0.001** \\ Degree of virtual & & & & & & & & \\ experience involvement & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Characterisation of the PIMM-based segments. \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Segments**} \\ \cline{2-9}  & \multicolumn{2}{c}{_Contromists_} & \multicolumn{2}{c}{_Immersionists_} & \multicolumn{1}{c}{**df**} & \multicolumn{1}{c}{\(\mathbf{\eta^{2}}\)} & \multicolumn{1}{c}{_p-Value_} \\ \cline{2-9}  & **M** & **SD** & **M** & **SD** & & & & \\ \hline
**Perceived Learning Benefits (PLB)** & & & & & & & & \\ Comprehension of the previously & 3.63 & 0.60 & 4.23 & 0.52 & 82 & 4.25 & 0.18 & **<0.001** \\ \multicolumn{9}{l}{Stimulation of responsiveness and active learning} & 3.74 & 0.65 & 4.14 & 0.58 & 82 & 2.58 & 0.07 & **0.012** \\ \multicolumn{9}{l}{Control over the learning process} & 3.53 & 0.70 & 3.94 & 0.73 & 82 & 2.20 & 0.06 & **0.031** \\ \multicolumn{9}{l}{Improving effectiveness in learning} & 3.63 & 0.76 & 4.03 & 0.68 & 82 & 2.19 & 0.06 & **0.032** \\ \hline
**Future Behavioural Intention (FBI)** & & & & & & & & \\ Willingness for future use & 3.47 & 0.70 & 4.17 & 0.98 & 82 & 3.83 & 0.15 & **<0.001** \\ \multicolumn{9}{l}{Willingness to use VR in studying} & 3.58 & 0.96 & 4.00 & 0.75 & 82 & 2.02 & 0.05 & **0.047** \\ \multicolumn{9}{l}{Willingness to recommend VR as a learning tool} & 4.00 & 0.88 & 4.43 & 0.61 & 82 & 2.43 & 0.07 & **0.017** \\ \hline
**Satisfaction (SAT)** & & & & & & & & \\ Satisfaction & 4.26 & 0.56 & 4.68 & 0.47 & 82 & 3.22 & 0.11 & **0.002** \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Segment differences in perceived learning benefits, future behavioural intention, and satisfaction. of [32], where a similar pattern was identified when segmenting maritime engineering students based on the perceived ease of use of the HMD-VR engine room simulator. Taken together, the findings of both studies underpin the relevance of segmentation approaches as a reliable tool for a deeper understanding of students' affective experiences with VR technologies in an educational context. The findings of the segmentation analysis have several significant implications for maritime educators. For instance, tailoring instructional strategies to bridge the gap between _Immersionists_ and _Contornists_ could ensure that all the students benefit equally from integrating VR technologies in higher maritime education.