LEADER 04809nam 22007095 450 001 9910682565503321 005 20250515063245.0 010 $a9783031247583 010 $a3031247582 024 7 $a10.1007/978-3-031-24758-3 035 $a(MiAaPQ)EBC7217836 035 $a(Au-PeEL)EBL7217836 035 $a(OCoLC)1373986939 035 $a(DE-He213)978-3-031-24758-3 035 $a(PPN)26910013X 035 $a(CKB)26291142500041 035 $a(EXLCZ)9926291142500041 100 $a20230320d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aGuide to Teaching Data Science $eAn Interdisciplinary Approach /$fby Orit Hazzan, Koby Mike 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (xxvii, 321 pages) $cillustrations (black and white, and colour) 311 08$aPrint version: Hazzan, Orit Guide to Teaching Data Science Cham : Springer International Publishing AG,c2023 9783031247576 320 $aIncludes bibliographical references and index. 327 $aPart I: Overview of Data Science and Data Science Education -- Chapter 1. Introduction -- Chapter 2. What is data science -- Chapter 3. Introduction to data science education -- Chapter 4. Data science thinking -- Part II: Challenges of Data Science Education -- Chapter 5. The pedagogical challenge of data science education -- Chapter 6. Data science education and the variety of learners -- Chapter 7. The interdisciplinarity challenge -- Chapter 8. Data science skills -- Part III: Data science Teaching frameworks -- Chapter 9. Teacher Preparation - the Method for Teaching Data Science course -- Chapter 10. Data Science for Social Science -- Chapter 11. Conclusion. 330 $aData 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. 606 $aArtificial intelligence$xData processing 606 $aTeaching 606 $aQuantitative research 606 $aEducation$xData processing 606 $aAlgorithms 606 $aData Science 606 $aDidactics and Teaching Methodology 606 $aData Analysis and Big Data 606 $aComputers and Education 606 $aAlgorithms 615 0$aArtificial intelligence$xData processing. 615 0$aTeaching. 615 0$aQuantitative research. 615 0$aEducation$xData processing. 615 0$aAlgorithms. 615 14$aData Science. 615 24$aDidactics and Teaching Methodology. 615 24$aData Analysis and Big Data. 615 24$aComputers and Education. 615 24$aAlgorithms. 676 $a006.312 676 $a006.312 700 $aHazzan$b Orit$f1962-$01379565 702 $aMike$b Koby 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910682565503321 996 $aGuide to teaching data science$93419508 997 $aUNINA