Smart Stem Driven Computer Science Education
Download Smart Stem Driven Computer Science Education PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Smart Stem Driven Computer Science Education book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Smart STEM-Driven Computer Science Education
At the centre of the methodology used in this book is STEM learning variability space that includes STEM pedagogical variability, learners’ social variability, technological variability, CS content variability and interaction variability. To design smart components, firstly, the STEM learning variability space is defined for each component separately, and then model-driven approaches are applied. The theoretical basis includes feature-based modelling and model transformations at the top specification level and heterogeneous meta-programming techniques at the implementation level. Practice includes multiple case studies oriented for solving the task prototypes, taken from the real world, by educational robots. These case studies illustrate the process of gaining interdisciplinary knowledge pieces identified as S-knowledge, T-knowledge, E-knowledge, M-knowledge or integrated STEM knowledge and evaluate smart components from the pedagogical and technological perspectives based on data gathered from one real teaching setting. Smart STEM-Driven Computer Science Education: Theory, Methodology and Robot-based Practices outlines the overall capabilities of the proposed approach and also points out the drawbacks from the viewpoint of different actors, i.e. researchers, designers, teachers and learners.
Evolution of STEM-Driven Computer Science Education
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-driven CS education strategies, curriculum development, and new ideas for research.
Smart Education and e-Learning 2020
This book contains the contributions presented at the 7th international KES conference on Smart Education and e-Learning (KES SEEL-2020), which being held as a virtual conference on June 17-19, 2020. It contains fifty three high quality peer-reviewed papers that are grouped into several interconnected parts: Part 1 – Smart Education, Part 2 – Smart e-Learning, Part 3 – Smart Pedagogy, Part 4 - Smart Education: Systems and Technology, Part 5 – Smart Education: Case Studies and Research, Part 6 - Smart University Development: Organizational and Managerial Issues, Part 7 - Smart Education and Smart Universities and their Impact on Students with Disabilities, Part 8 - Mathematical Models in Smart Education and e-Learning, and Part 9 - Models of Professional Practice in Higher Education. Smart education and smart e-learning are emerging and rapidly growing areas with the potential to transform existing teaching strategies, learning environments, and educational activities and technology in the classroom. Smart education and smart e-learning focus on enabling instructors to develop new ways of achieving excellence in teaching in highly technological smart classrooms, and providing students with new opportunities to maximize their success and select the best options for their education, location and learning style, as well as the mode of content delivery. This book serves as a useful source of research data and valuable information on current research projects, best practices and case studies for faculty, scholars, Ph.D. students, administrators, and practitioners – all those who are interested in smart education and smart e-learning.