Measuring Motivation for Generative AI‐based Language Learning: Scale Development and Validation Based on the Self‐Determination Theory

ABSTRACT The accelerating use of generative artificial intelligence (GenAI) in language learning calls for the development of theory‐driven measurement instruments. For this reason, the current study aims to develop and validate a motivation scale for GenAI‐based language learning, grounded in the self‐determination theory (SDT). The data were collected twice from two independent groups of EFL learners in two universities. Exploratory factor analysis (EFA) and test‐retest analyses were conducted on the data from the first participant group. Confirmatory factor analysis (CFA) and correlational analyses for the criterion validity were conducted through the data from the second participant group. The reliability analyses were conducted separately on the data from both participant groups. The findings revealed that the developed scale demonstrated a valid and reliable measurement model with both groups of participants. In conjunction with the self‐determination theory, it has 17 items with three factors: autonomy, competence, and relatedness. The findings also revealed that these factors are highly associated with the dimensions of generative AI acceptance. It was concluded that the scale can be used as a valid and reliable instrument to measure EFL learners’ motivation for generative AI‐based language learning within diverse learning environments, including face‐to‐face, open, distance, and blended learning.