# A Global Overview of SVA--Spatial-Visual Ability
## 5 Results
### Analysis by the Age Categories and Assessment Tools
#### 5.1.4 Ages 16 Years to 17 Years and up to 17 Years--Higher-Secondary-School Students (A4)  
Table 6 showcases the studies conducted in the age-group of 16-17 years. In 1993, researchers [PERSON], [PERSON] and [PERSON] delved into the shortcomings of conventional measures, notably the Scholastic Aptitude Test (SAT) and the Graduate Record Examination (GRE), as tools to identify top-notch individuals in the fields of physical science and engineering. They undertook longitudinal studies on vast numbers of high school students who were monitored for 11 years after their graduation. The predictive validity of spatial-mathematical and verbal-mathematical ability composites was verified, and diverse educational and occupational groups were effectively identified [8].  
An experiment conducted by [16] used stratified random sampling to assign 33 secondary school learners to experimental and control groups; the experimental groups were trained in interaction-enabled DVEST (Desktop Virtual Environment Spatial Trainer) and animation-enhanced DVEST, while the control group received traditional tutoring. The results of this experiment [16] emphasised the relevance of spatial visualisation skills in technical training and advised using digital resources such as iDVEST in order to assist students to enhance their spatial abilities.  
An Italian study in 2006, demonstrates how established methods of assessment were modified to measure 3D spatial skills in young learners. The methods for developing the measures, as well as the basis for selecting and constructing the questions, are also included in the study. The findings implied that a latent spatial intelligence is assessed by different tests and that it is advisable to administer the currently developed test to a larger student population for further validation [30].  
Authors [PERSON] and [PERSON] utilized Facet Theory and Multidimensional Similarity Structure Analysis (SSA) to examine correlates of spatial ability performance. The findings suggested the pattern of spatial ability in academically gifted individuals is similar to that of more representative sample sizes, implying that the findings can be extended to larger sample sizes [31]. They recommended that additional studies be undertaken to  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Reference** & **Country** & **Year** & **Age** & **Sector** & **Objective** \\ \hline \multirow{3}{*}{[8]} & \multirow{3}{*}{USA} & \multirow{3}{*}{1993} & \multirow{3}{*}{Grades 9 to 12} & \multirow{3}{*}{A + G} & Group-membership prediction can improve test-validation designs that are focused on individual differences in standard performance and the significance of SVA in STEM and creative disciplines.—NA & \multirow{3}{*}{D} & Group-membership prediction can improve test-validation designs that are focused on individual differences in standard performance and the significance of SVA in STEM and creative disciplines.  
determine the generalizability of the findings on the highlighted aspects of spatial ability in academically gifted students.