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Exploring Clusters of Novice Programmers' Anxiety-Induced Behaviors during Block- and Text-Based Coding: A Predictive and Moderation Analysis of Programming Quality and Error Debugging Skills

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Title: Exploring Clusters of Novice Programmers' Anxiety-Induced Behaviors during Block- and Text-Based Coding: A Predictive and Moderation Analysis of Programming Quality and Error Debugging Skills
Language: English
Authors: Abdullahi Yusuf (ORCID 0000-0003-2487-0564), Amiru Yusuf Muhammad
Source: Journal of Educational Computing Research. 2024 62(7):1798-1836.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 39
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Novices, Programming, Anxiety, Coding, Troubleshooting, Predictor Variables, Physiology, Measurement Equipment, Markov Processes, Algorithms, Psychological Patterns, Self Control
DOI: 10.1177/07356331241270707
ISSN: 0735-6331
1541-4140
Abstract: The study investigates the potential of anxiety clusters in predicting programming performance in two distinct coding environments. Participants comprised 83 second-year programming students who were randomly assigned to either a block-based or a text-based group. Anxiety-induced behaviors were assessed using physiological measures (Apple Watch and Electrocardiogram machine), behavioral observation, and self-report. Utilizing the Hidden Markov Model and Optimal Matching algorithm, we found three representative clusters in each group. In the block-based group, clusters were designated as follows: "stay calm" (students allocating more of their time to a calm state), "stay hesitant" (students allocating more of their time to a hesitant state), and "to-calm" (those allocating minimal time to a hesitant and anxious state but displaying a pronounced propensity to transition to a calm state). In contrast, clusters in the text-based group were labeled as: "to-hesitant" (exhibiting a higher propensity to transition to a hesitant state), "stay hesitant" (allocating significant time to a hesitant state), and "stay anxious" (remaining persistently anxious in a majority of the coding time). Additionally, our results indicate that novice programmers are more likely to experience anxiety during text-based coding. We discussed the findings and highlighted the policy implications of the study.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1443793
Database: ERIC
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  Data: Exploring Clusters of Novice Programmers' Anxiety-Induced Behaviors during Block- and Text-Based Coding: A Predictive and Moderation Analysis of Programming Quality and Error Debugging Skills
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  Data: <searchLink fieldCode="AR" term="%22Abdullahi+Yusuf%22">Abdullahi Yusuf</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2487-0564">0000-0003-2487-0564</externalLink>)<br /><searchLink fieldCode="AR" term="%22Amiru+Yusuf+Muhammad%22">Amiru Yusuf Muhammad</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Educational+Computing+Research%22"><i>Journal of Educational Computing Research</i></searchLink>. 2024 62(7):1798-1836.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: The study investigates the potential of anxiety clusters in predicting programming performance in two distinct coding environments. Participants comprised 83 second-year programming students who were randomly assigned to either a block-based or a text-based group. Anxiety-induced behaviors were assessed using physiological measures (Apple Watch and Electrocardiogram machine), behavioral observation, and self-report. Utilizing the Hidden Markov Model and Optimal Matching algorithm, we found three representative clusters in each group. In the block-based group, clusters were designated as follows: "stay calm" (students allocating more of their time to a calm state), "stay hesitant" (students allocating more of their time to a hesitant state), and "to-calm" (those allocating minimal time to a hesitant and anxious state but displaying a pronounced propensity to transition to a calm state). In contrast, clusters in the text-based group were labeled as: "to-hesitant" (exhibiting a higher propensity to transition to a hesitant state), "stay hesitant" (allocating significant time to a hesitant state), and "stay anxious" (remaining persistently anxious in a majority of the coding time). Additionally, our results indicate that novice programmers are more likely to experience anxiety during text-based coding. We discussed the findings and highlighted the policy implications of the study.
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        Value: 10.1177/07356331241270707
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      – Text: English
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      Pagination:
        PageCount: 39
        StartPage: 1798
    Subjects:
      – SubjectFull: Novices
        Type: general
      – SubjectFull: Programming
        Type: general
      – SubjectFull: Anxiety
        Type: general
      – SubjectFull: Coding
        Type: general
      – SubjectFull: Troubleshooting
        Type: general
      – SubjectFull: Predictor Variables
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      – SubjectFull: Physiology
        Type: general
      – SubjectFull: Measurement Equipment
        Type: general
      – SubjectFull: Markov Processes
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Psychological Patterns
        Type: general
      – SubjectFull: Self Control
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      – TitleFull: Exploring Clusters of Novice Programmers' Anxiety-Induced Behaviors during Block- and Text-Based Coding: A Predictive and Moderation Analysis of Programming Quality and Error Debugging Skills
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            NameFull: Amiru Yusuf Muhammad
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