## 6 Conclusions  
While it is common for students at higher-education levels to engage in activities involving dataset analysis, data visualization, and drawing conclusions from data, there is a lack of established models for DBL methodologies in the existing literature. Therefore, the purpose of this work is twofold: to present a clear definition of Dataset-Based Learning and to provide a comprehensive guide for designing activities using this approach. This study begins with a systematic literature review that analyses the use of datasets in higher-education active learning activities. For this purpose, documents in the field of education from the databases of Scopus and WOS containing the words \"data\" and \"active learning\" were located. From a total of 236 located results, 16 documents were analysed for this SLR. Most of the reviewed documents present case studies that combine the use of datasets with other active methodologies [34; 35; 37; 38; 43; 44] or that take place in laboratory modules [36; 39]. The review articles also highlight the importance of using real-world data [31; 32; 34; 35; 37; 38; 39; 46], which can be given to the students; obtained using simulations; or gathered by the students themselves using different methods, such as consulting data sources or running experiments. Some of the review papers also state that using datasets in active learning activities is associated with benefits such as improved confidence and enhance learning [31; 32]. Upon examining the literature, we determine that DBL is an active learning approach that can be used as a stand-alone methodology or integrated with other methodologies, incorporating a distinctive element: placing datasets at the core of the activity. The paper continues by establishing a clear definition of a DBL lesson. In this lesson, the dataset provides information and context to the activity, the material to work with, and the solution to the activity that can be extracted from the information contained in the dataset itself. The DBL approach emphasizes the acquisition of concepts through practical engagement with real-world situations. Concepts are presented as a formalization of the actions that are necessary to work with reality. In this sense, the teaching process is quite different from classical ones that usually present concepts as abstract elements that must be set down by concreting them in realistic scenarios. The main characteristics of a dataset, such as its size and complexity, were analysed, since they need to be considered when designing a DBL activity. Moreover, the benefits and challenges of DBL were deduced from the SLR and by combining the advantages of active learning methodologies, studying real-world situations, working with data, and engaging in collaborative learning. Afterwards, a common approach to designing a DBL lesson is presented. The teaching process is divided into three main phases: course scripting, lesson flow, and evaluation and optimization of the learning process. The steps to be followed in each of these phases are described in detail. Next, we present three case studies contextualized in different engineering fields that were designed according to the proposed common approach, and we outline the benefits of using a DBL methodology as opposed to traditional approaches. Then, the paper presents three case studies in which teachers used the proposed common approach for DBL to design their activities. These three case studies help to prove the application of the proposed approach in different fields of engineering and how using a DBL approach presents advantages compared with traditional methodologies. These case studies help to illustrate what a DBL activity is, which we consider essential in this article, because although we found examples of DBL in the SLR, none of them were explicitly identified as DBL. The three cases contribute, in different roles, to the design of DBL activities, each one emphasizing specific aspects of data analysis, interpretation, and application.