## 3 Method
### UGVA Method and the Image Structure
We consider the following types of planar symmetry as suitable for creating an image in the UGVA notation (see Figure 4; axes are shown in different colors):  
* Bilateral vertical axial symmetry (type \(\alpha\)) allows for contrasting higher and lower groups of axes, emphasizing dynamics of the parameters; e.g., comparing a student's data from the previous program (lower stratum shows the data from undergraduate learning) and the current program (middle stratum shows the data from graduate learning);
* Bilateral horizontal axial symmetry (type \(\beta\)) allows for contrasting left and right groups of axes, emphasizing the ratio of different groups of parameters with similar roles in the model of the analyzed system, e.g., comparing data from courses in humanities and engineering courses;
* Combined axial symmetry (type \(\lambda\)) includes independently interpreted vertical and horizontal symmetry of the image; it is used to give an in-depth view of the situation, for example, combining the features from the examples to the symmetry types \(\alpha\) and \(\beta\);
* Radial symmetry (type \(\delta\)) allows interpreting composition of axes around the image center (all axes influence the image equally), e.g., each axis of type \(E\) can visualize parameters of a certain course for a student. In addition to the symmetry types and types of axes, the dynamics of parameters of the visualized systems can be shown as coloring of the graphic primitives, demonstrating the difference between the current and previous values of the parameter. It is useful to select a unified color scheme for all assessed systems and parameters (e.g., in the form of a heat map). We can code the image structure as follows: symmetry type (coded by a Greek letter), the number of chief axes, type of the axes (coded by a Latin letter), then the signs of presence of the general evaluation zone (\(i\)) taking into account activity (\(t\)). Additional artifacts and operative data are not coded. Thus, the image shown in Figure 2a can be denoted as \(\lambda 5 Bit\): on the left (basic) image, there are strata for current parameters (middle stratum, five axes) and the relevant values from the previous state of the modeled system (low stratum); the evaluation zone (upper stratum) is the image's face. Images shown in Figure 2b-d are coded as \(\delta 6 Bit\), \(\delta 5 Bit\), and \(\delta Eit\), respectively. The mapped systems can be multiparameter entities of different origins (e.g., teams, projects, goods, processes, individuals, etc.). The efficiency of the resulting visualization will depend on the quality of prepared data from the base parametric model for decision making and careful choice of the image structure. The layer of individual parameters for the elements of the target group is usually shown as artifacts and color markings (heat map). Later in this article, we will use the following color code: neutral values (or uncertainty) are shown in white; the minimum value--red, the maximum value--green; intermediary  
Figure 4: Graphic templates of different types of planar symmetry used in the UGVA images: (a) bilateral vertical axial symmetry (type \(\alpha\)), (b) bilateral horizontal axial symmetry (type \(\beta\)), (c) combined axial symmetry (type \(\lambda\)), (d) radial symmetry (type \(\delta\)). states are shown using colors from gradients from green to white, and white to red; gray is used for the image zones that are not tied to any parameter of the analyzed system.