What question did this study set out to answer?

The aim was to adapt the Artificial Intelligence Learning Intention Scale (AILIS) and evaluate its psychometric properties among Iranian medical sciences students.

June 20, 2026Medical Education OnlineOpen Access

Cross-cultural adaptation and psychometric evaluation of the artificial intelligence learning intention scale (AILIS) among medical sciences students: a methodological study

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Authors

ATAmir Hossein Taghiparast AMAmaneh Mahmoudian MGMaryam Ghaemi‐Amiri

Discussion

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Overview

Methodological study adapts and evaluates the AILIS for Persian medical students, suggesting a reliable assessment tool.

Key Points

The aim was to adapt the Artificial Intelligence Learning Intention Scale (AILIS) and evaluate its psychometric properties among Iranian medical sciences students.
Conducted a methodological psychometric study with 800 medical sciences students at Babol University, Iran.
Employed exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to assess construct validity.
Reliability confirmed through Cronbach’s alpha, McDonald’s omega, and ICC.
EFA indicated a four-factor structure explaining 44.55% of variance, with factor loadings >0.40.
Confirmatory factor analysis showed acceptable fit (χ²/df = 3.42, RMSEA = 0.078, CFI = 0.932).
Cronbach’s alpha ranged from 0.854 to 0.904, indicating strong internal consistency.

Cite This Study

Taghiparast et al. (2026) studied this question.

synapsesocial.com/papers/6a36306fdb0793dc1a537a4a https://doi.org/10.1080/10872981.2026.2690326

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June 20, 2026Medical Education OnlineOpen Access

Cross-cultural adaptation and psychometric evaluation of the artificial intelligence learning intention scale (AILIS) among medical sciences students: a methodological study

View Full Paper

Ask AI

Bookmark

Authors

ATAmir Hossein Taghiparast AMAmaneh Mahmoudian MGMaryam Ghaemi‐Amiri

Discussion

Member takes

Overview

Methodological study adapts and evaluates the AILIS for Persian medical students, suggesting a reliable assessment tool.

Key Points

The aim was to adapt the Artificial Intelligence Learning Intention Scale (AILIS) and evaluate its psychometric properties among Iranian medical sciences students.
Conducted a methodological psychometric study with 800 medical sciences students at Babol University, Iran.
Employed exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to assess construct validity.
Reliability confirmed through Cronbach’s alpha, McDonald’s omega, and ICC.
EFA indicated a four-factor structure explaining 44.55% of variance, with factor loadings >0.40.
Confirmatory factor analysis showed acceptable fit (χ²/df = 3.42, RMSEA = 0.078, CFI = 0.932).
Cronbach’s alpha ranged from 0.854 to 0.904, indicating strong internal consistency.

Cite This Study

Taghiparast et al. (2026) studied this question.

synapsesocial.com/papers/6a36306fdb0793dc1a537a4a https://doi.org/10.1080/10872981.2026.2690326

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