#249: Dialogic Intelligence: Rethinking the pedagogical goal of CSCL in the context of Generative AI

As generative AI surpasses students in knowledge delivery and examination performance, education faces an unprecedented challenge in defining what human intelligence means. This theory paper argues that our response should be to reclaim, revalue, and rethink intelligence itself, advancing dialogic intelligence as a central educational aim. The dominant view of intelligence as an individual, measurable trait reflects print literacy's historical affordances, which have obscured intelligence's fundamentally relational nature. AI's emergence as a ubiquitous cognitive technology necessitates recovering an older understanding: intelligence is the capacity to support the emergence of truth and goodness through responsive relationship—whether between people, with nature, or with technology such as generative AI. While the CSCL community has explored teaching thinking, research has typically focused on collaboration as a means to enhance curricular learning. The dialogic responsiveness of generative AI suggests instead that we should design CSCL to promote dialogic intelligence as an end in itself. We illustrate this agenda through two CSCL design examples that prioritize dialogic intelligence over content mastery.