Evolution of STEM-Driven Computer Science Education: The Perspective of Big Concepts
Autor Vytautas Štuikys, Renata Burbaitėen Limba Engleză Hardback – 2 ian 2024
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.
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Specificații
ISBN-13: 9783031482342
ISBN-10: 3031482344
Pagini: 360
Ilustrații: XVI, 360 p. 83 illus., 39 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.7 kg
Ediția:1st ed. 2024
Editura: Springer Nature Switzerland
Colecția Springer
Locul publicării:Cham, Switzerland
ISBN-10: 3031482344
Pagini: 360
Ilustrații: XVI, 360 p. 83 illus., 39 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.7 kg
Ediția:1st ed. 2024
Editura: Springer Nature Switzerland
Colecția Springer
Locul publicării:Cham, Switzerland
Cuprins
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.
Notă biografică
Vytautas Štuikys is a Professor-emeritus. He holds PhD and doctor habilitatus degrees in Software Engineering. and Computer Science. His research interests include automated design (including STEM-driven systems and components) using high-level models and approaches (including AI-based ones). He has published more than 150 papers in the international Journals and Conference Proceedings. He is an author (co-author) of four monographs published by Springer Nature.
Renata Burbaitė, PhD, is an Informatics (Computer Science, Robotics) teacher at school and an Assoc. Professor at the Software Engineering Department of Kaunas University of Technology. Her research interests include smart education system design, Computer Science (CS) educational domain modelling, STEM-oriented robot-based CS education methodologies. She organizes seminars and workshops for the country's informatics teachers and serves on the assessment board of the State matriculation exam in information technology. She is a co-author of more than 40 research papers and monographs, Smart STEM-Driven Computer Science Education: Theory, Methodology, and Robot-Based Practices”, published by Springer in 2018, and of 4 textbooks for high school students.
Textul de pe ultima copertă
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.
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.
Caracteristici
Includes an evolutionary model to understand the aim and content of the book Covers Big Concepts - the Internet of Things, Data Science, Artificial Intelligence and Robotics from a didactic view Guides the creation of STEM/CS-based teaching materials to better integrate these topics into the learning process