129371 20241125101146.0 doi 10.3390/app132312704 sideral 135657 ART-2023-135657 eng Díaz-Pérez, Lucía Universidad de Zaragoza (orcid)0000-0003-3823-7903 Providing a Common Approach to Designing Dataset-Based Learning Activities Based on a Literature Review 2023 Access copy available to the general public Unrestricted While there are references available in the literature regarding learning experiences with Dataset-Based Learning (DBL) approaches, there is a noticeable absence of a standardized model for designing DBL activities. This gap was identified in this work after performing a systematic literature review (SLR). In contrast to other active learning methodologies, the lack of a common framework for the DBL methodology makes it challenging to compare different DBL approaches. This paper highlights the knowledge gap in the methodology for designing DBL activities and aims to provide a common approach for sharing the view and details about what DBL entails in higher education and how to design a DBL activity. Additionally, we illustrate these concepts with three case studies in different engineering fields. Based on the SLR results and the review of additional literature, this work defines DBL as an active teaching methodology that focuses on using datasets to promote the learning and understanding of specific concepts and skills. These datasets should contain real data presented in different formats. As a common starting point, in a DBL lesson, the dataset not only provides information and context in the activity statement but also serves as the material to work with, and the solution to the activity is entirely extracted from the information contained in the dataset. info:eu-repo/grantAgreement/ES/DGA/T21-23R info:eu-repo/grantAgreement/ES/DGA/T32-23R info:eu-repo/grantAgreement/ES/DGA/T56-23R info:eu-repo/grantAgreement/ES/DGA/T59-23R info:eu-repo/grantAgreement/EUR/ERASMUS+KA226/2020-1-IT02-KA226-HE-095144 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 2.5 2023 ENGINEERING, MULTIDISCIPLINARY 44 / 181 = 0.243 2023 Q1 T1 PHYSICS, APPLIED 87 / 179 = 0.486 2023 Q2 T2 CHEMISTRY, MULTIDISCIPLINARY 115 / 231 = 0.498 2023 Q2 T2 MATERIALS SCIENCE, MULTIDISCIPLINARY 258 / 439 = 0.588 2023 Q3 T2 0.508 2023 Engineering (miscellaneous) 2023 Q2 Fluid Flow and Transfer Processes 2023 Q2 Materials Science (miscellaneous) 2023 Q2 Instrumentation 2023 Q2 Process Chemistry and Technology 2023 Q3 Computer Science Applications 2023 Q3 5.3 2023 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Lopez-Pellicer, Francisco J. Universidad de Zaragoza (orcid)0000-0001-6491-7430 Brufau, Pilar Universidad de Zaragoza (orcid)0000-0002-0415-0001 Lacasta, Javier Universidad de Zaragoza (orcid)0000-0003-3071-5819 Trillo-Lado, Raquel Universidad de Zaragoza (orcid)0000-0001-6008-1138 Yagüe-Fabra, José A. Universidad de Zaragoza (orcid)0000-0001-7152-4117 Zarazaga-Soria, Francisco Javier Universidad de Zaragoza (orcid)0000-0002-6557-2494 5001 600 Universidad de Zaragoza Dpto. Ciencia Tecnol.Mater.Fl. Área Mecánica de Fluidos 5002 515 Universidad de Zaragoza Dpto. Ingeniería Diseño Fabri. Área Ing. Procesos Fabricación 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 13, 23 (2023), 12704 [25 pp.] Appl. sci. Applied Sciences (Switzerland) 2076-3417 1523330 http://zaguan.unizar.es/record/129371/files/texto_completo.pdf Versión publicada 2708337 http://zaguan.unizar.es/record/129371/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:129371 articulos driver 2024-11-22-12:04:28 ARTICLE