Mapping the complexity of learners’ attitudes toward ChatGPT: preliminary validation of a new scale

Abstract

The Chat Generative Pre-trained Transformer (ChatGPT), a prominent example of Artificial Intelligence Generated Content (AIGC) technology, has garnered considerable attention from educational researchers and is increasingly employed in education. Learners' attitudes toward tools like ChatGPT are crucial for maximising their educational effectiveness. Previous research has overlooked the multidimensional structure of learners' attitudes toward emerging technologies, encompassing both positive and negative emotional and rational dimensions. This study aimed to develop and validate a scale, the Learners' Attitudes Toward ChatGPT Scale (LATCS), for assessing university students' attitudes toward ChatGPT. First, initial scale items were generated. A rigorous stratified random sampling method was employed, recruiting a total sample of 850 university students from seven universities across four administrative regions in mainland China. Following psychometric procedures, the total sample was split into two subsamples: an exploratory sample and a validation sample. The exploratory sample, consisting of 425 participants, was used to conduct exploratory and confirmatory factor analyses to develop the preliminary LATCS, comprising 16 items. The validation sample, with an independent sample of 425 participants (115 males), was used to validate the LATCS's reliability and validity through confirmatory factor analysis. These findings offer a scientific tool for further exploring individuals' attitudes toward ChatGPT.

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