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  • Gebundenes Buch

Data science is a new field that touches on almost every domain of our lives, and thus it is taught in a variety of environments. Accordingly, the book is suitable for teachers and lecturers in all educational frameworks: K-12, academia and industry.
This book aims at closing a significant gap in the literature on the pedagogy of data science. While there are many articles and white papers dealing with the curriculum of data science (i.e., what to teach?), the pedagogical aspect of the field (i.e., how to teach?) is almost neglected. At the same time, the importance of the pedagogical…mehr

Produktbeschreibung
Data science is a new field that touches on almost every domain of our lives, and thus it is taught in a variety of environments. Accordingly, the book is suitable for teachers and lecturers in all educational frameworks: K-12, academia and industry.

This book aims at closing a significant gap in the literature on the pedagogy of data science. While there are many articles and white papers dealing with the curriculum of data science (i.e., what to teach?), the pedagogical aspect of the field (i.e., how to teach?) is almost neglected. At the same time, the importance of the pedagogical aspects of data science increases as more and more programs are currently open to a variety of people.

This book provides a variety of pedagogical discussions and specific teaching methods and frameworks, as well as includes exercises, and guidelines related to many data science concepts (e.g., data thinking and the data science workflow), main machine learning algorithms and concepts (e.g., KNN, SVM, Neural Networks, performance metrics, confusion matrix, and biases) and data science professional topics (e.g., ethics, skills and research approach).

Professor Orit Hazzan is a faculty member at the Technion's Department of Education in Science and Technology since October 2000. Her research focuses on computer science, software engineering and data science education. Within this framework, she studies the cognitive and social processes on the individual, the team and the organization levels, in all kinds of organizations.

Dr. Koby Mike is a Ph.D. graduate from the Technion's Department of Education in Science and Technology under the supervision of Professor Orit Hazzan. He continued his post-doc research on data science education at the Bar-Ilan University, and obtained a B.Sc. and an M.Sc. in Electrical Engineering from Tel Aviv University.
Autorenporträt
Dr. Orit Hazzan is Professor at the Department of Education in Science and Technology at Technion - Israel Institute of Technology. Her other publications include the Springer titles Application of Management Theories for STEM Education, Risk Management of Education Systems, The MERge Model for Business Development, Agile Anywhere, and Agile Software Engineering. Dr. Noa Ragonis is a researcher in the field of computer science education, focusing on cognitive aspects of teaching and learning, particularly in relation to logic programming, object oriented programming, and computational thinking. She has authored ten computer science high-school textbooks and teachers' guides. Dr. Tami Lapidot is Executive Manager of Machshava - the Israeli National Center for Computer Science Teachers. All three authors have extensive experience of teaching, management, research, and involvement in computer science teacher preparation programs, as well as of participation in national initiatives and policy-making committees. They have taught courses on computer science and on computer science education to high school pupils, undergraduate students, and pre-service and in-service teachers. The research the authors have conducted examines a variety of computer science education topics, including teaching methods, learning processes, teacher preparation, and social and organizational issues of computer science education.