Framing artificial intelligence in education: innovation narratives, contested equity, and environmental silence in journal calls for papers (CFPs)

Calls for papers (CFPs) play a formative role in shaping emerging research agendas, yet they are rarely examined. This study analyzes 111 CFPs using content analysis to examine how artificial intelligence (AI) in education is framed. Findings reveal a dominant framing in which CFPs presume the integration of AI into education, treating its effectiveness as already established rather than an open empirical question. This pattern is consistent with innovation-oriented framings of AI. Many calls are structured in ways that implicitly exclude studies that find AI ineffective or counterproductive. Equity emerges as a sharply polarized domain, with CFPs making opposing, high-certainty claims about whether AI mitigates or exacerbates inequality. Ethical concerns are commonly referenced but selectively emphasized. Notably, environmental impacts are almost entirely absent despite their prominence in broader debates about AI’s societal costs. These findings indicate that CFPs not only reflect but structure research agendas, potentially narrowing the range of findings that are recognized as legitimate or publishable within the field. Further research is needed to examine whether these framing patterns are reinforced or mitigated through peer review and editorial decision-making, and whether they influence which findings are ultimately incorporated into the published literature.