Development and validation of the student readiness and anxiety scale for AI-assisted biology teaching (SRAS-AIBT)

OpenAlex · English

As the use of artificial intelligence in education increases, determining student readiness and anxiety has become a necessity; however, the lack of a measurement tool specific to biology education in the literature formed the basis of this study. This study aims to address this gap by developing a scale that can measure student readiness and anxiety about the use of artificial intelligence in biology teaching. This research employed an exploratory sequential mixed-methods design. First, new items were developed and an item pool created by gathering student opinions based on relevant concepts and literature reviews. Then, the prepared items were submitted to expert opinions, and after expert evaluations, validity and reliability tests of the scale were conducted using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). This study involved 322 students in the EFA phase and 300 students in the CFA phase, aged 18-22, studying biology in a province in eastern Turkey. The developed scale consisted of two factors and 15 items. The scale was developed as a 5-point Likert-type instrument ranging from 'Strongly Disagree' (1) to 'Strongly Agree' (5). According to the EFA results, the cumulative variance ratio was determined to be 73.084%. The Cronbach's alpha reliability coefficient was calculated as 0.95. The CFA results revealed that the two-factor model had a sufficient fit, and the values χ²/df = 3.7, RMSEA = 0.08, CFI = 0.94, and NNFI (TLI) = 0.93 support the structural validity of the model. As a reliable and valid instrument, the SRAS-AIBT serves as a practical tool for educators to design AI-assisted biology lessons tailored to student needs, thereby contributing directly to the improvement of instructional methods in this rapidly evolving field.