Computational Thinking In Sound

Computational Thinking in Sound is the first book for music fundamentals educators which is devoted specifically to music, sound, and technology. The book offers practical guidance on creating an interdisciplinary classroom program, and includes numerous student activities at the intersection of computing and music.

Through examples and analogies, Computational Thinking for the Modern Problem Solver introduces computational thinking as part of an introductory computing course and shows how computer science concepts are applicable to other fields. It keeps the material accessible and relevant to noncomputer science majors. With numerous color figures, this classroom-tested book focuses on both foundational computer science concepts and engineering topics. It covers abstraction, algorithms, logic, graph theory, social issues of software, and numeric modeling as well as execution control, problem-solving strategies, testing, and data encoding and organizing. The text also discusses fundamental concepts of programming, including variables and assignment, sequential execution, selection, repetition, control abstraction, data organization, and concurrency. The authors present the algorithms using language-independent notation.

Recording Analysis: How the Record Shapes the Song identifies and explains how the sounds imparted by recording processes enhance the artistry and expression of recorded songs. Moylan investigates how the process of recording a song transforms it into a richer experience and articulates how the unique elements of recorded sound provide essential substance and expression to recorded music. This book explores a broad array of records, evaluating the music, lyrics, social context, literary content and meaning, and offers detailed analyses of recording elements as they appear in a wide variety of tracks. Accompanied by a range of online resources, Recording Analysis is an essential read for students and academics, as well as practitioners, in the fields of record production, song-writing and popular music.

While the growth of computational thinking has brought new awareness to the importance of computing education, it has also created new challenges. Many educational initiatives focus solely on the programming aspects, such as variables, loops, conditionals, parallelism, operators, and data handling, divorcing computing from real-world contexts and applications. This decontextualization threatens to make learners believe that they do not need to learn computing, as they cannot envision a future in which they will need to use it, just as many see math and physics education as unnecessary. The Handbook of Research on Tools for Teaching Computational Thinking in P-12 Education is a cutting-edge research publication that examines the implementation of computational thinking into school curriculum in order to develop creative problem-solving skills and to build a computational identity which will allow for future STEM growth. Moreover, the book advocates for a new approach to computing education that argues that while learning about computing, young people should also have opportunities to create with computing, which will have a direct impact on their lives and their communities. Featuring a wide range of topics such as assessment, digital teaching, and educational robotics, this book is ideal for academicians, instructional designers, teachers, education professionals, administrators, researchers, and students.

A guide to computational thinking education, with a focus on artificial intelligence literacy and the integration of computing and physical objects. Computing has become an essential part of today’s primary and secondary school curricula. In recent years, K–12 computer education has shifted from computer science itself to the broader perspective of computational thinking (CT), which is less about technology than a way of thinking and solving problems—“a fundamental skill for everyone, not just computer scientists,” in the words of Jeanette Wing, author of a foundational article on CT. This volume introduces a variety of approaches to CT in K–12 education, offering a wide range of international perspectives that focus on artificial intelligence (AI) literacy and the integration of computing and physical objects. The book first offers an overview of CT and its importance in K–12 education, covering such topics as the rationale for teaching CT; programming as a general problem-solving skill; and the “phenomenon-based learning” approach. It then addresses the educational implications of the explosion in AI research, discussing, among other things, the importance of teaching children to be conscientious designers and consumers of AI. Finally, the book examines the increasing influence of physical devices in CT education, considering the learning opportunities offered by robotics. Contributors Harold Abelson, Cynthia Breazeal, Karen Brennan, Michael E. Caspersen, Christian Dindler, Daniella DiPaola, Nardie Fanchamps, Christina Gardner-McCune, Mark Guzdial, Kai Hakkarainen, Fredrik Heintz, Paul Hennissen, H. Ulrich Hoppe, Ole Sejer Iversen, Siu-Cheung Kong, Wai-Ying Kwok, Sven Manske, Jesús Moreno-León, Blakeley H. Payne, Sini Riikonen, Gregorio Robles, Marcos Román-González, Pirita Seitamaa-Hakkarainen, Ju-Ling Shih, Pasi Silander, Lou Slangen, Rachel Charlotte Smith, Marcus Specht, Florence R. Sullivan, David S. Touretzky

Computational thinking is a lifelong skill important for succeeding in careers and life. Students especially need to acquire this skill while in school as it can assist with solving a number of complex problems that arise later in life. Therefore, the importance of teaching computational thinking and coding in early education is paramount for fostering problem-solving and creativity. Teaching Computational Thinking and Coding to Young Children discusses the importance of teaching computational thinking and coding in early education. The book focuses on interdisciplinary connections between computational thinking and other areas of study, assessment methods for computational thinking, and different contexts in which computational thinking plays out. Covering topics such as programming, computational thinking assessment, computational expression, and coding, this book is essential for elementary and middle school teachers, early childhood educators, administrators, instructional designers, curricula developers, educational software developers, researchers, educators, academicians, and students in computer science, education, computational thinking, and early childhood education.

"This book outlines a musical journey through Scratch. Scratch is an approachable computer programming environment that contains a rich set of media features, such as music and sound - both of which are explored here. The book features a series of independent musical projects built in Scratch and guides readers through the processes required to create each project. Readers will encounter coding techniques and algorithmic music processes while completing the exercises. In general, the projects are very interactive and encourage readers to make music through playing and composing with each task"--

An international overview of how policy makers, curriculum developers, and school practitioners can integrate computational thinking into K–12 curricula. In today’s digital society, computational thinking (CT) is a critical component of all children’s education. In Computational Thinking Curricula in K–12, editors Harold Abelson and Siu-Cheung Kong present a range of professional perspectives on the most effective ways to integrate CT into school curricula. Their edited volume, which offers an overview of educational policy, curriculum development, school implementation, and classroom practice, will appeal especially to policy makers, curriculum developers, school practitioners, and educational researchers. The essays cover twelve countries and regions across three continents: Australia, China, Finland, Hong Kong, India, Israel, New Zealand, Singapore, South Korea, Spain, Taiwan, and the United Kingdom, with a particular emphasis on Asia. A companion to the editors’ earlier Computational Thinking Education in K–12, this book consists of two sections: 1) educational policy and curriculum development and 2) school implementation and classroom practice. The authors delve into issues of regional history; governmental planning; official initiatives; leadership commitment; curriculum design; pedagogical implementation; equity, diversity, and inclusion; assessment, including longitudinal assessment across age groups; formal and informal learning approaches to CT; and teacher development. Specific topics include core competencies and CT education, robotics education and CT, AI and CT, and game-based platforms for computational problem-solving. The varying ways that CT is being integrated into the early grades, in particular, presents an interesting case study in international comparative education.