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.

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.

Recently, there has been a significant increase in the development and interest in applying generative AI across various domains, including education. The emergence of large language models (LLMs), such as the ChatGPT tool, fueled by advancements in generative AI, is profoundly reshaping education. The use of the ChatGPT tool offers personalized support, improves accessibility, and introduces innovative methods for students and educators to engage with information and learning materials. Furthermore, ChatGPT facilitates a wide range of language learning services, including language instruction, speech recognition, pronunciation feedback, and immersive virtual simulations for hands-on learning experiences. This book explores the transformative potential of the ChatGPT tool within education, shedding light on the opportunities that arise through the integration of the ChatGPT tool into various aspects of the learning process. It serves as a platform for the community to share cutting-edge research ideas concerning the use of the ChatGPT tool in digital education. Readers will discover how the ChatGPT tool can enhance student engagement, foster personalized learning experiences, facilitate intelligent tutoring systems, support virtual classroom interactions, and revolutionize assessment and feedback mechanisms.

Many educators in the realm of higher education face the critical challenge of fostering creativity in students using traditional teaching methods. In today's rapidly evolving world, these methods have become inadequate to nurture the innovative thinking demanded by modern society. Impacts of Generative AI on Creativity in Higher Education reveals a solution in the integration of generative AI into higher education. To revolutionize how we nurture and harness student creativity, the book explores the intersection of creativity, generative AI, and higher education with a fresh perspective and practical guidance for educators and institutions. It delves into the fundamental concepts of generative AI and its potential applications, providing educators with the tools to create more engaging and innovative learning environments.

This book is about the Internet of Things in the field of education. Specifically, it focuses on two major topics: IoT (Internet of Things) solutions to support distance education and new pedagogical approaches to support development of computational thinking with educational devices possessing the characteristics of IoT. As the educational landscape has dramatically changed in times of global pandemic, online resources and media, such as IoT, have become increasingly important. This situation compels all educational scholars, researchers and practitioners to search for new solutions, new educational pathways and new agents for knowledge development to support learning. This book presents the possibilities of IoT as both a catalyst and performance tool for education. The convergence of multiple technologies, real-time analytics, machine learning, commodity sensors, and embedded systems can serve as tools for learning support and this book details exactly how these powerful tools can be utilized to best effect.

The Adams Jobs Almanac provides an unprecedented amount of information on career opportunities and strategies. The book includes: - Names and addresses for thousands of leading employers nationwide - Information for which jobs each company commonly hires - Industry forecasts and geographical cross-references - Job outlooks for a variety of professions - Multiple extensive indexes - Advice on preparing resumes and succeeding at interviews - The latest information on online job resources With annually updated information, The Adams Jobs Almanac is the most comprehensive national career reference guide available!