دانلود کتاب تفکر رایانشی: بازاندیشی در شیوه تفکر ما

When I first read Jeannette Wing’s influential essay “Computational Thinking” published in 2006, I immediately recognized its importance. I wholeheartedly agreed with her assertion that computational thinking (CT) should be a fundamental component of university education for all disciplines, and that students majoring in computer science would be equipped to excel in a wide range of careers beyond their technical training. I translated Wing’s essay into Japanese, and it was published in the Journal of the Information Processing Society of Japan in 2015. However, when Prof. Michael Vallance, our colleague at Future University Hakodate (hereafter referred to as FUN), used my translation as the teaching material, he found that students struggled to understand it. Wing’s essay includes many technical terms from computer science but offers few concrete examples—particularly ones that demonstrate how such concepts apply to other fields. While the essay was written for educators, it is not structured to help beginners grasp the essence of computational thinking. This observation led us at FUN to launch a project aimed at publishing a book filled with accessible and practical examples of CT. It was not easy to find examples that made sense to people outside of computer science. We each tried various approaches and held frequent discussions. Eventually, we compiled our findings into the desired book in Japanese, which translates Wing’s abstract ideas into concrete terms that are easier to understand for non-specialists. At the same time, international interest in teaching computational thinking was gaining momentum, with new academic societies and initiatives being launched. In Japan, however, government agencies such as the Ministry of Education had interpreted CT to mean programming and began to incorporate it into elementary school curricula. Even national media outlets like NHK produced TV programs based on this interpretation. Needless to say, programming knowledge and skills, along with the ability to effectively utilize modern AI technology, are certainly part of CT, but CT encompasses much more. This English edition is based on the Japanese edition published by FUN Press in 2022. Chapters 1, 2, 4 and 5 of that Japanese edition have been revised to a diverse extent. This English edition was unable to include Chap. 3, authored by Michael Vallance. For his research, please see his paper titled “Computational thinking and interdisciplinary learning: time to focus on pedagogy” published in 2020. The structure of this book is designed to be progressive, starting with an introduction to fundamental concepts in computer science, moving through methods for understanding computational thinking, and culminating in its practical application. However, it has been consciously written so that readers can begin reading from any chapter. This book begins in Chap. 1 by serving as a primer for readers unfamiliar with computer science, defining computational thinking as “thinking like a computer scientist.” The chapter explains the origins of computer science and its unique worldview by contrasting it with fields like physics and mathematics, while also addressing its relationship with programming, deep learning, and generative AI. Chapter 2 delves into the practical benefits of applying computational thinking in the real world. It introduces three of four essential concepts—abstraction, modeling, and virtualization— which are presented as fundamental operations for generating new information. The chapter uses relatable examples to make these terms accessible and concludes by connecting computational thinking to the principles of information design. Chapter 3 introduces the fourth essential concept, meta, and its related idea of self-reference. Acknowledging the complexity of the topic, the chapter explains how to think about an object and concept from a higher perspective, using real world examples to clarify how to apply this thinking both in human activities and within a computer. Chapter 4 is an essay in which a computer scientist and education scholar shares her personal journey, explaining how her childhood experiences cultivated a computational mindset. She uses the unique analogy of cooking to explain computational thinking, breaking down a recipe into a series of logical steps, and discusses how this perspective can be taught effectively to children. Finally, in Chap. 5 , a cognitive scientist with no background in computer science reports on her personal struggle to understand computational thinking. She shares her initial discomfort and the turning point that allowed her to grasp the concept, concluding with a non-specialist’s unique discovery of computational thinking’s altruistic power.