Language Teachers’ Assessment Literacy in AI-aided Adaptive Learning Environments

AI-aided Language Assessment Literacy (LAL), is a pivotal aspect of modern teaching, posing both an indispensable asset and a formidable challenge. Despite its paramount importance, research on teachers’ LAL, especially in the context of AI-aided tools, has been notably scarce. This paper addresses the research gap by conducting a practical investigation, emphasizing the application of LAL concepts with a special focus on integrating Artificial Intelligence in language assessment. For this purpose, 261 EFL teachers of three groups (i.e. novice teachers with one to three years of experience, senior teachers with three to five years of experience, and experienced teachers with more than five years of experience) participated in the research. Then the process of pre-test, 50-hour teacher training course, 16-session teaching in Magic School or Edapp environment, post-test, and interview were conducted. The reasons for choosing these platforms were that they offer Adaptive Learning Environments (ALE), are integrated with AI and accessible, and have a simple user interface. The mixed methods analyses of the experiment data showed that: AI-aided ALE training has led to the development of teachers’ LAL; regarding teaching quality, the teachers’ performance decreased from G3 to G2 and finally G1 respectively; while in the case of the LAL variable, G2 outperformed the others.