Artificial intelligence and academic writing questionnaire (AI-AWQ): development and validation among medical students’ experiences using exploratory factor analysis

Abstract

INTRODUCTION: This study aimed to develop and validate the Artificial Intelligence and Academic Writing Questionnaire (AI-AWQ) to assess participants' perceptions with AI. The primary focus was to explore the factors that influence attitudes toward AI in educational settings. METHODS: This study utilized a mixed-methods approach to develop and validate the psychometric properties of the AI-AWQ. The questionnaire, consisting of 30 items rated on a 5-point Likert scale (1 = Never, 5 = Always), was administered to a sample of 252 medical and dental students at Shiraz University of Medical Sciences, Iran, who had taken the academic writing course during the 2023-2024 academic year. Data were analyzed using Exploratory Factor Analysis (EFA), with Varimax rotation employed to clarify the underlying factors. RESULTS: A total of 252 completed questionnaires were analyzed, of which 59.5% were from Iranian students and the remaining respondents were international students. The results of the exploratory factor analysis demonstrated satisfactory sampling adequacy (KMO = 0.930) and a significant Bartlett's test of sphericity (P < 0.001), confirming the suitability of the data for factor analysis. Construct validity testing led to the extraction of five distinct factors-Perceived Effectiveness of AI, Ethical and Authenticity Concerns, AI-Supported Writing Process, AI Feedback and Writing Enhancement, and Affective and Motivational Impact-which together accounted for 77.99% of the total variance. The questionnaire demonstrated strong validity and reliability, with a Content Validity Index (CVI) of 0.903, a Content Validity Ratio (CVR) of 0.882, and an overall internal consistency confirmed by a Cronbach's alpha of 0.883. CONCLUSION: The findings suggest that the AI-AWQ provides preliminary evidence of reliability and validity for measuring perceptions of AI, offering insights into the multi-faceted nature of AI and academic writing. This study contributes to understanding the factors shaping individuals' views on AI in educational contexts and provides a foundation for further research.

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