User Experience Design: A quantitative approach to three user experiences

Case Study

In the previous article, three user experience quantification methods were introduced. Through this article, we will work with cases to study the use of behavioral-centric quantification methods. The case needs to use the experience-centric quantization method to obtain the behavior-centric quantization expression and compare it with the experience-centric quantization results. The details are as follows:

First, the cognitive experiment is used to obtain the time and the steps in the behavioral interaction process. We selected a small sample sampling method, with 24 people involved in the experiment, age distribution between 22~27岁. The task is to complete the photo shoot and send the photos as MMS in the form of two mobile phones with similar appearance, similar keyboard layout and same grade. In the process of photographing, the operator is completed under a unified platform to minimize the impact of environmental factors and other external factors on the process. and recording the operator's operation steps and operation time by recording the way. Secondly, after each task completes the operator to answer the satisfaction, the emotion response, the esthetic response questionnaire in time, thus records the whole process in time the subjective experience feeling. Finally, in the process of data processing, the time and the steps are obtained through the analysis of the video, and the subjective experience degree is the result of the comprehensive calculation of the satisfaction, the emotional response and the aesthetic reaction. As shown in table 1:

Table 1 Experience Degree calculation

The P and T data obtained in the course of behavior are shown in table 2:

Table 2 Experimental data based on behavior-centered quantification method

Finally, it is necessary to construct a functional relationship between experience degree and step, time STI =f (p,t) =e. Through the analysis of the overall data of the experiment, it is found that the less the operation time of each step, the better the feeling of bringing to the user, which will help to improve the user's experience degree and the negative influence on the user's experience degree. Therefore, when we build the model, we consider that P and t affect the degree of experience in the form of p/t. And everyone's experience standard is different, in the experimental data, the operation time, the step and the experience degree of the part is obvious jumps, therefore we need to determine a standard value to balance all the data. There is also an important element in the behavior layer, that is, the frequency of information reception, that is, the frequency of operation, and the difference in the frequency of operation for everyone to bring different experience evaluation criteria. Therefore, we finally determined to use 129/211 as the standard value by considering the total step, the total time and the frequency synthetically. All the data is balanced by the logarithm of the base p/t of 129/211. We assume that the functional relationship between experience degree, step, and time is: Sti=log_0.63(p/t) [A (p/t)²+b (p/t) +c]. According to this inference, the formula for two surface fitting with the first 15 sets of data in the experimental data is as follows:

sti= log_0.63(p/t) [165 (p/t)²-109p/t+25.4] (1)

Its visualization is shown in Figure 1.

Fig. 1 schematic diagram of behavior-centric quantization results

The results of the following 9 groups of P and t data in the fitting formula were calculated to be STI, compared with the data e obtained in the Quantification method based on the experience, as shown in table 3:

Table 3 Experimental data based on behavior-centered quantification method

Comparing STI with E, the average difference between them was 8.6% between 1.72,sti and E. In combination with P, T, and p/t analysis, the trend of STI data is more apt to describe the experience trend of the operator. This shows that there are still some differences between the quantitative results from the subjective point of view and the quantitative results based on the behavior from the objective. And only the combination of three kinds of quantitative methods, fully consider the subjective and objective factors brought about by the quantitative differences, such a user experience quantification is more accurate.

(Note: This case is a quantitative method in the initial study completed, there are some deficiencies, the late study has improved, there is the opportunity to share with you.) The research thought aspect also hoped can give everybody some reference. ）

Concluding remarks

This series of articles presents a quantitative approach to three user experiences, which is to study behavior-centric quantization in the case of mobile phone experience. The final expression for the user experience level, experience step, and experience time is:

sti= log_0.63(p/t) [165 (p/t)²-109p/t+25.4]

The expression shows that the quantification based on behavior is to calculate the experience degree from the objective point of view. At the same time, through the comparative analysis of the data in the case, it shows that subjective and objective factors have significant difference to user experience. Therefore, in order to obtain a more satisfactory user experience quantification, we must consider the application of three methods synthetically. In the next step, we will use more samples to validate the other two methods based on the research in this paper, and to continue to study the quantification of the user experience in three different ways.