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 |
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| Language: | English |
| Authors: | Abdullahi Yusuf (ORCID |
| 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 |
| 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. |
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| ISSN: | 0735-6331 1541-4140 |
| DOI: | 10.1177/07356331241270707 |
