Computational Thinking in Science
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Authors
Denning, Peter J.
Subjects
Computers
Design
Biology
Automation
Algorithms
Neural networks
Scientists
Computer science
Mathematical models
Simulation
Power
Designers
Nobel prizes
Methods
Design
Biology
Automation
Algorithms
Neural networks
Scientists
Computer science
Mathematical models
Simulation
Power
Designers
Nobel prizes
Methods
Advisors
Date of Issue
2017
Date
Jan/Feb 2017
Publisher
Sigma XI-The Scientific Research Society
Language
Abstract
A quiet but profound revolution has been taking place throughout science. The computing revolution has
transformed science by enabling all sorts of new discoveries through information technology. Throughout most of
the history of science and technology, there have been two types of characters. One is the experimenter, who
gathers data to reveal when a hypothesis works and when it does not. The other is the theoretician, who designs
mathematical models to explain what is already known and uses the models to make predictions about what is not
known. The two types interact with one another because hypotheses may come from models, and what is known
comes from previous models and data. The experimenter and the theoretician were active in the sciences well
before computers came on the scene. Computational thinking is generally defined as the mental skills that
facilitate the design of automated processes.
Type
Article
Description
Series/Report No
Department
Computer Science (CS)
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
7 p.
Citation
Denning, Peter J. "Computational thinking in science." American Scientist 105.1 (2017): 13-17.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.