## 4 Experimental Evaluation
### User Study  
In order to evaluate the utility of the behavior change tips of our system, we conducted a usability test with a group of students from the University of Cagliari, Italy. The study was conducted in June 2023. Participants were recruited through personal contacts and \begin{table}
\begin{tabular}{l c} \hline \hline
**Regressor** & \(r\) \\ \hline Random Forest & 0.22 \\ \hline Random Tree & 0.33 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Sleep quality forecasting results. networking. The participants of our study consisted of 10 students (7 males and 3 females) aged 21 through 26. The average age was 23. All of them had experience in the usage of smartphones and electronic interfaces. In our study, we employed the assessment framework introduced by [PERSON] et al. [35]. The evaluation process involved administering questionnaires and conducting interviews with participants after presenting them with an overview of the system and the related application. To measure agreement with the statements in the questionnaire, we utilized the _Likert scale_ method [36]. The questionnaire is presented in Table 2. Each participant had an individual meeting during which we provided a high-level explanation of the system's functionality. Subsequently, we demonstrated a customized version of our smartphone application without explanations, allowing participants to familiarize themselves with the interface. Afterward, we introduced the original application with explanations and observed the participants' interactions for a period. We then instructed the participants to independently use both versions of the application until they felt confident about the system's functionality and potential utility. Finally, the participants completed the questionnaire online through a form. The questions primarily focused on the application's utility, both with and without explanations for the obtained forecast, and whether the explanations were easy to understand. The participation of potential users, particularly students, was crucial in obtaining diverse perspectives and evaluating the application's suitability within its user base. Their responses contributed to a comprehensive assessment of the application's utility, highlighting its strengths and areas that required further attention. The results, illustrated in Figure 10, are visualized using a horizontal bar chart. The chart displays the percentage of responses for each question. This type of chart provides a clear and immediate representation of the emerging trends in the questionnaire, identifying the predominant trends and differences in user responses to the various questions. The average results for the questions regarding the system without explanations (Q1 and Q3) reached a mean value of 2.7 and 2.8, respectively. In contrast, the average results for the questions regarding the system with explanations (Q2 and Q4) were close to the value of 4 (mean value of 4.1 and 3.8, respectively). These average values highlight an improvement in the trust, usefulness, and understanding of the system when explanations are provided regarding the prediction of sleep quality. The responses suggest that users perceive practical value in the system with explanations and consider them helpful in assessing the system's reliability and making informed decisions. According to the results, the explanations