A comparison of programming languages and algebraic notation as expressive languages for physics

Bruce L. Sherin*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

68 Scopus citations

Abstract

The purpose of the present work is to consider some of the implications of replacing, for the purposes of physics instruction, algebraic notation with a programming language. What is novel is that, more than previous work, I take seriously the possibility that a programming language can function as the principle representational system for physics instruction. This means treating programming as potentially having a similar status and performing a similar function to algebraic notation in physics learning. In order to address the implications of replacing the usual notational system with programming, I begin with two informal conjectures: (1) Programming-based representations might be easier for students to understand than equation-based representations, and (2) programming-based representations might privilege a somewhat different "intuitive vocabulary." If the second conjecture is correct, it means that the nature of the understanding associated with programming-physics might be fundamentally different than the understanding associated with algebra-physics. In order to refine and address these conjectures, I introduce a framework based around two theoretical constructs, what I call interpretive devices and symbolic forms. A conclusion of this work is that algebra-physics can be characterized as a physics of balance and equilibrium, and programming-physics as a physics of processes and causation. More generally, this work provides a theoretical and empirical basis for understanding how the use of particular symbol systems affects students' conceptualization.

Original languageEnglish (US)
Pages (from-to)1-61
Number of pages61
JournalInternational Journal of Computers for Mathematical Learning
Volume6
Issue number1
DOIs
StatePublished - 2001

Keywords

  • Algebra
  • Cognition
  • Physics
  • Programming
  • Representations

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Engineering(all)
  • Computer Science Applications
  • Computational Theory and Mathematics

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