An open-access article was published, introducing “algorithmic agency” and the Co-Intelligent Academic Practice (CAP) framework to critically re-envision researcher preparation, asserting that generative artificial intelligence fundamentally transforms the epistemological conditions of scientific knowledge co-construction.
Ifenthaler, D., & Gibson, D. C. (2027). From computational literacy to algorithmic agency: Re-envisioning researcher preparation in the era of generative artificial intelligence. Frontiers of Digital Education, 4(1), 9. https://doi.org/10.1007/s44366-027-0118-2
The emergence of generative artificial intelligence (GenAI) systems has fundamentally altered the epistemological conditions under which educational research is conducted, rendering existing faculty preparation frameworks necessary but insufficient. Building on a call for a computational mindset and subsequent work on educational data literacy, this article proposes a three-stage developmental progression culminating in algorithmic agency, which is the capacity to critically co-construct scientific knowledge with large language models and automated analytical pipelines while maintaining methodological rigor and preserving human epistemic authority. Unlike prior frameworks, which conceive of artificial intelligence as an analytical instrument under human direction, algorithmic agency addresses the qualitatively distinct challenge posed by GenAI systems that function as epistemic participants capable of synthesizing literature, constructing arguments, and producing knowledge claims that enter scholarly discourse alongside human-authored work. To operationalize this progression, we propose the Co-Intelligent Academic Practice (CAP) framework, a theoretically grounded developmental architecture comprising four cumulative competency domains organized across three developmental stages. A methodology integrating design and systems thinking provides the developmental process through which faculty build and sustain these competencies. We further argue that individual competency development is insufficient without commensurate institutional enablement, including governed infrastructure, value-aligned policy, scholarly recognition, community-based developmental support, and equitable global participation. The article concludes by identifying empirical validation of the CAP staging model as the field’s most urgent methodological priority and arguing that faculty development is the primary institutional lever through which epistemic norms for the co-intelligent era are established or abandoned.
