research-article

Measuring the Cognitive Load of Learning to Program: A Replication Study

Authors:

Albina Zavgorodniaia,

Juha SorvaAuthors Info & Claims

UKICER '20: United Kingdom & Ireland Computing Education Research conference.

Pages 3 - 9

https://doi.org/10.1145/3416465.3416468

Published: 03 September 2020 Publication History

Abstract

Cognitive load (CL) on a learner’s working memory has emerged as an influential concept in computing education and beyond. CL is commonly divided in at least two components, intrinsic load (IL) and extraneous load (EL). We seek progress on two questions: (1) How can CL components be measured in the programming domain? (2) How should CL measurement deal with the “third component” of germane load (GL)? We replicate two studies: Morrison and colleagues’ [49] evaluation of a questionnaire for self-assessing CL in programming, which is an adaptation of a generic instrument; and Jiang and Kalyuga’s [24] study, which found support for a two-component measure of CL in language learning, with GL redundant. We crowd-sourced CL data using Morrison’s questions at the end of a video tutorial on programming for beginners. A confirmatory factor analysis found strong support for a three-factor model, with factors matching the items intended to capture IL, EL, and GL, respectively. A two-factor model with IL-targeting and GL-targeting items combined gave a poorer fit. Our findings strengthen the claims of discriminant validity and internal reliability for Morrison’s CL questionnaire for programming; construct validity for GL remains open, however. We affirm the need for further research on the two-component theory of CL and the sensitivity of CL self-assessments to contextual factors.

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Cited By

Thorgeirsson SZhang CWeidmann TWeidmann KSu Z(2024)An Electroencephalography Study on Cognitive Load in Visual and Textual ProgrammingProceedings of the 2024 ACM Conference on International Computing Education Research - Volume 110.1145/3632620.3671124(280-292)Online publication date: 12-Aug-2024
https://dl.acm.org/doi/10.1145/3632620.3671124
Meier JHesse PAbele SRenkl AGlogger‐Frey I(2024) Video‐based modeling examples and comparative self‐explanation prompts for teaching a complex problem‐solving strategy Journal of Computer Assisted Learning10.1111/jcal.1299140:4(1852-1870)Online publication date: 23-Apr-2024
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Pesonen HLeinonen JHaaranen LHellas A(2023)Exploring the Interplay of Achievement Goals, Self-Efficacy, Prior Experience and Course AchievementProceedings of the 2023 Conference on United Kingdom & Ireland Computing Education Research10.1145/3610969.3611178(1-7)Online publication date: 7-Sep-2023
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cover image ACM Other conferences

UKICER '20: United Kingdom & Ireland Computing Education Research conference.

September 2020

75 pages

ISBN:9781450388498

DOI:10.1145/3416465

Editors:
Joseph Maguire
University of Glasgow
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Quintin Cutts
University of Glasgow

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Cited By

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https://dl.acm.org/doi/10.1145/3632620.3671124
Meier JHesse PAbele SRenkl AGlogger‐Frey I(2024) Video‐based modeling examples and comparative self‐explanation prompts for teaching a complex problem‐solving strategy Journal of Computer Assisted Learning10.1111/jcal.1299140:4(1852-1870)Online publication date: 23-Apr-2024
https://doi.org/10.1111/jcal.12991
Pesonen HLeinonen JHaaranen LHellas A(2023)Exploring the Interplay of Achievement Goals, Self-Efficacy, Prior Experience and Course AchievementProceedings of the 2023 Conference on United Kingdom & Ireland Computing Education Research10.1145/3610969.3611178(1-7)Online publication date: 7-Sep-2023
https://dl.acm.org/doi/10.1145/3610969.3611178
Haynes-Magyar CEricson B(2022)The Impact of Solving Adaptive Parsons Problems with Common and Uncommon SolutionsProceedings of the 22nd Koli Calling International Conference on Computing Education Research10.1145/3564721.3564736(1-14)Online publication date: 17-Nov-2022
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Duran RZavgorodniaia ASorva J(2022)Cognitive Load Theory in Computing Education Research: A ReviewACM Transactions on Computing Education10.1145/348384322:4(1-27)Online publication date: 15-Sep-2022
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Haynes CEricson BKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)Problem-Solving Efficiency and Cognitive Load for Adaptive Parsons Problems vs. Writing the Equivalent CodeProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445292(1-15)Online publication date: 6-May-2021
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Zavgorodniaia AHellas ASeppälä OSorva J(2020)Should Explanations of Program Code Use Audio, Text, or Both? A Replication StudyProceedings of the 20th Koli Calling International Conference on Computing Education Research10.1145/3428029.3428050(1-10)Online publication date: 19-Nov-2020
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