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TAILS: Teachers' AI Literacy Scale for language teacher education

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Evidence · 2 claims (2 for) · 1 study (1 design), q3 · 0 of 1 report an effect size · 2 claims rest on one study

Description

TAILS is a 27-item validated self-report scale developed by Salim Nabhan to assess AI literacy among preservice English language teachers.

Components

  • TAILS: Teachers' AI Literacy Scale for language teacher education: TAILS is a self-assessment questionnaire measuring language teachers' AI literacy across the six ED-AI dimensions. The initial version comprises 30 items (five per dimension) answered on a five-point Likert scale from strongly disagree to strongly agree, plus demographic items; the validated version is a refined 27-item scale. Example items include "I can collaborate with AI tools to design engaging lessons" and "I can decide when it is appropriate to use AI tools in my teaching and when not to." It is intended for diagnosing competencies, designing professional development, and guiding responsible AI integration. (Salim Nabhan (2026))

Claims

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Key Sources

  • Salim Nabhan, Anita Habók. (2026). Language teachers' AI literacy: A psychometric study based on the ED-AI framework. Computers and Education: Artificial Intelligence 10 (2026) 100583. https://doi.org/10.1016/j.caeai.2026.100583
Page metadata
Field Value
type product
id tails-teachers-ai-literacy-scale-for-language-teacher-education
title TAILS: Teachers' AI Literacy Scale for language teacher education
description TAILS is a 27-item validated self-report scale developed by Salim Nabhan to assess AI literacy among preservice English language teachers.
status review
product_kind assessment
generated by process:settle-candidates on 2026-10-12
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