## 3 Establishing a Common Approach for Dataset-Based Learning
### Benefits and Challenges of DBL  
In this subsection, we present the benefits of DBL as a synthesis of the SLR results, and the combination of the benefits of active learning methodologies, studying real situations, and working with data. In addition, DBL provides a good scenario for teamwork and collaborative learning, as students can work with the datasets in teams. In that case, the benefits of collaborative learning are also achieved. Thus, the authors define the following benefits as the main benefits of using a DBL approach:  
* As an active learning methodology, it enhances student-centred learning: students are actively involved because the lesson requires active participation on their end [65] and they engage in the learning process [13]. * Active engagement in the learning process increases students' interests in the topic to be learned [66], which also enhances students' motivation, which significantly improves their learning [32]. * Better understanding and adeptness: Placing more emphasis on the meaning, applicability, and relevance of learning materials provides a better understanding of the subjects learned. When students are given more challenging and meaningful problems, they become more proficient [67]. * In-depth learning and constructivist approach: DBL fosters learning by involving students with interaction with learning materials. They relate the concept they study to real situations and problems [68]. * Self-motivated attitude: As in the above point, the use of resources close to reality improves the utility of the lessons and motivates students to learn [68]. * Emphasis on comprehension instead of facts: students must be able to discover the problems and their nature and develop a solution to them. In this method, collaborative research through discussion forums takes the place of lecturing. * Augmenting self-learning: Datasets force students to confront new scenarios that they must resolve. This generates interest and responsibility in their learning. * The use of real-world data enhances students' engagement [32]. When close-to-reality data are not used, students perceive their lessons as theoretical concepts unlikely to be applied to the real world [69]. This generates doubts in the utility of the lessons. * Providing research experience: The use of real datasets provides students with authentic/relevant research experience, helps teaching the process of science, and gives students a glimpse of how messy real data can be managed [11]. * Acquisition of data-related skills: Working with data enhances de acquisition of skills such as critical thinking [2], structural thinking [1], data literacy [3], computational thinking [4], and data-driven thinking [5]. In addition, data visualization fosters the development of critical thinking skills [33]. * Reinforcing interpersonal skills and teamwork: Teams work with shared datasets in collaboration, which fosters and reinforces interactions among students, teamwork, and interpersonal skills [70]. * In addition, this methodology is a particularly useful approach for subjects related to data management because it makes it \"easier\" to empathize with the problem and to understand the effects of the data management concepts learned. * Immediate student feedback: In a DBL activity, the teacher assumes the role of a guide, talking with students and monitoring their progress. This approach enables quick and accurate assessment of the students' learning [39]. However, developing this learning approach requires time and skills from the teacher responsible for preparing the activity. The main challenges that the teacher and students could face are the following:  
* As every active learning methodology, DBL activities require more preparation time to cover concepts than expositive traditional lessons [71]. However, active learning methodologies allow for a deeper understanding of the subject and the development of soft skills. * Discovering key dataset resources according to the topics of the subject may not be an easy task.