{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/132660"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/132660","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Beyond the imitation game: complementary intelligence partnerships in education","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Galla, Michele K."],"institution":"University of Illinois Urbana-Champaign","degree_name":"Ed.D.","degree_level":"Dissertation","degree_discipline":"Educ Policy, Orgzn & Leadrshp","degree_department":null,"school":null,"contributors":["Magee, Liam","Cope, William","Kalantzis, Mary","Ortega-Martin, José Luis"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-12","date_published":"2025-12","updated_at":"2026-07-22T22:25:07Z","subjects":["Anthropocentrism","AI","Noetic Intelligence"],"languages":["en"],"rights":["Copyright 2025 Michele Galla"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/132660","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Magee, Liam","Cope, William","Kalantzis, Mary","Ortega-Martin, José Luis"]},{"key":"dc:creator","label":"Author","values":["Galla, Michele K."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-12","2025-11-26"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Educ Policy, Orgzn & Leadrshp"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ed.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Anthropocentrism","AI","Noetic Intelligence"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2025 Michele Galla"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/132660"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-12-01","The student, Michele Galla, accepted the attached license on 2025-11-25 at 15:32.","The student, Michele Galla, submitted this Dissertation for approval on 2025-11-25 at 15:47.","This Dissertation was approved for publication on 2025-11-26 at 10:06.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22953 on 2026-02-19 at 18:46:00"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Beyond the imitation game: complementary intelligence partnerships in education"]}]}],"canonical_facts":{"dc:contributor":["Magee, Liam","Cope, William","Kalantzis, Mary","Ortega-Martin, José Luis"],"dc:creator":["Galla, Michele K."],"dc:date":["2025-12","2025-11-26"],"dc:description":["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.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-12-01","The student, Michele Galla, accepted the attached license on 2025-11-25 at 15:32.","The student, Michele Galla, submitted this Dissertation for approval on 2025-11-25 at 15:47.","This Dissertation was approved for publication on 2025-11-26 at 10:06.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22953 on 2026-02-19 at 18:46:00"],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/132660"],"dc:language":["en"],"dc:rights":["Copyright 2025 Michele Galla"],"dc:subject":["Anthropocentrism","AI","Noetic Intelligence"],"dc:title":["Beyond the imitation game: complementary intelligence partnerships in education"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Educ Policy, Orgzn & Leadrshp"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ed.D."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:07Z"}