## 4 Results and Discussion
### Case Study Results
#### 4.1.2 Results  
Following the methodology chosen for the case study and taking into account the proposed hypothesis, we presented the updated version of Coco Shapes and its web application to the school's stakeholders to obtain feedback on the support provided by the data in terms of monitoring students. The presentation was carried out at the school facilities, and the responses of those interested were recorded with their respective authorization.  
Tokenization of the text was carried out to analyze the feedback. In this phase, the entire text was decomposed into individual words to facilitate a detailed analysis. A data frame was created to house these tokenized words, allowing for more efficient manipulation and analysis [54]. Data cleaning was then performed to eliminate common words or'stopwords' that do not add substantial meaning based on a predefined list of stopwords in Spanish. In addition, specific numbers and markers were eliminated to improve the data-cleaning process. Data cleaning was further enhanced by removing 'not available' (NA) [55] values and empty strings, thus ensuring the quality and relevance of the dataset for analysis.  
Exploratory data analysis was then performed, focusing on the frequency of the words. The frequency of each word was calculated and represented as a percentage of the total. A filter was set to include only words for which the frequency exceeded a specific threshold, such as more than 1%, to allow us to focus on the most relevant terms. This quantitative analysis was complemented by a graphic visualization using a bar graph, making it possible to identify the most common words in the stakeholder discussion.  
An emotion analysis was also carried out [56] to identify and extract emotional connotations in the language of the texts. This approach allowed us to determine whether the tone was positive, negative, or neutral and to capture both explicit expressions of emotions and subtle nuances. This technique allows for an objective and automatic evaluation of the attitudes and feelings of the author of a piece of text, thus offering a deeper and more  
Figure 8: Average usage times for Coco Shapes.  
quantifiable understanding of the perceptions and emotional reactions of the interviews. The analysis used the statistical program R version 4.1.1 [53; 57].  
Figure 9 shows the distribution of various emotions, highlighting that positive emotions (32.53%) and trust (20.48%) have the highest values. This suggests that participants perceive the studied environment, likely related to the integration of LA into multimedia experiences, favorably and trustingly. This prevalence indicates that users find value and security in implementing the proposed guidelines. Additionally, the considerable representation of anticipation (13.25%) suggests that participants accept the guidelines and have positive expectations for their future implementation, reinforcing the guidelines' effectiveness in generating interest and anticipation. Although joy (8.43%), surprise (7.23%), and sadness (3.61%) have lower representations, their presence points to areas where the guidelines can be adjusted to increase satisfaction and reduce stress or dissatisfaction. Negative emotions (8.43%) and disgust (2.41%) are low but present, indicating that while the general perception is positive, specific aspects could be improved. Emotion is a crucial component in the learning experience, and the presence of emotions, such as trust and positivity, indicates that the guidelines are aligned with users' emotional needs, which is essential for engagement and learning effectiveness. Fear (2.41%) and anger (1.2%) are minimal, which is positive since such emotions can harm learning and collaboration. In summary, the distribution of emotions revealed by the figure justifies the relevance of these categories in the study, showing that the proposed guidelines are functional and emotionally resonant with users, which is crucial for their success and adoption.