Development of Artificial Intelligence-Assisted Learning Satisfaction Scale: Validity and Reliability Study

Abstract

This research is targeted upon tracing the satisfaction levels of the students in universities with AI-assisted learning experiences besides to create a measurement tool, which is valid and reliable in this respect. The work on the Scale tool of the survey, designed to be developed in two stages, was executed in the academic year 2024–2025 and the number of the participants was 640 university students who said they had used different AI applications. After a thorough literature review, students’ focus group interviews involving AI, and the discussions with experts in the academic field, the scale items were decided upon. The data were subjected to an Exploratory Factor Analysis (EFA) for the first sample group (n = 259), and it was revealed that the scale had one-factor nature. The results of EFA indicated that the 12-item draft scale covered 68.6% of the variance. A Confirmatory Factor Analysis (CFA) carried out on the data from the second sample group (n = 381) attests that the 12 items and the single-factor structure offered good fit indices. Later still, the second-level CFA aligned with this structure’s validity. The Cronbach alpha internal consistency coefficient of the scale was reported as.96 and reliability was very high. The results demonstrate that the 12-item Learning Assistance with AI Satisfaction questionnaire is a valid and reliable measurement tool. The scale in question gives a strong foundation to researchers and practitioners to find out the satisfaction levels of students with the AI-assisted learning experiences and to make educational policies accordingly. © 2026 Taylor & Francis Group, LLC.