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<p>This study aimed to assess teachers’ AI-Specific TPACK and attitudes toward AI, and to examine their associations with prior technology experience and demographic characteristics. Guided by the TPACK framework and the Technology Acceptance Model, a cross-sectional survey was conducted with 725 teachers from Surakarta, Indonesia. Data were collected via a validated online questionnaire comprising 29 AI-Specific TPACK items and 12 Attitude Toward AI items, both demonstrating strong construct validity and high internal reliability. Descriptive statistics, Pearson correlations, t-tests, and ANOVA were used for analysis. Findings revealed high AI-Specific TPACK, particularly in technological knowledge, alongside positive attitudes toward AI’s usefulness and integration, though ethical and dependency concerns persisted. Prior technology used significantly predicted both higher TPACK and more favorable attitudes, while demographic differences were limited. These results underscore the importance of targeted professional development that addresses pedagogical integration, ethical considerations, and equitable access, informing educational policy and capacity-building initiatives in AI integration.</p>

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Assessing Teachers’ Readiness for AI Integration: Insights from AI-Specific TPACK and Attitudes Toward AI

  • 期刊论文

  • 发表日期：

    2026年3月4日

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  • Sudi Dul Aji,
  • Nurul Ain,
  • Akhmad Zaini,
  • Muhammad Nur Hudha,
  • Kadek Dwi Hendratma Gunawan,
  • Hestiningtyas Yuli Pratiwi,
  • Andi Wahyudi

摘要

This study aimed to assess teachers’ AI-Specific TPACK and attitudes toward AI, and to examine their associations with prior technology experience and demographic characteristics. Guided by the TPACK framework and the Technology Acceptance Model, a cross-sectional survey was conducted with 725 teachers from Surakarta, Indonesia. Data were collected via a validated online questionnaire comprising 29 AI-Specific TPACK items and 12 Attitude Toward AI items, both demonstrating strong construct validity and high internal reliability. Descriptive statistics, Pearson correlations, t-tests, and ANOVA were used for analysis. Findings revealed high AI-Specific TPACK, particularly in technological knowledge, alongside positive attitudes toward AI’s usefulness and integration, though ethical and dependency concerns persisted. Prior technology used significantly predicted both higher TPACK and more favorable attitudes, while demographic differences were limited. These results underscore the importance of targeted professional development that addresses pedagogical integration, ethical considerations, and equitable access, informing educational policy and capacity-building initiatives in AI integration.