Karl Beecher - Computational Thinking: A Beginner’s Guide to Problem-Solving and Programming

BCS Learning & Development Ltd 2017

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Paperback ISBN: 978-1-78017-36-41

PDF ISBN-13: 978-1-78017-36-58

EPUB ISBN-13: 978-1-78017-36-65

Kindle ISBN-13: 978-1-78017-36-72

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A must-read for students embarking on their first major projects, and any teacher stepping up to the challenge of teaching Computing at school. This is not just a book about programming, more a template for teaching. Karl Beecher speaks in plain English. Incisive insight and practical advice, standing independent of the Python exemplars used, predicated as it is on a holistic understanding of the subject terrain.

Roger Davies, Director of IT, Queen Elizabeth School, and Editor,
Computing At School, Tenderfoot Training Project

I really enjoyed this book - it bridges the gap between the very practical, but perhaps narrow, field of computer programming with the real world problems that computer scientists might need to solve. The issue with encouraging young people to learn coding is that they often struggle to understand how and when to use specific concepts and ideas. The underlying principles and real world applications are essential, and much harder to put across, than remembering the syntax for an IF statement. The discussions are presented in a readable format that would be suitable for bright GCSE students and should be essential reading for all A Level computer scientists.

With the shift in focus at GCSE and A Level alike, from programming to computational thinking, explanations and examples of abstraction, decomposition and generalisation, along with modelling, logic and efficiency are both engaging and useful.

Mark Clarkson, Subject Leader and CAS Master Teacher

Computational Thinkingis a sprint through the theoretical underpinnings of computation through to their application and the creation of software. The thirteen chapters start with an explanation of what is computational thinking, move through logical and algorithmic thinking, abstraction and modelling, to then focus on how to apply these concepts. The middle set of chapters cover how to create software with a focus on object-oriented solutions with a relatively short discussion on testing. Python is used as the programming language to demonstrate the use of the various techniques introduced in the early chapters but it would be straight forward to convert the examples to other similar languages such as Java, C#, etc. The final chapter provides a guided example based on the creation of a computer-controlled home automation system. Each chapter has a set of exercises to work through and model answers for these are supplied in an appendix.

This is a very good overview of a very large field. While all of the topics are deserving of their own book the strength of this book is the explanation and demonstration of their close relationships.