Article

Self-efficacy and mental models in learning to program

Authors:

Vennila Ramalingam,

Deborah LaBelle,

Susan WiedenbeckAuthors Info & Claims

ITiCSE '04: Proceedings of the 9th annual SIGCSE conference on Innovation and technology in computer science education

Pages 171 - 175

https://doi.org/10.1145/1007996.1008042

Published: 28 June 2004 Publication History

Abstract

Learning to program is a unique experience for each student, and it is not fully understood why one person in an introductory programming course learns to program better and more quickly than the next. Self-efficacy is an individual's judgment of his or her ability to perform a task within a specific domain [1]. A mental model is a person's internal (mental) representation of real world objects and systems [9]. Research has shown that high self-efficacy and a good mental model are important to knowledge acquisition and transfer. This research investigates the effects of students' self-efficacy and mental models of programming on learning to program. The results show that self-efficacy for programming is influenced by previous programming experience and increases as a student progresses through an introductory programming course. The results also show that the student's mental model of programming influences self-efficacy and that both the mental model and self-efficacy affect course performance.

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Cited By

Figueiredo EFonseca CPaiva T(2024)Self-efficacy and academic performance in higher education: a case studyAutoeficacia y rendimiento académico en educación superior: un caso de estudioEuropean Public & Social Innovation Review10.31637/epsir-2024-9609(1-16)Online publication date: 4-Nov-2024
https://doi.org/10.31637/epsir-2024-960
Q. Cowit NBarker L(2024)Designing for Interdisciplinary Transfer to Reduce Intrinsic Cognitive Load, Increase Self-Efficacy, and Promote Conceptual Understanding in Introductory ProgrammingProceedings of the 24th Koli Calling International Conference on Computing Education Research10.1145/3699538.3699553(1-13)Online publication date: 12-Nov-2024
https://dl.acm.org/doi/10.1145/3699538.3699553
Gilbert CMcDonald BScott M(2024)Exploring the Relationship between Debugging Self-Efficacy and CASE Tools for Novice TroubleshootingProceedings of the 2024 Conference on United Kingdom & Ireland Computing Education Research10.1145/3689535.3689556(1-7)Online publication date: 5-Sep-2024
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Index Terms

Self-efficacy and mental models in learning to program
1. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Computing education programs
        Computer science education

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cover image ACM Conferences

ITiCSE '04: Proceedings of the 9th annual SIGCSE conference on Innovation and technology in computer science education

June 2004

296 pages

ISBN:1581138369

DOI:10.1145/1007996

Conference Chair:
Roger Boyle
University of Leeds, UK
,
Program Chairs:
Martyn Clark
University of Leeds, UK
,
Amruth Kumar
Ramapo College of NJ

ACM SIGCSE Bulletin Volume 36, Issue 3
September 2004
280 pages
ISSN:0097-8418
DOI:10.1145/1026487
Issue’s Table of Contents

Copyright © 2004 ACM.

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: 28 June 2004

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June 28 - 30, 2004

Leeds, United Kingdom

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Cited By

Figueiredo EFonseca CPaiva T(2024)Self-efficacy and academic performance in higher education: a case studyAutoeficacia y rendimiento académico en educación superior: un caso de estudioEuropean Public & Social Innovation Review10.31637/epsir-2024-9609(1-16)Online publication date: 4-Nov-2024
https://doi.org/10.31637/epsir-2024-960
Q. Cowit NBarker L(2024)Designing for Interdisciplinary Transfer to Reduce Intrinsic Cognitive Load, Increase Self-Efficacy, and Promote Conceptual Understanding in Introductory ProgrammingProceedings of the 24th Koli Calling International Conference on Computing Education Research10.1145/3699538.3699553(1-13)Online publication date: 12-Nov-2024
https://dl.acm.org/doi/10.1145/3699538.3699553
Gilbert CMcDonald BScott M(2024)Exploring the Relationship between Debugging Self-Efficacy and CASE Tools for Novice TroubleshootingProceedings of the 2024 Conference on United Kingdom & Ireland Computing Education Research10.1145/3689535.3689556(1-7)Online publication date: 5-Sep-2024
https://dl.acm.org/doi/10.1145/3689535.3689556
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