Developing and validating the scale of language teachers’ computational thinking competency in Computer Assisted Language Learning (LTCCTCALL): Empowering language teaching by cultivating the heart of the 21st-century digital skill

In recognition of the integration of Information and Communications Technology (ICTs) along with Artificial Intelligence (AI) into education, several educational organizations have recommended cultivating 21st-century digital skills as part of every educational curriculum. The computational thinking skill, which is at the core of 21st-century digital skills, has gained research in several fields, such as physics and psychology (Barkela et al., 2024). However, applied linguistics and computer-assisted language learning (CALL) have overlooked this crucial skill, which might stem from the lack of language teachers’ computational thinking competency. For this reason, in the present study the researchers developed a new theoretical framework, and it’s corresponding scale specifically designed for applied linguistics and CALL, namely the Language Teachers’ Computational Thinking Competency in Computer Assisted Language Learning (LTCCTCALL). Using deductive and inductive methods, the researchers developed the items, followed by a validation process that used the Rasch-Andrich rating scale model (RSM) to assess the scale’s item difficulty and validity using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). LTCCTCALL was validated with five factor structures that included 15 items in the Iranian EFL context, involving 273 Iranian in-service language teachers. Based on this result, the study introduced a new theoretical framework and its scale to the fields of CALL, applied linguistics, and the Common European Framework of Reference for Languages (CEFR) to lead the community’s continued growth and to prevent the community from falling behind other fields that incorporate computational thinking skills into our classrooms to have problem-solving approaches with CALL, AI, and chatbots in language class.

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Publication Details

Journal
Asian-Pacific Journal of Second and Foreign Language Education
Published
2025-10-12
DOI
https://doi.org/10.1186/s40862-025-00353-w
Primary Topic
Teaching and Learning Programming
Type
article
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article

Developing and validating the scale of language teachers’ computational thinking competency in Computer Assisted Language Learning (LTCCTCALL): Empowering language teaching by cultivating the heart of the 21st-century digital skill

Babak Daneshvar Ghorbani, Amir Reza Rahimi
Asian-Pacific Journal of Second and Foreign Language Education
Teaching and Learning Programming
article

Developing and validating the scale of language teachers’ computational thinking competency in Computer Assisted Language Learning (LTCCTCALL): Empowering language teaching by cultivating the heart of the 21st-century digital skill

Babak Daneshvar Ghorbani, Amir Reza Rahimi
article en

Abstract

In recognition of the integration of Information and Communications Technology (ICTs) along with Artificial Intelligence (AI) into education, several educational organizations have recommended cultivating 21st-century digital skills as part of every educational curriculum. The computational thinking skill, which is at the core of 21st-century digital skills, has gained research in several fields, such as physics and psychology (Barkela et al., 2024). However, applied linguistics and computer-assisted language learning (CALL) have overlooked this crucial skill, which might stem from the lack of language teachers’ computational thinking competency. For this reason, in the present study the researchers developed a new theoretical framework, and it’s corresponding scale specifically designed for applied linguistics and CALL, namely the Language Teachers’ Computational Thinking Competency in Computer Assisted Language Learning (LTCCTCALL). Using deductive and inductive methods, the researchers developed the items, followed by a validation process that used the Rasch-Andrich rating scale model (RSM) to assess the scale’s item difficulty and validity using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). LTCCTCALL was validated with five factor structures that included 15 items in the Iranian EFL context, involving 273 Iranian in-service language teachers. Based on this result, the study introduced a new theoretical framework and its scale to the fields of CALL, applied linguistics, and the Common European Framework of Reference for Languages (CEFR) to lead the community’s continued growth and to prevent the community from falling behind other fields that incorporate computational thinking skills into our classrooms to have problem-solving approaches with CALL, AI, and chatbots in language class.

Asian-Pacific Journal of Second and Foreign Language EducationVol. 10(1)
Universitat de València (ES), Iran University of Science and Technology (IR)
Openalex Percentile: Top 68%
Teaching and Learning Programming
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