Writing Prompts to Identify At-Risk Students in Introductory Programming Courses.
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| Title: | Writing Prompts to Identify At-Risk Students in Introductory Programming Courses. |
|---|---|
| Authors: | Clark, Jon D.1 jon.clark@colostate.edu, Kinnett, Seth J.1 seth.kinnett@colostate.edu |
| Source: | Information Systems Education Journal. May2026, Vol. 24 Issue 3, p4-15. 12p. |
| Subject Terms: | *Readability formulas, *Computer programming education, *Student assignments, *Educational intervention, *Students, *Educational evaluation, Maintainability (Engineering) |
| Abstract: | The identification of at-risk students early in introductory programming courses is critical to their success. Timely intervention requires assessment before substantial code has been written, and good and bad habits are formed. This study asserts that the use of natural language writing prompts can be used as a diagnostic tool, based on the SOLO taxonomy of cognitive development. The relationship between natural language metrics (Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning FOG Index) and code maintainability (McCabe’s Essential Complexity) by 29 novice student programmers completing a Java assignment was evaluated. Statistical results show significant differences in all three natural language metrics between students who produced maintainable and unmaintainable code, with the strongest predictability demonstrated by the FOG Index (FOG Index: p=.086, CI90= [-3.4, -.20]). These results were interpreted through the SOLO taxonomy, suggesting that students performing at the Multistructural level produce both disconnected writing (high complexity scores) and unstructured code (high essential complexity), while students performing at the Relational level produce coherent structures in both domains. Further, this study provides implementation guidelines for instructors to manage writing prompts, interpret results, and design impactful interventions, resulting in a low-cost, scalable approach for early student assessment. [ABSTRACT FROM AUTHOR] |
| Copyright of Information Systems Education Journal is the property of Information Systems & Computing Academic Professionals (ISCAP) 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: | Education Research Complete |
| FullText | Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 192831157 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Writing Prompts to Identify At-Risk Students in Introductory Programming Courses. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Clark%2C+Jon+D%2E%22">Clark, Jon D.</searchLink><relatesTo>1</relatesTo><i> jon.clark@colostate.edu</i><br /><searchLink fieldCode="AR" term="%22Kinnett%2C+Seth+J%2E%22">Kinnett, Seth J.</searchLink><relatesTo>1</relatesTo><i> seth.kinnett@colostate.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Information+Systems+Education+Journal%22">Information Systems Education Journal</searchLink>. May2026, Vol. 24 Issue 3, p4-15. 12p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Readability+formulas%22">Readability formulas</searchLink><br />*<searchLink fieldCode="DE" term="%22Computer+programming+education%22">Computer programming education</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+assignments%22">Student assignments</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+intervention%22">Educational intervention</searchLink><br />*<searchLink fieldCode="DE" term="%22Students%22">Students</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+evaluation%22">Educational evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Maintainability+%28Engineering%29%22">Maintainability (Engineering)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The identification of at-risk students early in introductory programming courses is critical to their success. Timely intervention requires assessment before substantial code has been written, and good and bad habits are formed. This study asserts that the use of natural language writing prompts can be used as a diagnostic tool, based on the SOLO taxonomy of cognitive development. The relationship between natural language metrics (Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning FOG Index) and code maintainability (McCabe’s Essential Complexity) by 29 novice student programmers completing a Java assignment was evaluated. Statistical results show significant differences in all three natural language metrics between students who produced maintainable and unmaintainable code, with the strongest predictability demonstrated by the FOG Index (FOG Index: p=.086, CI90= [-3.4, -.20]). These results were interpreted through the SOLO taxonomy, suggesting that students performing at the Multistructural level produce both disconnected writing (high complexity scores) and unstructured code (high essential complexity), while students performing at the Relational level produce coherent structures in both domains. Further, this study provides implementation guidelines for instructors to manage writing prompts, interpret results, and design impactful interventions, resulting in a low-cost, scalable approach for early student assessment. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Information Systems Education Journal is the property of Information Systems & Computing Academic Professionals (ISCAP) 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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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.62273/RRRD8805 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 4 Subjects: – SubjectFull: Readability formulas Type: general – SubjectFull: Computer programming education Type: general – SubjectFull: Student assignments Type: general – SubjectFull: Educational intervention Type: general – SubjectFull: Students Type: general – SubjectFull: Educational evaluation Type: general – SubjectFull: Maintainability (Engineering) Type: general Titles: – TitleFull: Writing Prompts to Identify At-Risk Students in Introductory Programming Courses. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Clark, Jon D. – PersonEntity: Name: NameFull: Kinnett, Seth J. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 1545679X Numbering: – Type: volume Value: 24 – Type: issue Value: 3 Titles: – TitleFull: Information Systems Education Journal Type: main |
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