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Dual Process Theories: Computing Cognition in Context

Published: 15 September 2022 Publication History

Abstract

This paper explores a major theoretical framework from psychology, Dual Process Theory (DPT), which has received surprisingly little attention in the computing education literature. DPT postulates the existence of two qualitatively different kinds of cognitive systems, a fast, intuitive “System 1” and a slow, reflective “System 2”. System 1 is associated with cognitive factors such as crystallized intelligence, long-term memory and associative learning; System 2 with fluid intelligence, working memory, and rule learning. This paper summarizes DPT and the way it has been expressed and explored in literatures relating to intelligence, memory, learning, attention, cognitive load, and more. It proposes a summary model, the Dual Process Cycle (DPC). It then considers example concepts from computing education within the context of this model. Examples include programming expertise, mental models of programs, the notional machine, code reading and code writing, and the theory of Learning Edge Momentum (LEM). In conclusion, it is argued that the DPC (and the framework of DPTs in general) provides a useful context for defining such concepts more richly and exactly, and for generating interesting questions about them.

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cover image ACM Transactions on Computing Education
ACM Transactions on Computing Education  Volume 22, Issue 4
December 2022
384 pages
EISSN:1946-6226
DOI:10.1145/3561990
  • Editor:
  • Amy J. Ko
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 September 2022
Online AM: 28 March 2022
Revised: 15 November 2021
Accepted: 16 September 2021
Received: 15 January 2021
Published in TOCE Volume 22, Issue 4

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  1. Dual process theories
  2. Dual Process Cycle
  3. computing cognition
  4. Psychology of programming

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  • (2023)10 Things Software Developers Should Learn about LearningCommunications of the ACM10.1145/358485967:1(78-87)Online publication date: 21-Dec-2023
  • (2023)Design friction in autonomous drive—exploring transitions between autonomous and manual drive in non-urgent situationsPersonal and Ubiquitous Computing10.1007/s00779-023-01780-727:6(2291-2305)Online publication date: 27-Nov-2023

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