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Towards Data-Driven Learning Paths to Develop Computational Thinking with Scratch

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dc.contributor.authorMoreno-León, Jesús
dc.contributor.authorRobles, Gregorio
dc.contributor.authorRomán González, Marcos
dc.contributor.funderComunidad de Madrid
dc.date.accessioned2026-01-09T15:06:33Z
dc.date.available2026-01-09T15:06:33Z
dc.date.issued2017-08-01
dc.descriptionThis is an Accepted Manuscript of an article published by IEEE in "IEEE Transactions on Emerging Topics in Computing, vol. 8, no. 1, pp. 193-205, 1 Jan.-March 2020", available at: https://doi.org/10.1109/TETC.2017.2734818en
dc.descriptionEste es el manuscrito aceptado del artículo publicado por IEEE en "IEEE Transactions on Emerging Topics in Computing, vol. 8, no. 1, pp. 193-205, 1 Jan.-March 2020", disponible en línea: https://doi.org/10.1109/TETC.2017.2734818es
dc.description.abstractWith the introduction of computer programming in schools around the world, a myriad of guides are being published to support educators who are teaching this subject, often for the first time. Most of these books offer a learning path based on the experience of the experts who author them. In this paper we propose and investigate an alternative way of determining the most suitable learning paths by analyzing projects developed by learners hosted in public repositories. Therefore, we downloaded 250 projects of different types from the Scratch online platform, and identified the differences and clustered them based on a quantitative measure, the computational thinking score provided by Dr. Scratch. We then triangulated the results by qualitatively studying in detail the source code of the prototypical projects to explain the progression required to move from one cluster to the next one. The result is a data-driven itinerary that can support teachers and policy makers in the creation of a curriculum for learning to program. Aiming to generalize this approach, we discuss a potential recommender tool, populated with data from public repositories, to allow educators and learners creating their own learning paths, contributing thus to a personalized learning connected with students' interests.en
dc.description.provenanceMade available in DSpace on 2026-01-09T15:06:33Z (GMT). No. of bitstreams: 1 Towards_Data_Driven_Draft.pdf: 1748615 bytes, checksum: dc3afc96a35039c7a76be57e2b87406b (MD5) Previous issue date: 2017-08-01en
dc.description.sponsorshipThis work has been funded in part by the Region of Madrid under project “eMadrid - Investigación y Desarrollo de tecnolog´as para el e-learning en la Comunidad de Madrid” (S2013/ICE-2715).en
dc.description.versionversión final
dc.identifier.citationJ. Moreno-LeÓn, G. Robles and M. RomÁn-GonzÁlez, "Towards Data-Driven Learning Paths to Develop Computational Thinking with Scratch," in IEEE Transactions on Emerging Topics in Computing, vol. 8, no. 1, pp. 193-205, 1 Jan.-March 2020, doi: 10.1109/TETC.2017.2734818
dc.identifier.doihttps://doi.org/10.1109/TETC.2017.2734818
dc.identifier.issn2168-6750
dc.identifier.urihttps://hdl.handle.net/20.500.14468/31338
dc.journal.issue1
dc.journal.titleIEEE Transactions on Emerging Topics in Computing
dc.journal.volume8
dc.language.isoen
dc.page.final205
dc.page.initial193
dc.publisherIEEE
dc.relation.centerFacultad de Educación
dc.relation.departmentMétodos de Investigación y Diagnóstico en Educación I
dc.relation.projectidS2013/ICE-2715
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject5802.07 Formación profesional
dc.subject.keywordsProgrammingen
dc.subject.keywordscomputational thinkingen
dc.subject.keywordslearning pathsen
dc.subject.keywordsdata-drivenen
dc.subject.keywordsScratchen
dc.subject.odsODS 4 - Educación de calidad
dc.titleTowards Data-Driven Learning Paths to Develop Computational Thinking with Scratchen
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
relation.isAuthorOfPublicationf326c028-97b6-4d2b-bfdf-25491ee66c8a
relation.isAuthorOfPublication.latestForDiscoveryf326c028-97b6-4d2b-bfdf-25491ee66c8a
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