## 5 Case Studies
### DBL in a Course of Fluid Mechanics  
Another example of application of DBL could be oriented towards a real scenario scaled down to laboratory practice, in this case, for free surface flow, in line with [32] but using experimental data instead of computational data. The activity is part of one of the practical sessions in the mandatory subject of fluid mechanics in the mechanical engineering degree program. Its goal is to enhance the understanding of concepts related to free surface flow. The use of data in this activity offers significant benefits in enhancing the educational experience. Incorporating data-driven approaches into the learning process provides students with practical hands-on experience to go beyond theoretical concepts in a faster and direct way. It is crucial to ensure that the size of the dataset is manageable and aligned with the students' abilities. The complexity of the dataset should be adjusted to a level that is suitable for the students' understanding and skills, enabling them to effectively address the collection, analysis, and interpretation of data within the context of the learning activity. In a traditional experimental activity, students measure and collect data automatically, without thinking about the concepts they are handling; students are thus forced to carry out work after the laboratory session to analyse the data collected and find themselves disconnected from the master class, which often leads to them not always performing the task at hand. With this DBL approach and design of the activity, students gain a deeper understanding of these fundamental concepts during the session itself. Students develop essential data analysis and interpretation skills by working with the collected dataset in the laboratory. Identifying patterns, trends, and relationships in the data enables students to draw meaningful conclusions and extract relevant information to achieve the learning objectives. This DBL approach aims to enhance students' critical thinking and teamwork skills, which a traditional activity does not allow to achieve. The variability in the collected datasets among different teams encourages students to think critically about the factors influencing the outcomes. Collaborative work in teams promotes effective communication and teamwork, essential skills in engineering and problem solving. The asynchronous activity, including conducting surveys and seeking feedback from students, contributes to continuous improvement. Understanding the effectiveness of the data-driven teaching process and the students' learning experiences empowers the teacher to make informed decisions to enhance the methodology for future sessions. The DBL approach thus proves instrumental in improving the learning experience, addressing the limitations of traditional approaches. During course scripting, the teacher identifies the learning outcomes to work on with the students during the activity. In this case, they were steady-flow conditions, uniform flow, classification of subcritical or supercritical flow, and detection of a hydraulic jump generation. Regarding the soft skills to be acquired, the aim was mainly to enhance students' skills in critical thinking and teamwork. Once the learning outcomes are identified, the teacher designs the experimental conditions (in this case, bed slope of the channel, initial and boundary conditions) and establishes the real-world context on which the activity is based, adapting it to the available laboratory facility. As a final step in this process, the professor sets up the installation, prepares the measuring instruments, and creates a script for students detailing how to collect the experimental data they need to work on during the lesson. By proposing different conditions in the setup and flow, the discussion of student results in the activity is promoted, as the collected dataset may vary from one team to another. During the synchronous lesson, in a 2 h session with nine students at the same time divided in three teams, the steps were the following:  
1.