m+Medelevator.RU
← Поиск публикаций
Scientific reports · 2026

Development and validation of the teachers generative AI professional competence scale.

СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Aldighrir Wafa Mohammed

Аннотация

Generative artificial intelligence is rapidly reshaping teachers' professional practices, creating new demands for judgment, responsibility, and autonomy in educational decision-making. However, existing measurement tools largely focus on AI literacy, attitudes, or general readiness, leaving a critical gap in assessing how teachers engage with generative AI in professionally meaningful and ethically responsible ways. This study addresses this gap by developing and validating the Teachers' Generative AI Professional Competence Scale, conceptualized as a multidimensional construct comprising pedagogical judgment, ethical leadership, and professional agency. A sequential exploratory mixed-method design was employed, beginning with construct specification, literature synthesis, item generation, expert validation, and cognitive pretesting. The scale was then administered to a sample of 648 teachers in Saudi Arabia. Data were randomly split for exploratory and confirmatory factor analyses. Results supported a stable three-factor structure with strong item loadings and satisfactory explained variance. Confirmatory factor analysis demonstrated excellent model fit and substantially better fit than the one-factor model over alternative factor structures. Reliability and validity evidence, including internal consistency, composite reliability, and average variance extracted, indicated strong psychometric properties. Multigroup CFA supported configural and loading invariance across the gender groups examined; scalar and strict invariance could not be evaluated conclusively from the retained output. In addition, exploratory graph analysis recovered a three-community solution consistent with the factor-analytic structure and demonstrated high structural stability. Overall, the findings provide promising initial evidence for the validity and reliability of the proposed scale for assessing teachers' professional competence in the context of generative AI. The scale provides a valuable tool for future research, teacher education, and policy development aimed at supporting responsible and human-centered integration of AI in education.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты