01338nam0 2200265 450 00004212620160607102049.020160607d1966----km-y0itaa50------baitaITDante e l'Italia meridionaleAtti del secondo Congresso nazionale di studi danteschi a cura del seminario di studi danteschi di Caserta, sotto gli auspici della Società Dantesca Italiana e della Società Nazione Dante AlighieriCaserta-Benevento-Cassino-Salerno-Napoli, 10-16 Ottobre 1965Firenze<<L.S.>> Olschki1966LXXI, 512 p.28 tav.25 cm.in testa al front. : Comitato nazionale per le celebrazioni del VII centenario della nascita di DanteAtti del II Congresso nazionale di Studi danteschiCongresso nazionale di studi danteschi<2.1965Caserta-Benevento-Cassino-Salerno-Napoli>305054ITUniversità della Basilicata - B.I.A.REICATunimarc000042126Dante e l'Italia meridionale132242UNIBASLETTERESTD1100120160607BAS011019STD1100120160607BAS011020BAS01BAS01BOOKBASA1Polo Storico-UmanisticoDSLFCollezione DiSLFDF/SE3853941F39412016060702Prestabile Generale04581nam 22006855 450 991072009300332120250610115742.09789819900268(electronic bk.)978981990025110.1007/978-981-99-0026-8(MiAaPQ)EBC7243092(Au-PeEL)EBL7243092(DE-He213)978-981-99-0026-8(OCoLC)1378936602(PPN)26965819X(CKB)26540740900041(EXLCZ)992654074090004120230429d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierEducational Data Science: Essentials, Approaches, and Tendencies Proactive Education based on Empirical Big Data Evidence /edited by Alejandro Peña-Ayala1st ed. 2023.Singapore :Springer Nature Singapore :Imprint: Springer,2023.1 online resource (298 pages)Big Data Management,2522-0187Print version: Peña-Ayala, Alejandro Educational Data Science: Essentials, Approaches, and Tendencies Singapore : Springer,c2023 9789819900251 Includes bibliographical references and index.1. Engaging in Student-Centered Educational Data Science through Learning Engineering -- 2. A review of clustering models in educational data science towards fairness-aware learning -- 3. Educational Data Science: Is an “Umbrella Term” or an Emergent Domain? -- 4. Educational Data Science Approach for End-to-End Quality Assurance Process for Building Credit-Worthy Online Courses -- 5. Understanding the Effect of Cohesion in Academic Writing Clarity Using Education Data Science -- 6. Sequential pattern mining in educational data: the application context, potential, strengths, and limitations -- 7. Sync Ratio and Cluster Heat Map for Visualizing Student Engagement.This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to leverage and produce descriptive, explanatory, and predictive closures to study and understand education phenomena at in classroom and online environments. This is why diverse researchers and scholars contribute with valuable chapters to ground with well-–sounded theoretical and methodological constructs in the novel field of Educational Data Science (EDS), which examines academic big data repositories, as well as to introduces systematic reviews, reveals valuable insights, and promotes its application to extend its practice. EDS as a transdisciplinary field relies on statistics, probability, machine learning, data mining, and analytics, in addition to biological, psychological, and neurological knowledge aboutlearning science. With this in mind, the book is devoted to those that are in charge of educational management, educators, pedagogues, academics, computer technologists, researchers, and postgraduate students, who pursue to acquire a conceptual, formal, and practical landscape of how to deploy EDS to build proactive, real- time, and reactive applications that personalize education, enhance teaching, and improve learning! Chapter “Sync Ratio and Cluster Heat Map for Visualizing Student Engagement” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.Big Data Management,2522-0187Artificial intelligenceData processingData miningBig dataData ScienceData Mining and Knowledge DiscoveryBig DataEducacióthubProcessament de dadesthubDades massivesthubLlibres electrònicsthubArtificial intelligenceData processing.Data mining.Big data.Data Science.Data Mining and Knowledge Discovery.Big Data.Educació.Processament de dadesDades massives005.7Peña-Ayala Alejandro1355139MiAaPQMiAaPQMiAaPQ9910720093003321Educational Data Science: Essentials, Approaches, and Tendencies4332087UNINA