Towards an Operationalization of AI acceptance among Pre-service Teachers

Abstract

Artificial Intelligence (AI) has found its popularity in many fields of our life, ranging from song recommendation to lung cancer identification. CSE can impart AI knowledge to all people (including teachers) so that they can make an informed decision about AI. Besides, AI technologies can support tailoring the education to the students’ needs or unload teachers by doing routine work for them and leaving more space for creativity. However, despite the growing potential of AI applications in education, some skepticism or even rejection can be observed. It could be especially critical for teacher education: by being a role model for pupils, teachers could multiply their attitude towards AI while transferring it to the pupils. Although AI acceptance is broadly investigated in the marketing context, there is not much prior research on AI acceptance among teachers. Besides, AI acceptance as a term is questionable due to the heterogeneity of the AI field. We highlight the research gap, propose an instrument for the data collection, and introduce the idea of the acceptance spectrum. The proposed concept is exemplified by the case study of acceptance of the AI-supported homework assessment among pre-service teachers.