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Exploring the Link Between Problem-Solving Strategies and Programming Performance: A Comparative Analysis of High and Low Performers.

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Title: Exploring the Link Between Problem-Solving Strategies and Programming Performance: A Comparative Analysis of High and Low Performers.
Authors: Huang, Sora Chi-Fang1 (AUTHOR) 81008001e@ntnu.edu.tw, Chen, Zhi-Hong1,2 (AUTHOR), Lin, Yu-Tzu1,2 (AUTHOR), Yeh, Martin K.3 (AUTHOR), Chen, Yi-Wei1 (AUTHOR)
Source: Journal of Educational Computing Research. Mar2026, Vol. 64 Issue 2, p493-523. 31p.
Subjects: Problem solving, Visual programming (Computer science), Eye tracking, Students, Computer programming education, Self-regulated learning
Abstract: Although studies have investigated how students' problem-solving strategies influence their performance, few explore the comparison between high and low performers. Moreover, there is a lack of empirical evidence on the effect of students' problem-solving strategies on their performance in visual programming systems. To address this research gap, we developed a visual programming system based on the self-regulated learning model, providing top-down and bottom-up perspectives. We recruited 35 university students to use the visual programming system and collected eye movement data to analyze their problem-solving strategies. Finally, 19 students' data with the weighted gaze sampling rate exceeding 80% were used to ensure robust data reliability. The results revealed: (1) a positive correlation between performance and visits to the top-down tracking window, and a negative correlation with the bottom-up window; and (2) both high and low performers used both strategies, but high performers favored the top-down approach. The findings suggest that to better support low performers, the visual programming system should provide guidance on applying the top-down strategy for problem-solving. The implications of this study highlight the importance of problem-solving strategies in programming and suggest that incorporating visual scaffolding for the top-down approach may help low performers narrow the gap with high performers. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Educational Computing Research is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 191254706
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PubType: Academic Journal
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  Data: Exploring the Link Between Problem-Solving Strategies and Programming Performance: A Comparative Analysis of High and Low Performers.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Educational+Computing+Research%22">Journal of Educational Computing Research</searchLink>. Mar2026, Vol. 64 Issue 2, p493-523. 31p.
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  Data: <searchLink fieldCode="DE" term="%22Problem+solving%22">Problem solving</searchLink><br /><searchLink fieldCode="DE" term="%22Visual+programming+%28Computer+science%29%22">Visual programming (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Eye+tracking%22">Eye tracking</searchLink><br /><searchLink fieldCode="DE" term="%22Students%22">Students</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+programming+education%22">Computer programming education</searchLink><br /><searchLink fieldCode="DE" term="%22Self-regulated+learning%22">Self-regulated learning</searchLink>
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  Data: Although studies have investigated how students' problem-solving strategies influence their performance, few explore the comparison between high and low performers. Moreover, there is a lack of empirical evidence on the effect of students' problem-solving strategies on their performance in visual programming systems. To address this research gap, we developed a visual programming system based on the self-regulated learning model, providing top-down and bottom-up perspectives. We recruited 35 university students to use the visual programming system and collected eye movement data to analyze their problem-solving strategies. Finally, 19 students' data with the weighted gaze sampling rate exceeding 80% were used to ensure robust data reliability. The results revealed: (1) a positive correlation between performance and visits to the top-down tracking window, and a negative correlation with the bottom-up window; and (2) both high and low performers used both strategies, but high performers favored the top-down approach. The findings suggest that to better support low performers, the visual programming system should provide guidance on applying the top-down strategy for problem-solving. The implications of this study highlight the importance of problem-solving strategies in programming and suggest that incorporating visual scaffolding for the top-down approach may help low performers narrow the gap with high performers. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Educational Computing Research is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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      – SubjectFull: Eye tracking
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              Text: Mar2026
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