AI in Education: Teacher Readiness and AI-TPACK Survey Dataset with Qualitative Coding (India, N = 208)

This dataset contains anonymised quantitative and qualitative data from a mixed-method research study on Artificial Intelligence (AI) integration in education, focusing on teacher readiness, AI-TPACK competencies, and systemic challenges. The dataset includes responses from 208 educators across India (Mumbai, Pune, Bengaluru, Rajasthan, and other regions). FILES INCLUDED: 1. Anonymised_Data.xlsx- Survey_Data: 208 participants × 28 variables- Likert-scale responses converted to numeric (0–4)- Domain scores: CK, PK, AI-TK, AI-TCK, AI-TPK, AI-TPACK- Participant_ID anonymisation (T001–T208)- No personally identifiable information (PII) - Qualitative_Responses:Verbatim responses to 5 open-ended questions linked via Participant_ID 2. Coded_Dataset.xlsx- Codebook: 10 thematic codes (deductive + inductive)- Coded_Qualitative_Data: All responses coded- Theme_Frequency: Distribution of themes (κ = 0.81)- AI_TPACK_Scores: Individual and aggregate scores- Confidence_Scores: AI confidence classification- README: Ethics, anonymisation protocol, and coding methodology RESEARCH CONTEXT:This dataset supports analysis of teacher readiness, AI adoption, pedagogical shifts, ethical concerns, and policy gaps in AI-enabled education. All data have been anonymised in compliance with GDPR and research ethics standards. This dataset is suitable for secondary research, AI in education studies, and policy analysis.