# Evaluation of Effective Cognition for the QGIS Processing Modeler
## 4 Evaluation of Processing Modeler
### Evaluation by Eye-Tracking Measurements  
The eye-tracking experiment was designed in a complex way to confirm or reject the hypothesis H1 and H2. All tested diagrams are in Appendix A. The design of the test contain more tasks to find maximum information. Some models serve for evaluation repetitively for a different purpose, e.g., find symbol, compare orientation, or read the labels. After testing only reliable answers and correct record by eye-tracker were finally evaluated and presented in the article. The first evaluation concerned the discriminability of symbols. These tasks required finding input data and output data symbols in the models. The task was: \"_Click on the symbol where the input data are_\" (task A1, A2, A3 in Appendix A). The number of incorrect answers recorded was zero. The next task was \"_Click on the symbol where the output data are_\" (task A4, A5, A6). The wrong answers were two times 2 (A4, A5), and 4 for task A6. However, model A6 has a big influence of arrangement to answer. It means that the input and output symbols were nearly high in _Perceptual Discriminability_, but the errors report about space for improvements of symbols such as inner icons that are suggested in Section 4.1. for increasing transparency and using all visual variables. Besides the number of correct/wrong answers, the time of the first click was recorded. The distribution of times had not normal distribution (tested by Shapiro-Wilk test). Non-parametrical test [PERSON] tested if the medians of the \"first click time\" of all tasks (A1-A5) is equal. [PERSON] tested whether time samples originate from the same distribution. The result of the statistical test revealed the there is no significant difference between finding the symbol of input and output. It means that basic symbols are discriminable and none of them is dominant in perception. The next task aimed to verify the influence of _Dual Coding_ (but the influence of the discriminability present). The task was: \"_Click on the symbol where the 'Fixed Distance Buffer' operation is called_\" (task A13, A14, A15). Once again, it was necessary to find the white symbol and read the labels in the symbols. A total of 21 correct answers were recorded (one incorrect). The results for 22 respondents were calculated as an attention heat map (Figure 15). The heat map expresses the calculation of places where the peaks of gaze fixations are by all respondents. The figure shows that all white symbols correctly attracted the gaze of respondents. Respondents searched for white operation symbols and then read a particular operation label. The highest attentions were recorded at the two places where the _Fixed Distance Buffer_ operation was (top and bottom). Next, the lower peaks of fixations are at another white symbol with the different operation. It is evident that white colours of operation attract the gaze. Both principles of _Visual Expressiveness_ (and also _Perceptual Discriminability_), by using white colour fill, and _Dual Coding_ were verified. In fact, this stimulus did not confirm the poor distinguishing of white symbols from a white canvas. The poorest distinguishing result was expected in the theoretical part of this article. The principle of Semantic Transparency was difficult to test. The transparency of the icons was tested with the task: _\"Are all operations from the same source library?\"_ The tested model is shown in Figure 16 (Appendix A16, 17, 18). Three incorrect answers were recorded from 22 respondents. Semantic Transparency of data types was only possible to solve in the Processing Modeler with expressive text. This was verified in a model where the task was: _\"Does the input data have the same data type as the output data?\" (A10, 11, 12)._ The data symbols were labelled with the words \"table\" and \"raster\" as a part of the data name in the model. It is \"user design help\" to the respondents to distinguish the data type. The number of incorrect answers was three for two models and two incorrect answers for A11 task.