Beyond the imitation game: complementary intelligence partnerships in education

This dissertation examines a paradox that challenges core assumptions about intelligence in education: the “Bloom’s Taxonomy Inversion,” where Large Language Models excel at “higher-order” synthesis while failing at “lower-order” factual recall. I trace this anomaly to AI’s anthropocentric foundations, from Turing’s imitation framing through the Dartmouth agenda, showing how human-centric benchmarks, while providing early focus and legitimacy, ultimately constrained architectural development and educational applications. As institutions rush to integrate AI without adequate frameworks, these theoretical gaps produce problematic practices: treating AI as either threats to replace human intelligence or as deficient tools requiring perfection of human-like performance. I argue that anthropocentrism has created a paradigm mismatch. Educational theory developed for individual human learners proves inadequate for human-AI collaboration, leaving educators without guidance for effective cognitive partnerships. I propose a paradigm shift to Complementary Intelligence, introducing Noetic Intelligence (NI) to describe machine-native cognitive capabilities distinct from human cognition. Rather than pursuing AI that imitates humans, the framework positions NI as a partner with asymmetric but complementary strengths. My research contributes in three ways. First, it offers theoretical advancement through the Complementary Intelligence framework, which grounds human-NI collaboration in architectural difference rather than deficiency. Second, it provides practical resources through the “Beyond the Imitation Game (BIG) Research Handbook,” a pedagogical guide featuring the Dual-Track Complementary Cognition Taxonomy and assessment tools for evaluating collaborative intelligence. Third, it employs a dual-perspective methodology, treating NI systems as research participants through structured interviews with eleven architecturally diverse systems and comparing human versus noetic coding of responses. This approach produces a framework refined through collaboration rather than human theorizing alone. The research generates concrete educational applications: pedagogies that strategically distribute cognitive labor according to architectural strengths, assessments evaluating collaborative quality and learning growth rather than individual outputs, and curricula developing “intelligence awareness” as a foundational 21st-century literacy. By repositioning the human-NI relationship from imitation to complementarity, this work provides educators with theoretically grounded and actionable frameworks for teaching in an era of multiple intelligences.

Name thesis:degree_name

Ed.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Educ Policy, Orgzn & Leadrshp

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Galla, Michele K.

Contributors dc:contributor

• Magee, Liam
• Cope, William
• Kalantzis, Mary
• Ortega-Martin, José Luis

• Anthropocentrism
• AI
• Noetic Intelligence

Statement dc:rights

• Copyright 2025 Michele Galla

Language dc:language

en

Handle dc:identifier

https://hdl.handle.net/2142/132660

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/132660