04184nam a22005535i 4500 978-3-031-48235-9 DE-He213 20251030110905.0 cr nn 008mamaa 231227s2024 sz | s |||| 0|eng d 9783031482359 978-3-031-48235-9 10.1007/978-3-031-48235-9 doi Q342 UYQ bicssc COM004000 bisacsh UYQ thema Štuikys, Vytautas. author. aut http://id.loc.gov/vocabulary/relators/aut 68777 Evolution of STEM-Driven Computer Science Education [electronic resource] : The Perspective of Big Concepts / by Vytautas Štuikys, Renata Burbaitė. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XVI, 360 p. 83 illus., 39 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda 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. 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. . Computational intelligence. 64052 Education Data processing. Software engineering. 33953 Robotics. 59148 Computational Intelligence. 64052 Computers and Education. Software Engineering. 33953 Robotics. 59148 Burbaitė, Renata. author. aut http://id.loc.gov/vocabulary/relators/aut 68778 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031482342 Printed edition: 9783031482366 Printed edition: 9783031482373 https://doi.org/10.1007/978-3-031-48235-9 ZDB-2-SCS ZDB-2-SXCS 56967 56967