# Innovating Statistics Education: The Design of a Novel App Using Design Thinking
## 4 EstApp Design Process  
### Empathize Phase: Activities and Results  
In the Empathize stage, a qualitative study was conducted involving interviews with a total of 14 participants, 8 students (who learned or are learning statistics at university), and 6 professors (who teach statistics) from the Pontificia Universidad Catolica de Valparaiso (PUCV), Chile. The purpose of these interviews was to gain a deep understanding of users' experiences, needs, and perceptions regarding the learning and teaching of descriptive statistics in the university context. Appendix A shows the questions asked in the interviews. The findings revealed that, while students value the applicability of statistics, they face significant challenges such as data interpretation and a lack of motivation stemming from unengaging methodologies. On the other hand, professors reported varied experiences in teaching the discipline, highlighting the main obstacles to be difficulty in motivating student participation and grounding abstract concepts.  
Additionally, a survey was conducted involving 440 students from diverse undergraduate programs at PUCV, including business administration, computer science, accounting, bachelors of science, biology, social work, and statistics, among others. The objective of the survey was to understand the needs of users (upper-level students) related to learning statistics, as well as their motivations and frustrations when facing any course related to descriptive statistics. The open-ended questions allowed for the identification of concerns related to unintuitive interfaces, lack of practical exercises, and decontextualized applications. On the other hand, Likert-type questions revealed a marked interest in applications that incorporate examples related to the area of study, attractive visualizations, and the ability to generate data.  
Furthermore, a comparative analysis (benchmarking) of existing applications and tools for learning and analyzing statistics was conducted. Table 2 shows the comparative analysis between the applications Kahoot [34], Mentimeter [35], Codap [36], Rossmanchance [37], Fathom [24], and ArtofStat [38] considering 3 criteria:  
1. [noitemsep]
2. Usability: high level (intuitive and easy-to-use interface), medium level (slightly confusing interface), low level (non-intuitive interface, difficult to use).
3. Language: high level (use of non-technical language that is easy to understand for non-experts), medium level (use of some technical concepts to explain), low level (use of technical and specific language, difficult to understand for those who do not know statistics).
4. Design: high level (pleasant and aesthetic interface), medium level (interface with some visually annoying elements), low level (unattractive and unfriendly interface for the user).  
The results indicated that, while some applications like Kahoot [34] and Mentimeter [35] facilitate learning in the classroom, they lack advanced statistical functions. On the other hand, tools like Codap [36], Fathom [24], Rossmanchance [37], and ArtofStats [38] allow for data analysis but have unintuitive interfaces and a high degree of technicality.  
Collectively, the findings from the Empathize phase provided a deep understanding of the needs, challenges, and motivations of students and professors regarding the learning and teaching of descriptive statistics. This information was useful for defining user profiles, empathy maps, and key requirements of the EstApp application in subsequent design process phases.