Artificial intelligence and academic writing questionnaire (AI-AWQ): development and validation among medical...

Area of Science:

• Educational Technology
• Psychometrics
• Artificial Intelligence

Background:

• The integration of Artificial Intelligence (AI) into academic settings necessitates tools to evaluate user perceptions.
• Understanding student attitudes towards AI is crucial for effective implementation in educational contexts.

Purpose of the Study:

• To develop and validate the Artificial Intelligence and Academic Writing Questionnaire (AI-AWQ).
• To assess participants' perceptions of AI and explore factors influencing attitudes toward AI in educational settings.

Main Methods:

• A mixed-methods approach was used to develop and validate the AI-AWQ.
• The 30-item questionnaire was administered to 252 medical and dental students using a 5-point Likert scale.
• Exploratory Factor Analysis (EFA) with Varimax rotation was employed for data analysis.

Main Results:

• Exploratory Factor Analysis identified five key factors: Perceived Effectiveness of AI, Ethical and Authenticity Concerns, AI-Supported Writing Process, AI Feedback and Writing Enhancement, and Affective and Motivational Impact.
• These factors explained 77.99% of the total variance.
• The AI-AWQ demonstrated strong validity (CVI=0.903, CVR=0.882) and reliability (Cronbach's alpha=0.883).

Conclusions:

• The AI-AWQ is a reliable and valid instrument for measuring perceptions of AI in academic writing.
• The findings offer insights into the complex relationship between AI and academic writing, informing future research and educational strategies.