Computational Thinking

The MIT Press Essential Knowledge

by Peter J. Denning, Matti Tedre

An introduction to computational thinking that traces a genealogy beginning centuries before the digital computer.

A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation; eventually, every field had a computational branch: computational physics, computational biology, computational sociology. More recently, "computational thinking" has become part of the K-12 curriculum. But what is computational thinking? This volume in the MIT Press Essential Knowledge series offers an accessible overview, tracing a genealogy that begins centuries before digital computers and portraying computational thinking as pioneers of computing have described it.

The authors explain that computational thinking (CT) is not a set of concepts for programming; it is a way of thinking that is honed through practice: the mental skills for designing computations to do jobs for us, and for explaining and interpreting the world as a complex of information processes. Mathematically trained experts (known as "computers") who performed complex calculations as teams engaged in CT long before electronic computers. The authors identify six dimensions of today's highly developed CT--methods, machines, computing education, software engineering, computational science, and design--and cover each in a chapter. Along the way, they debunk inflated claims for CT and computation while making clear the power of CT in all its complexity and multiplicity.

Genres: Computer Science, Science, Technology, Philosophy, Computers, Nonfiction, Audiobook

246 pages, Paperback

First published January 1, 2019

About the author

Peter J. Denning is Distinguished Professor of Computer Science at the Naval Postgraduate School, Monterey, California. He is the coauthor of The Innovator's Way: Essential Practices for Successful Innovation and Great Principles of Computing, both published by the MIT Press.

Reviews

[chsmiley · Rating 4 out of 5]

Overall, I liked this book. I have a background in Computer Science and the Computational Sciences so I was familiar with a lot of the concepts in the book, but had never read about the history and theoretical underpinnings of the CT movement from a big picture perspective. The book confirmed some of my thinking about the way that computer science education is often divorced from design thinking as well as the domain knowledge needed in particular specialties.

The section on machine learning seemed to skip right to neural nets to the exclusion of other approaches which felt lacking to me since the book was more comprehensive in other sections. I also agreed with another reviewer's critique that the book was light on ethical concerns in computational thinking. This is especially true as it relates to the danger of promoting ethnic, gender, and other stereotypes using black box models like neural nets. Other than that, the book felt well-considered and worth reading if you have an interest in CT.

[Sam · Rating 4 out of 5]

I picked this book nearly randomly from the bookshelf in the library, and I'm quite satisfied with this choice. The authors talk about important things, about which I also was thinking from time to time, but wasn't able to find sources to satisfy my interest. Now I know, that it was all about computational thinking. Spoiler: this is not just the ability to solve problems like a programmer.

For me it seemed weird, when some smart people talked about the possibility, that we live in a computer simulation. Like, I literally imagined that they claim that there is extremely big and powerfull computer somewhere, which simulates our world (here come The Matrix references). Well, maybe some people really believe in this. However, in the context of computational thinking it makes sence:

"Everything we think and everything we think, is computed by natural process. Instead of using computation to understand nature, they say, we will eventually accept that everything in nature is computation."

In this sence, the statement that our universe is simulated is just a peculiar worldview. Especially, taking into account that scientists regard many processes as computational e.g. DNA transcription, brain and chemical processes etc.

Well, I don't like, when people compare brain to computers. However, the rise of such claims is "understandable as a continuation of the ongoing quest to understand the world through the latest available technology". Maybe, I don't have the neccessary flexibility of thinking, but when I hear, the comparisson "brain = computer", I think about it as some fundamental postulate, which I don't like. Now I see, that that this is also the way to explain nature. Below is the citation, which I like, and I also met with this thought previously, but cannot remmember, where:

"For instance, in the Age of Enlightment, the world was compared to the clockwork. The brain has successively been compared to the mill, the telegraph system, hydraulic systems, electromagnetic systems, and the computer."

And as the pretendent for the next stage in this progression, the authors propose quantum computers. They don't develop this thought further, maybe because quantum computers now are only theoretical entities, however, I would like to read about interpretation of brain as quantum computer. Maybe, this will even allow to better understand not only brain, as hardware, but also mind, as software.

In general, authors describe many interesting and, to my mind, fundamental things about teaching computational thinking. The main point here is that institutes of education should be very agile, in order to provide the most modern and actual knowledge. This is obvious, but also this is not, what you are usually thinking about.

[Héctor Iván Patricio Moreno · Rating 5 out of 5]

Una introducción bastante completa, entretenida y pensada para las personas que no saben nada de Pensamiento Computacional o sólo han escuchado mencionarlo por todos lados, sin entender bien a qué se refiere.

Escrito por los encargados de recomendar temarios a las escuelas sobre lo que deberían enseñar en este tema, miembros de la ACM, es un libro que toca ampliamente a todo lo que nos podemos referir con el término además de la historia y la evolución.

Si nunca recibiste educación de esto, lo recomiendo mucho. Si eres un doctor en Pensamiento computacional o ciencias computacionales, probablemente tenga poco qué aportarte.

Otra cosa que me gustó es que es una fuente de referencias para educarte mucho más sobre el tema y que presenta los temas de manera muy muy sencilla, tanto que es posible tomar estas explicaciones para usarlas en clases o explicaciones a otras personas.

Pequeño Resumen:
- El pensamiento computacional es más antiguo que las computadoras automáticas.
- Las computadoras automáticas eran un sueño de los científicos desde mucho antes que existieran, sobre todo de los físicos y matemáticos.
- La computación nació como una rama de las matemáticas pero ha divergido tanto que no se puede decir que siguen siendo matemáticas.
- El modelo computacional es muy importante y es la base para el pensamiento computacional de la época.
- La arquitectura Von Neumann ha definido lo que entendemos como un programa o algoritmo, pero hay muchas formas de pensarlo.
- Parece que el pensamiento computacional no es tan transferible a otros medios, no es una meta-habilidad
- La computación tiene límites que es imposible sobrepasar. De ahí la pregunta ¿Qué es computable?
- El pensamiento actual de que el mundo es una simulación o una computadora es un pensamiento natural pero probablemente erróneo: casi siempre los humanos comparamos el mundo con nuestro último invento que nos ha cambiado la vida.
- La ciencia ha desarrollado su propio tipo de pensamiento computacional
- La computación no puede estar separada de otras áreas para que sea útil y debe aprender mucho del dominio en el que es aplicada.

[Darian · Rating 3 out of 5]

Pretty straightforward intro to CT that covers its history in great depth. I appreciated the way the author(s) describe the field and its importance as a set of conceptual frameworks, rather than a defined programming-based or CS-driven mindset.

Main issue with the book is its lack of addressing ethical concerns of modern technology and efforts to improve education in this realm. Any CT book published in 2019 should be dedicating a whole chapter to this, not a mere three pages toward the end.

[David Schwan · Rating 3 out of 5]

An overview of the history of computational thinking, plus a discussion and history of the teaching of computational thinking, the latter I found detracted from the book a bit. The author tries to argue that the skills required to implement computational thinking transfer well to other disciplines and at times seems to better argue against himself. Computational thinking does little to nothing to help one establish the reliability of the input data and hence while important, computational thinking needs to be supplemented by other areas.

[Garry Cotton · Rating 4 out of 5]

Interesting, thought provoking, approachable and paints a vivid picture of where virtually any work in computational fields is heading.

Starts off with an overview of low-level computational thinking, in other words the breaking down of problems into small, logical steps and problem space reduction. Finally, how the reduced problem can be formatted in a way that solution by computation is possible.

Discusses von Neumann architecture and how it drives the process of computational thinking. Computational efficiency is then tackled, the process of optimization and its impact, particularly in large software systems processing huge streams of data.

Dips into design and architecture as an increasingly important component of software construction and a computational thinker's skillset.

Finally, illustrates how the entire computational thinking paradigm will likely shift with the advent of quantum computing.

The book does labour a little in the mid-section, losing some of its initial and closing fervour, but the content and ideas presented make it a great read.

[Ashley Barratt · Rating 4 out of 5]

This book is an excellent primer for those wanting to know more about how Computational Thinking affects our lives.

AI, Machine Learning and Big Data Analytics are the equivalent of today’s gold rush - how can we make sense of the opportunity and the potential threat.

As a person would has invested a professional lifetime working in Tech - and who believes that empowering the wisdom of Youth is essential - the big question left at the end of the book contains an interesting challenge:

‘ ... how shall we shape computing education so that our graduates can develop the design sensibilities, wisdom, and caring they will need to navigate in this world, of which they will be citizens? Our current curriculum ... is not up to this task’

Recommended

[Abdullah Shams · Rating 3 out of 5]

This book covers quite a lot. Most dominating point of view taken by the writer is on history of Computational thinking.

In my view history is important, but for that it should have been named history of computational thinking.

The main idea of computational thinking even though connected to its history, grounding it in history misguides its progress. Hidden in the spread of the book, there is a glimpse of the realization on humans parts, that at most our reality is computable to such an extent that you can rely on these computation with your life. Its this form of reliability that enables further progress for the hidden goal to free human conscious for the ultimate realization.

[Teo · Rating 4 out of 5]

2019.08.04–2019.08.05

Contents

Denning PJ & Tedre M (2019) (05:56) Computational Thinking

Series Foreword
Preface
Acknowledgments

1. What Is Computational Thinking?
2. Computational Methods
3. Computing Machines
4. Computer Science
5. Software Engineering
6. Designing for Humans
7. Computational Science
8. Teaching Computational Thinking for All
9. Future Computation

Epilogue: Lessons Learned

Glossary
Notes
References and Further Reading
Index

[Weltengeist · Rating 3 out of 5]

The term "computational thinking" has a number of different meanings, depending on who you ask. Most people (and most books on the topic) would agree to the "modern" interpretation that computational thinking is about what the average (i.e., non computer scientist) person should know about algorithms, modelling etc. in order to be a better problem solver and to be better at understanding the world around us.

There is, however, another group that interprets "computational thinking" to be about everything, absolutely everything that has anything to do with computers or the way computer professionals and scientists work and think (or used to work or used to think). Personally, I find this extremely broad definition quite useless, but it has its adherents. And you may not be surprised to hear that the authors are amongst them.

For this reason, most of this book reads more like "a brief history of computer science" than like what you would expect if you had the Wikipedia definition of computational thinking in mind when you bought it.

Not surprisingly, I found the last two chapters (dealing with the "modern" definition of computational thinking and with its future) to be the most useful ones, as they were what I was expecting the whole book to be about. As for most of the rest, I simply don't get who the target audience is - people with an IT background already know most of that, and people without will probably not understand them, as they discuss a lot of ambitious concepts on very few pages and without any illustrations.

Summing up, 2 1/2 stars, rounding up. I was hoping for something else.

[Zain Aman · Rating 2 out of 5]

It's an intriguing misnomer. I picked it from the library expecting to get a general overview of the methods and principles of computational thinking. I approached this book with high expectations of clarity and foundational insight into a subject so pivotal to modern problem-solving. What I found instead was an extensive historical account of computational sciences.

While the book did a pretty good job on the inception, evolution and dynamism of computational thinking and its paradigm shifts (in the late 60s and afterwards), it didn't miss to give me a feeling of the subject of inquiry being left alone, as it was just mostly the history of the subject, and not the subject of matter the book pivots towards a narrative of its historical development. It covers the evolution of computational sciences, its pioneers, and the intellectual journey that brought computational thinking into academic and professional discourse. While the author did a pretty good job at this, it is not what the title promises.

It is rewarding for anyone who approaches this book with an appreciation for history and an interest in the evolution of core and essential ideas.
Many might pick up this book seeking a roadmap to mastering computational thinking, only to find themselves navigating an anthology of its milestones.

[Frobisher Smith · Rating 3 out of 5]

Interesting introduction to Computational Thinking, which is neither simply "thinking about computers," nor is it "thinking like a computer." The definition used in this book is, to paraphrase, thinking about how to solve problems with the assistance of a computer. This relates across the board for computer engineering, programming, and fields such as Computational Biology, even including the more esoteric fields like Computational Linguistics. This basic little intro is helpful for learning exactly what the issues are and where the conceptual world of "CT" is headed. It was very down to earth for a book about computing, and perhaps it would be better with a little more abstract digressions into topics like algorithm design, and digital poetics. It was very informative, especially with regards to the history of computing and the concepts involved in scientific modelling with computers. Not all of the MIT essential knowledge books are dry, but this one is pretty dry, all things considered.

[Andra Popovici · Rating 4 out of 5]

Overall, a good introduction to the history of how computing has evolved over time and how it impacts other fields. It also touches on some future considerations about the applicability of the computational thinking in various domains and how beneficial would it be to have more critical thinking tasks included in the scholar curriculums. I would have liked though to have more examples of how algorithmic thinking work and explain more with actual algorithms how they are used to solve problems around the world.

[George · Rating 5 out of 5]

Very much what it says on the cover - this is a great introduction to Computational Thinking. It provides a good overview on the topic, building on early conceptions of CT and how these ideas have changed over time. It delves into various fields and how they have responded to/ignored/eventually acknowledged this developing area. For something that is about 200 pages, it does well to cover so much. A good read.

[Eavan · Rating 2 out of 5]

I read this to try and understand the computer/data portion of MLIS. It’s a perfectly sized introduction that unfortunately is relying on the reader to know a bit more background knowledge than I have. I spent the past 4 and a half years studying some mad humanities, can you blame me? Luckily my roommate knows computers quite well so he answers any questions I have in the meantime. Interested in reading this series’ Metadata book at least, and not against trying others either.

[Sarah · Rating 4 out of 5]

I liked the comprehensiveness of this book given its length, and I think it did a good job of connecting some seemingly disparate computing concepts and dimensions, at least for a layman like me. I also enjoyed the way historical context was emphasized when the development of computational thinking over the past few thousand years was covered. Overall this was a useful read.

[Peter Aronson · Rating 3 out of 5]

Three and a half stars. An OK, if a bit dry, history of computational thinking. Maybe I'd find it more informative if I didn't have a degree in Computer and Information Science, and hadn't worked in the field for 40+ years, but I found little new. In particularly, it didn't seem to go into any depth about what actually made up computational thinking, which admittedly would be a difficult topic.

[Barry C · Rating 5 out of 5]

Professor Denning has written a comprehensive overview of computational thinking as it applies to many fields. Computational thinking should be taught at the elementary school level (it's not programming).

[Cas LeMaster · Rating 3 out of 5]

Comprehensive. Accurate. Boring.

It is essentially a review on the rise and refining of the computational sciences. I had anticipated more of an algorithmic approach to problem solving and software-based examples but instead got an introductory course to the role of CT in science and engineering.

[Gustavo · Rating 4 out of 5]

This book made me fall in love again with my profession, which needs of computational thinking at every step. Too simple for an experienced software engineer, but interesting for people who are curious about the computer revolution.

[Samuel Smith · Rating 4 out of 5]

Enjoyed this book. Good historical, philosophical, and topical introduction to the subject with an exploration of how computational engineering can change the world for the better. It made me even more grateful for the opportunity to pursue mastery of this subject.

[Daniel · Rating 4 out of 5]

It was a very difficult read for me. It was a good introduction in understanding the way in which programmers have to use a different way of thinking know as computational thinking in order to succeed in their field.

[Kico Meirelles · Rating 3 out of 5]

This is an ok book, no more than this. Perhaps I had the wrong expectation that the book would bring CT concepts and how to develop this mindset and approach. However the book is more about the history of CT and the relevance and progress of its educational adoption.

[Joseph Kreydt · Rating 3 out of 5]

This book is more a survey of the landscape of computing more than anything. It covers the surface level of computational thinking, but that's it. How We Use Computers might be a more fitting title for this book. Nonetheless, it was an interesting read.

[Jimmacc · Rating 4 out of 5]

I learned a lot from this book. I also picked up several topics to research further. The history portion(s) was excellent.

I was particularly interested in the education tops addressed in this book… how to teach the processes of abstraction and computation in a way that is relevant.

[tanvee · Rating 4 out of 5]

"A computing pioneer who worked with one of the first computers wrote in his
memoir that he still remembered the day when he suddenly realized he would be
spending most of the rest of his life looking for mistakes in his own programs.''

[Sabina · Rating 4 out of 5]

Great non-technical introduction to Computational Thinking(CT). The authors from MIT insist that CT should be part of a school curriculum like Maths and English.

[Matthias Noch · Rating 4 out of 5]

Not bad, very detailed, but a bit too much tailored to starters.

[Naynay · Rating 5 out of 5]

would you give me this book ? I need it for my research

[Mohamed Ahmed Aboushama · Rating 5 out of 5]

Great but not enough