Discovering Computer Science

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A01=Jessen Havill
Abstraction
Adjacency List
algorithm design methods
Algorithm efficiency
Author_Jessen Havill
Binary Search
Bit String
Boolean Expression
Category=UB
Category=UMB
Category=UMX
Category=UY
Cellular Automata
computational thinking
Computer Science
computer science principles
CSV File
data visualisation techniques
defensive programming
Elementary Steps
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Flesch Kincaid Grade Level Score
Functional Abstraction
Insertion Sort
interdisciplinary computational problem solving
interdisciplinary problems
Introduction to Computer Science
Koch Curve
Local Clustering Coefficient
Loop Condition
Merge Sort
Merge Sort Algorithm
numerical modelling
Pair Object
Pseudocode Algorithm
Python Interpreter
Python language
Python Program
Python Programming
Random Graphs
Recursive Call
Selection Sort
Small World Network
statistical data analysis
Trace Table
Turtle Graphics

Product details

  • ISBN 9780367472498
  • Weight: 1133g
  • Dimensions: 178 x 254mm
  • Publication Date: 28 Oct 2020
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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"Havill's problem-driven approach introduces algorithmic concepts in context and motivates students with a wide range of interests and backgrounds."


-- Janet Davis

, Associate Professor and Microsoft Chair of Computer Science, Whitman College

"This book looks really great and takes exactly the approach I think should be used for a CS 1 course. I think it really fills a need in the textbook landscape."


--

Marie desJardins, Dean of the College of Organizational, Computational, and Information Sciences, Simmons University

"Discovering Computer Science is a refreshing departure from introductory programming texts, offering students a much more sincere introduction to the breadth and complexity of this ever-growing field."


--

James Deverick, Senior Lecturer, The College of William and Mary

"This unique introduction to the science of computing guides students through broad and universal approaches to problem solving in a variety of contexts and their ultimate implementation as computer programs."


--

Daniel Kaplan, DeWitt Wallace Professor, Macalester College

Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming

is a problem-oriented introduction to computational problem solving and programming in Python, appropriate for a first course for computer science majors, a more targeted disciplinary computing course or, at a slower pace, any introductory computer science course for a general audience.

Realizing that an organization around language features only resonates with a narrow audience, this textbook instead connects programming to students’ prior interests using a range of authentic problems from the natural and social sciences and the digital humanities. The presentation begins with an introduction to the problem-solving process, contextualizing programming as an essential component. Then, as the book progresses, each chapter guides students through solutions to increasingly complex problems, using a spiral approach to introduce Python language features.

The text also places programming in the context of fundamental computer science principles, such as abstraction, efficiency, testing, and algorithmic techniques, offering glimpses of topics that are traditionally put off until later courses.

This book contains 30 well-developed independent projects that encourage students to explore questions across disciplinary boundaries, over 750 homework exercises, and 300 integrated reflection questions engage students in problem solving and active reading.

The accompanying website — https://www.discoveringcs.net — includes more advanced content, solutions to selected exercises, sample code and data files, and pointers for further exploration.

Jessen Havill is a Professor of Computer Science at Denison University. He has been teaching courses across the computer science curriculum for almost thirty years, and was awarded the College's highest teaching honor, the Charles A. Brickman Teaching Excellence Award, in 2013. Although his primary expertise is in the development and analysis of online algorithms, Dr. Havill has spent many years collaborating with colleagues across the curriculum to develop interdisciplinary academic opportunities for students. From 2016-2019, he became the founding Director of Denison University's interdisciplinary Data Analytics program. Dr. Havill earned his bachelor's degree from Bucknell University and his Ph.D. in computer science from The College of William and Mary.

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