Development and Pilot Validation of an AI Integration Readiness Instrument for Tamil Language Teachers

This pilot study aimed to develop and validate a reliable instrument for assessing Tamil language teachers’ readiness to integrate Artificial Intelligence (AI) into teaching and learning. The instrument consists of five constructs—Knowledge, Skills, Attitude, Challenges, and AI Usage Level—which collectively represent key dimensions of AI integration readiness. A quantitative descriptive design was employed, involving 36 Tamil language teachers from three primary schools near Kuala Lumpur. Data were analysed using SPSS Version 29.0 for descriptive statistics and reliability testing, while SmartPLS 4 was used solely for exploratory visualisation of inter-construct patterns due to the small pilot sample size. The findings showed high mean scores for Knowledge (4.18), Skills (4.15), and Attitude (4.20), indicating strong teacher readiness, whereas the Challenges construct recorded a moderate mean (3.05), reflecting limitations in infrastructure and training. Cronbach’s Alpha values ranged from 0.810 to 0.986, with an overall reliability of 0.947, demonstrating excellent internal consistency across all constructs. Overall, the study provides a valid and psychometrically sound instrument suitable for larger-scale research examining AI readiness among teachers in vernacular school contexts.

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Publication Details

Journal
International Journal of Academic Research in Business and Social Sciences
Published
2026-01-07
DOI
https://doi.org/10.6007/ijarbss/v16-i1/27385
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

Development and Pilot Validation of an AI Integration Readiness Instrument for Tamil Language Teachers

Ravindaran Maraya, Silllalee S.Kandasamy, Partiven A/L Muniandy
International Journal of Academic Research in Business and Social Sciences
Online Learning and Analytics
article

Development and Pilot Validation of an AI Integration Readiness Instrument for Tamil Language Teachers

Ravindaran Maraya, Silllalee S.Kandasamy, Partiven A/L Muniandy
article en

Abstract

This pilot study aimed to develop and validate a reliable instrument for assessing Tamil language teachers’ readiness to integrate Artificial Intelligence (AI) into teaching and learning. The instrument consists of five constructs—Knowledge, Skills, Attitude, Challenges, and AI Usage Level—which collectively represent key dimensions of AI integration readiness. A quantitative descriptive design was employed, involving 36 Tamil language teachers from three primary schools near Kuala Lumpur. Data were analysed using SPSS Version 29.0 for descriptive statistics and reliability testing, while SmartPLS 4 was used solely for exploratory visualisation of inter-construct patterns due to the small pilot sample size. The findings showed high mean scores for Knowledge (4.18), Skills (4.15), and Attitude (4.20), indicating strong teacher readiness, whereas the Challenges construct recorded a moderate mean (3.05), reflecting limitations in infrastructure and training. Cronbach’s Alpha values ranged from 0.810 to 0.986, with an overall reliability of 0.947, demonstrating excellent internal consistency across all constructs. Overall, the study provides a valid and psychometrically sound instrument suitable for larger-scale research examining AI readiness among teachers in vernacular school contexts.

International Journal of Academic Research in Business and Social SciencesVol. 16(1)
Pedagogical University (MZ), University of Malaya (MY), Language Science (South Korea) (KR)
Openalex Percentile: Top 96%
Online Learning and Analytics
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