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008			231227s2024 sz | o |||| 0|eng d
020			_a9783031482359
024	7		_a10.1007/978-3-031-48235-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ342 _b2024 EB
100	1		_aŠtuikys, V. _q(Vytautas) _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9689351
245	1	0	_aEvolution of STEM-Driven Computer Science Education _b: The Perspective of Big Concepts _cby Vytautas Štuikys, Renata Burbaitė
250			_afirst edition 2024
264		1	_aCham _c2024 _bSpringer International Publishing
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF
505	0		_aContext and model for writing this book: An idea of big concepts -- Part 1: Pedagogical aspects of STEM-driven CS education evolution: Integrated STEM-CS Skills model, personalisation aspects and collaborative learning -- Models for the development and assessment of Integrated STEM (ISTEM) Skills: A case study -- Enforcing STEM-driven CS education through personalisation -- Personal generative libraries for personalised learning: A case study -- Enforcing STEM-driven CS education through collaborative learning -- Part 2: Internet of Things (IoT) and Data Science (DS) concepts in K-12 STEM-driven CS education.-Methodological aspects of educational internet of things -- Multi-stage prototyping for introducing IoT concepts: A case study -- Introducing data science concepts into STEM-driven computer science education -- Part 3: Introduction to artificial intelligence -- A vision for introducing AI topics: A case study -- Speech recognition technology in K-12 STEM-driven computer science education -- Introduction to artificial neural networks and machine learning -- Overall evaluation of this book concepts and approaches.
520			_aThe book discusses the evolution of STEM-driven Computer Science (CS) Education based on three categories of Big Concepts, Smart Education (Pedagogy), Technology (tools and adequate processes) and Content that relates to IoT, Data Science and AI. For developing, designing, testing, delivering and assessing learning outcomes for K-12 students (9-12 classes), the multi-dimensional modelling methodology is at the centre. The methodology covers conceptual and feature-based modelling, prototyping, and virtual and physical modelling at the implementation and usage level. Chapters contain case studies to assist understanding and learning. The book contains multiple methodological and scientific innovations including models, frameworks and approaches to drive STEM-driven CS education evolution. Educational strategists, educators, and researchers will find valuable material in this book to help them improve STEM-driven CS education strategies, curriculum development, and new ideas for research. .
988			_aSpringer_Computer_2024
650		7	_2embne _aInteligencia artificial _9413115
700	1		_9689695 _aBurbaitė, Renata _eautor
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-48235-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2024 _dz _ejc _zSI