# Engineering the Future: Evaluation of Virtual Reality Across Project Lifecycle Stages
## 4 Results
### Predicting Perceived Practicality of VR Using a CHAID Classification Tree Model
The tree included all ordinal variables previously tested in the SEM, encompassing demographic characteristics such as age, education level, years of engineering experience, tenure in the current organization, and organizational unit size. It also incorporated a range of attitude-based measures reflecting participants' perspectives, experiences, and openness toward VR adoption. Crucially, the CHAID model enabled the inclusion of nominal variables that could not be accommodated in the SEM due to estimation limitations. These additional variables reflected participants' professional and organizational contexts--such as sex, academic background, organizational role, technical domain, and organization type--as well as their initial exposure to VR and their belief in its potential to enhance systems engineering, integration, and testing processes. This expanded set of predictors allowed for a more comprehensive and inclusive exploration of the factors influencing perceptions of VR's practicality. The CHAID decision tree is depicted in Figure 5.  
The classification tree was cross-validated using 10-fold cross-validation and reached a maximum depth of three, resulting in 12 nodes, when 7 of them were terminal. Despite the wide range of variables considered, only four predictors were selected as significant in the final CHAID model: willingness to adopt VR, familiarity with the technology, education level, and age. Other predictors--including demographic characteristics (such as sex), professional roles, organizational context, and other attitudinal measures--were not selected by the algorithm as effective splitting variables, suggesting that their influence may be more indirect or context-dependent. Willingness to adopt VR was the most decisive predictor, forming the initial split in the tree. Participants with lower willingness (\(\leq\)4.0) comprised the majority of the sample (94.6%) and had lower perceived practicality scores (mean = \(-\)0.10), whereas those reporting high willingness (>4.0) demonstrated significantly more favorable evaluations (mean = 1.69). This result underscores the importance of openness to technological adoption in shaping perceptions of technological utility. Within the low-willingness group, familiarity with VR further differentiated responses. Participants with limited familiarity (\(\leq\)3.0) reported more negative views (mean = \(-\)0.34), while those with greater familiarity (>3.0) expressed mildly positive attitudes (mean = 0.16). A deeper split within the low-familiarity group revealed an interaction effect: participants with the lowest willingness (\(\leq\)3.0) exhibited the most negative evaluations (mean = \(-\)0.69), while those slightly more open (>3.0) reported more neutral perceptions (mean = 0.16). Among participants with high willingness, age emerged as a meaningful factor. The most favorable evaluations came from older individuals (above 50, mean = 2.19), followed by younger respondents (mean = 1.96), and then middle-aged participants (mean = 0.92), suggesting a potential U-shaped relationship between age and optimism toward VR. Education level further distinguished responses among highly familiar participants. Those with a technician or practical engineer background reported the highest levels of perceived practicality (mean = 3.03), while those with bachelor's or master's degrees gave more neutral assessments (mean = 0.05). This pattern aligns with the SEM results, which showed that higher education levels were associated with lower perceived practicality, particularly during the development stages. Figure 5: CHAID classification tree predicting perceived practicality of VR. The gain summary indicates that the nodes with the highest predicted practicality scores were Node 10 (3.03), Node 7 (2.19), and Node 5 (1.96), each representing small but distinct subgroups. In contrast, Node 8 had the lowest predicted mean (\(-0.69\)), highlighting a group characterized by both low willingness and limited familiarity.