Evaluating English Teachers’ Artificial Intelligence Readiness and Training Needs with a TPACK-Based Model

With the rapid development and widespread adoption of artificial intelligence (AI) tools, the implementation of instructional pedagogy has transformed significantly. English teachers need to understand how AI tools can improve their teaching and must acquire the necessary technical and pedagogical knowledge to effectively utilize AI technology. Although the integration of AI into language teaching shows potential benefits, there remains a dearth of comprehensive research on English teachers’ perceptions, readiness, and professional development requirements in relation to AI.To address these knowledge research gaps, our study aims to evaluate English teachers’ current understanding of AI tools and their training needs for integrating AI into the English language classroom. Our proposed model uses the technological pedagogical content knowledge (TPACK) framework, which incorporates English language teaching and information literacy contexts. This framework allows for a holistic assessment of teachers’ readiness for integrating AI within English language teaching practices.A study was conducted with a class of preservice English teachers in Hong Kong. An online survey was designed to assess the readiness of English teachers for applying AI tools in the classroom as well as their understanding and level of information literacy. This study helped identify and address potential issues with the survey before launching it to a wider audience. Our findings confirmed the validity and reliability of the instrument and indicated that preservice English teacher participants are generally prepared to integrate AI tools into the English classroom. Corelation analysis was also conducted to assess the relationships among the constructs and showed that technological pedagogical knowledge (TPK) and instructional literacy (IL) were significant predictors of the overall TPACK construct. The study suggested professional training in the selection, implementation and progress monitoring of specific AI tools for English Language teaching; pedagogy design; and the ability to search for appropriate resources for the English classroom. The framework can be enhanced by using a mixed-method approach and incorporating a qualitative study to triangulate the findings. An explanatory sequential design will be recommended to collect quantitative data first, then qualitative data will be collected for further analysis.

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Publication Details

Journal
World Journal of English Language
Published
2024-08-30
DOI
https://doi.org/10.5430/wjel.v15n1p129
Citations
11
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
4.53
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article

Evaluating English Teachers’ Artificial Intelligence Readiness and Training Needs with a TPACK-Based Model

Kevin Kai-Wing Chan, William Ko-Wai Tang
11 citations
World Journal of English Language
Online Learning and Analytics
4.53
article

Evaluating English Teachers’ Artificial Intelligence Readiness and Training Needs with a TPACK-Based Model

Kevin Kai-Wing Chan, William Ko-Wai Tang
article en
11 citations

Abstract

With the rapid development and widespread adoption of artificial intelligence (AI) tools, the implementation of instructional pedagogy has transformed significantly. English teachers need to understand how AI tools can improve their teaching and must acquire the necessary technical and pedagogical knowledge to effectively utilize AI technology. Although the integration of AI into language teaching shows potential benefits, there remains a dearth of comprehensive research on English teachers’ perceptions, readiness, and professional development requirements in relation to AI.To address these knowledge research gaps, our study aims to evaluate English teachers’ current understanding of AI tools and their training needs for integrating AI into the English language classroom. Our proposed model uses the technological pedagogical content knowledge (TPACK) framework, which incorporates English language teaching and information literacy contexts. This framework allows for a holistic assessment of teachers’ readiness for integrating AI within English language teaching practices.A study was conducted with a class of preservice English teachers in Hong Kong. An online survey was designed to assess the readiness of English teachers for applying AI tools in the classroom as well as their understanding and level of information literacy. This study helped identify and address potential issues with the survey before launching it to a wider audience. Our findings confirmed the validity and reliability of the instrument and indicated that preservice English teacher participants are generally prepared to integrate AI tools into the English classroom. Corelation analysis was also conducted to assess the relationships among the constructs and showed that technological pedagogical knowledge (TPK) and instructional literacy (IL) were significant predictors of the overall TPACK construct. The study suggested professional training in the selection, implementation and progress monitoring of specific AI tools for English Language teaching; pedagogy design; and the ability to search for appropriate resources for the English classroom. The framework can be enhanced by using a mixed-method approach and incorporating a qualitative study to triangulate the findings. An explanatory sequential design will be recommended to collect quantitative data first, then qualitative data will be collected for further analysis.

World Journal of English LanguageVol. 15(1)
City University of Hong Kong (HK)
Quality Education
Openalex Percentile: Top 5%
Online Learning and Analytics
4.53
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