Evolution of STEM-Driven Computer Science Education The Perspective of Big Concepts /
The 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 as...
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| Autori principali: | , |
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| Natura: | Elettronico eBook |
| Lingua: | inglese |
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Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
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| Edizione: | 1st ed. 2024. |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1007/978-3-031-48235-9 |
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| 100 | 1 | |a Štuikys, Vytautas. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Evolution of STEM-Driven Computer Science Education |h [electronic resource] : |b The Perspective of Big Concepts / |c by Vytautas Štuikys, Renata Burbaitė. |
| 250 | |a 1st ed. 2024. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2024. | |
| 300 | |a 1 online resource (XVI, 360 p. 83 illus.). |b 39 illus. in color. | ||
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| 505 | 0 | |a Context 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 | |a The 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-drivenCS education strategies, curriculum development, and new ideas for research. . | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
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| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-48235-9 |
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