Artificial Intelligence in Educational Research and Scholarship: Seven Framings

In a recent interview (Bender et al., 2025), Professor Emily M. Bender discussed the limitations of technical solutions in addressing harmful Artificial Intelligence (AI) bias. She described a particular point we may reach at which technical solutions stop working, and when we should then widen the lens to ask about the problem framing itself. This is a crucial step in any inquiry that is of concern to both novice and experienced researchers alike: moving from problem-solving to problematisation. This commentary aims to provideeducational researchers with a glimpse into the wide array of research problems and problematisation of AI in Education (AIED). It discusses seven framings of AIED: methodological pluralism; metaphors; ethnographic studies; imagining futures through fiction; humanistic groundings of AI design and development; third space professionals in research; and open education. We describe why these particular frames are relevant and how we wrote this commentary. We go on to suggest that to sustain the desirable but sometimes elusive nexus between research and teaching, we need to see both as rich, diverse, and distributed activities consisting of many actors. We seek to probe: What is AI? Who gets to say so and why? What critical, creative and pluralistic approaches can we take to research into its effects on the outcomes and experiences of students in higher education?