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AI-Generated Errors as a Learning Tool: Improving Programming Education through Error Correction

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Title: AI-Generated Errors as a Learning Tool: Improving Programming Education through Error Correction
Language: English
Authors: Spartak Sakibayev, Bela Sakibayeva, Darkhan Toybazarov
Source: Journal of Educators Online. 2026 23(1).
Availability: Journal of Educators Online. Grand Canyon University, 23300 West Camelback Road, Phoenix, AZ 85017. e-mail: CIRT@gcu.edu. Web site: https://www.thejeo.com
Peer Reviewed: Y
Page Count: 12
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Programming, Error Patterns, Error Correction, Coding, Instructional Effectiveness, Extracurricular Activities, College Students, Foreign Countries, Grades (Scholastic)
Geographic Terms: Kazakhstan
ISSN: 1547-500X
Abstract: This study examines the utilization of AI-generated errors in programming education, with a focus on students' ability to identify and correct errors intentionally introduced into AI-generated code. The primary objective is to evaluate the effectiveness of this approach in enhancing students' programming competence and academic performance. Participants engaged with AI-generated code containing predefined errors, and their error detection and correction skills were assessed. The findings indicate that this method supports the development of programming proficiency and contributes to improved academic outcomes. This study adds to the existing literature on AI in education, providing a basis for future research on integrating AI tools into programming instruction.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1499130
Database: ERIC
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  Data: AI-Generated Errors as a Learning Tool: Improving Programming Education through Error Correction
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  Data: <searchLink fieldCode="AR" term="%22Spartak+Sakibayev%22">Spartak Sakibayev</searchLink><br /><searchLink fieldCode="AR" term="%22Bela+Sakibayeva%22">Bela Sakibayeva</searchLink><br /><searchLink fieldCode="AR" term="%22Darkhan+Toybazarov%22">Darkhan Toybazarov</searchLink>
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  Data: Journal of Educators Online. Grand Canyon University, 23300 West Camelback Road, Phoenix, AZ 85017. e-mail: CIRT@gcu.edu. Web site: https://www.thejeo.com
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  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Programming%22">Programming</searchLink><br /><searchLink fieldCode="DE" term="%22Error+Patterns%22">Error Patterns</searchLink><br /><searchLink fieldCode="DE" term="%22Error+Correction%22">Error Correction</searchLink><br /><searchLink fieldCode="DE" term="%22Coding%22">Coding</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Effectiveness%22">Instructional Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Extracurricular+Activities%22">Extracurricular Activities</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Grades+%28Scholastic%29%22">Grades (Scholastic)</searchLink>
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  Label: Abstract
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  Data: This study examines the utilization of AI-generated errors in programming education, with a focus on students' ability to identify and correct errors intentionally introduced into AI-generated code. The primary objective is to evaluate the effectiveness of this approach in enhancing students' programming competence and academic performance. Participants engaged with AI-generated code containing predefined errors, and their error detection and correction skills were assessed. The findings indicate that this method supports the development of programming proficiency and contributes to improved academic outcomes. This study adds to the existing literature on AI in education, providing a basis for future research on integrating AI tools into programming instruction.
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    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Programming
        Type: general
      – SubjectFull: Error Patterns
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      – SubjectFull: Error Correction
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      – SubjectFull: Coding
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      – SubjectFull: Instructional Effectiveness
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      – SubjectFull: College Students
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      – SubjectFull: Foreign Countries
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      – SubjectFull: Grades (Scholastic)
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      – SubjectFull: Kazakhstan
        Type: general
    Titles:
      – TitleFull: AI-Generated Errors as a Learning Tool: Improving Programming Education through Error Correction
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            NameFull: Spartak Sakibayev
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            NameFull: Bela Sakibayeva
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            NameFull: Darkhan Toybazarov
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              Y: 2026
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