This article proposes a critical typology of five emerging responses to artificial intelligence (AI) in language education, from prohibition and hype to critical engagement, highlighting the assumptions, tensions, and possibilities each orientation embodies. This typology serves as a reflective tool to examine how educators and institutions are…

Artificial intelligence (AI) and its subfield, machine learning, have become indispensable across various industries. With the aid of low-code/no-code development platform like KNIME, understanding and applying machine learning algorithms has been simplified for various fields, including business and information systems, as these platforms reduce…

Advances in machine learning (ML) offer new possibilities for science education research. We report on early progress in the design of an ML-based tool to analyze students' mechanistic sensemaking, working from a coding scheme that is aligned with previous work in physics education research (PER) and that is amenable to recently developed ML…