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What Drives Coding Adoption in Mathematics Teacher Education? Insights from an Extended UTAUT Model

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Title: What Drives Coding Adoption in Mathematics Teacher Education? Insights from an Extended UTAUT Model
Language: English
Authors: Zeynep Gül Dertli (ORCID 0000-0002-4750-5343), Nezihe Korkmaz (ORCID 0000-0002-1284-0483), Elif Boran (ORCID 0009-0001-9187-1463), Sena Uludağ (ORCID 0009-0005-1549-8723), Bahadır Yıldız (ORCID 0000-0003-4816-3071)
Source: International Journal of Education in Mathematics, Science and Technology. 2026 14(2):369-391.
Availability: International Journal of Education in Mathematics, Science and Technology. Necmettin Erbakan University, Ahmet Kelesoglu Education Faculty, Meram, Konya, 42090, Turkey. e-mail: ijermst@gmail.com; Web site: https://www.ijemst.net/index.php/ijemst/index
Peer Reviewed: Y
Page Count: 23
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Coding, Mathematics Teachers, Preservice Teachers, Student Attitudes, Intention, Foreign Countries, Mathematics Education, Universities, Self Efficacy, Student Motivation, Social Influences, Student Behavior
Geographic Terms: Turkey
ISSN: 2147-611X
Abstract: This study investigates the factors influencing pre-service mathematics teachers' intentions to integrate coding into their instructional practices, using the Unified Theory of Acceptance and Use of Technology (UTAUT) as its theoretical foundation. While coding is widely recognized as a crucial digital competency, its effective integration into mathematics education depends on various motivational and contextual variables. The study was conducted with 334 pre-service mathematics teachers from seven universities in Turkey. Data were collected using the Coding Usage Intention Scale, developed based on the UTAUT model and extended with additional variables: self-efficacy, perceived learning opportunities, and hedonic motivation. Structural Equation Modeling (SEM) was employed to test the proposed model. The results revealed that hedonic motivation was the most significant predictor of coding intention (β = 0.646, p < 0.001). Other significant predictors included performance expectancy, social influence, self-efficacy, and perceived learning opportunities. In contrast, effort expectancy and facilitating conditions did not have statistically significant effects. The overall model demonstrated good fit indices, supporting the validity of the proposed framework. These findings highlight the importance of both cognitive and affective factors in shaping pre-service teachers' willingness to adopt coding in education. The study offers theoretical and practical implications for teacher education programs, suggesting that increasing enjoyment, competence, and pedagogical awareness around coding may enhance its adoption in mathematics instruction.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1506059
Database: ERIC
FullText Text:
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  Data: What Drives Coding Adoption in Mathematics Teacher Education? Insights from an Extended UTAUT Model
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  Data: This study investigates the factors influencing pre-service mathematics teachers&#39; intentions to integrate coding into their instructional practices, using the Unified Theory of Acceptance and Use of Technology (UTAUT) as its theoretical foundation. While coding is widely recognized as a crucial digital competency, its effective integration into mathematics education depends on various motivational and contextual variables. The study was conducted with 334 pre-service mathematics teachers from seven universities in Turkey. Data were collected using the Coding Usage Intention Scale, developed based on the UTAUT model and extended with additional variables: self-efficacy, perceived learning opportunities, and hedonic motivation. Structural Equation Modeling (SEM) was employed to test the proposed model. The results revealed that hedonic motivation was the most significant predictor of coding intention (β = 0.646, p &lt; 0.001). Other significant predictors included performance expectancy, social influence, self-efficacy, and perceived learning opportunities. In contrast, effort expectancy and facilitating conditions did not have statistically significant effects. The overall model demonstrated good fit indices, supporting the validity of the proposed framework. These findings highlight the importance of both cognitive and affective factors in shaping pre-service teachers&#39; willingness to adopt coding in education. The study offers theoretical and practical implications for teacher education programs, suggesting that increasing enjoyment, competence, and pedagogical awareness around coding may enhance its adoption in mathematics instruction.
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  Data: 2026
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  Data: EJ1506059
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1506059
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 23
        StartPage: 369
    Subjects:
      – SubjectFull: Coding
        Type: general
      – SubjectFull: Mathematics Teachers
        Type: general
      – SubjectFull: Preservice Teachers
        Type: general
      – SubjectFull: Student Attitudes
        Type: general
      – SubjectFull: Intention
        Type: general
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Mathematics Education
        Type: general
      – SubjectFull: Universities
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      – SubjectFull: Self Efficacy
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      – SubjectFull: Student Motivation
        Type: general
      – SubjectFull: Social Influences
        Type: general
      – SubjectFull: Student Behavior
        Type: general
      – SubjectFull: Turkey
        Type: general
    Titles:
      – TitleFull: What Drives Coding Adoption in Mathematics Teacher Education? Insights from an Extended UTAUT Model
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              Y: 2026
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              Value: 14
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            – TitleFull: International Journal of Education in Mathematics, Science and Technology
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