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The baffling CS notions of "as-if" and "don't-care"

Published: 10 March 2010 Publication History

Abstract

The notions of "as if" and "don't care" are essential notions in computational thinking. The former appears in the reformulation of tasks, reduction between tasks, auxiliary variables, and more. The latter is the core of non-determinism, asynchronous execution, and arbitrary choices in deterministic algorithms. The two notions are not intuitive, and require abstraction. We expect computer science (CS) graduates, who developed computational thinking during their studies, to demonstrate comprehension of these notions. Unfortunately, this may not be the case. In this paper we present a study of CS graduates, which reveals difficulties of limited comprehension and acceptance of these notions. We characterize the difficulties, relate them to cognitive aspects of abstraction, and offer some didactic suggestions.

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Dubinsky, E. 1991. Reflective abstraction in advanced mathematical thinking, in Tall, D. (Ed.) Advanced Mathematical Thinking. Kluger 95--123.
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Hazzan, O. 2003. How students attempt to reduce abstraction in the learning of mathematics and in the learning of computer science, Computer Science Education, 13(2) 95--122.
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Hopcroft, J. E., Motwani, R., & Ullman, J. D. 2001. Introduction to Automata Theory, Languages, and Computation, Addison-Wesley. 2nd Ed.
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Cited By

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  • (2024)Utilization of Information Entropy in Training and Evaluation of Students’ Abstraction Performance and Algorithm Efficiency in ProgrammingIEEE Transactions on Education10.1109/TE.2024.335429767:2(266-281)Online publication date: Apr-2024
  • (2023)From Modelling to Assessing Algorithmic Abstraction – the Missing DimensionProceedings of the 23rd Koli Calling International Conference on Computing Education Research10.1145/3631802.3631815(1-12)Online publication date: 13-Nov-2023
  • (2023)Computer Science Education Research in IsraelPast, Present and Future of Computing Education Research10.1007/978-3-031-25336-2_18(395-420)Online publication date: 18-Apr-2023
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cover image ACM Conferences
SIGCSE '10: Proceedings of the 41st ACM technical symposium on Computer science education
March 2010
618 pages
ISBN:9781450300063
DOI:10.1145/1734263
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 10 March 2010

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  1. abstraction
  2. non-determinism
  3. task reformulation

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Cited By

View all
  • (2024)Utilization of Information Entropy in Training and Evaluation of Students’ Abstraction Performance and Algorithm Efficiency in ProgrammingIEEE Transactions on Education10.1109/TE.2024.335429767:2(266-281)Online publication date: Apr-2024
  • (2023)From Modelling to Assessing Algorithmic Abstraction – the Missing DimensionProceedings of the 23rd Koli Calling International Conference on Computing Education Research10.1145/3631802.3631815(1-12)Online publication date: 13-Nov-2023
  • (2023)Computer Science Education Research in IsraelPast, Present and Future of Computing Education Research10.1007/978-3-031-25336-2_18(395-420)Online publication date: 18-Apr-2023
  • (2018)COLORFUL CHALLENGESReversingACM Inroads10.1145/32316009:3(18-19)Online publication date: 15-Aug-2018
  • (2012)Detecting and understanding students' misconceptions related to algorithms and data structuresProceedings of the 43rd ACM technical symposium on Computer Science Education10.1145/2157136.2157148(21-26)Online publication date: 29-Feb-2012

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