Chapter One: Background, Problem & Purpose
Generative artificial intelligence has moved rapidly from a specialized technical development to a routine feature of school work, teacher planning, student writing, tutoring, communication, and assessment. The fundamental educational problem is what happens to learning when the visible artifact of learning can be produced without the interpretive, rhetorical, and authorial work that education is intended to develop.
Three Research Questions:
- RQ1: How do K–12 classroom-facing educators understand and navigate the friction-reducing affordances of generative AI in academic work, particularly in relation to productive and exclusionary friction?
- RQ2: What institutional conditions, including policy, assessment design, professional development, leadership disposition, and governance structures, enable or constrain friction-preserving pedagogy across classroom, building, and system levels?
- RQ3: What framework-aligned policy language, assessment expectations, and instructional-design supports do K–12 educators and school-system leaders describe as necessary to preserve productive friction while reducing exclusionary friction under conditions of generative AI?
Chapter Two: Review of Literature & Theoretical Framework
Chapter Two establishes the theoretical spine of the study. Extending Walter Ong's media ecology, the paper names the present condition tertiary algorithmicity, a media environment wherein algorithmic systems both curate and generate symbolic content, rendering human authorship optional at scale (Miner, 2026b).
To address this condition, the study presents the Pedagogical Friction Framework, distinguishing noetic, rhetorical, and existential friction as learner-facing dimensions, and infrastructural friction as the institutional condition of possibility.
Chapter Three: Methodology and Design
The study uses a qualitative-dominant convergent mixed methods design (Creswell & Plano Clark, 2018), notated QUAL + quan. Qualitative inquiry provides the primary means of understanding how participants interpret generative AI, pedagogical friction, learning, authorship, and institutional response, while supporting quantitative evidence describes survey patterns and national context. Constructivism governs the research questions and primary interpretation; pragmatism supplies the narrower mixed methods warrant for bringing several forms of evidence into conversation.
Participant Groups and Convergent Logic:
The study examines how people in different educational roles interpret and respond to pedagogical friction: (1) classroom-facing educators, (2) building-level administrators, and (3) district or system-level leaders, with adult university students contributing a retrospective learner perspective analyzed as a distinct participant perspective. A convergent design lets these sources be collected during the same period, analyzed by methods appropriate to each, and integrated through joint displays and narrative discussion. It does not seek causal effects or statistical generalization.
Counterarguments & Framework Limits
1. Cognitive Augmentation Objection (Mollick, 2024; Riva, 2025)
Objection: AI functions as an intellectual co-pilot extending human cognition like writing or calculators.
Rebuttal: Tools extend expert cognition only after baseline schemas exist. Routine AI reliance during novice formation prevents building foundational schemas required for expertise.
2. Technological Determinism Objection (Feenberg, 2002)
Objection: Claiming tertiary algorithmicity dictates outcomes overstates medium power and ignores human agency.
Rebuttal: Naming pedagogical friction as an intentional instructional response asserts human agency within a powerful default rather than treating the default as destiny.
3. Rigor as Gatekeeping Objection (Dolmage, 2017; Annamma et al., 2013)
Objection: Demanding struggle and friction risks preserving exclusionary barriers that penalize disabled or multilingual learners.
Rebuttal: The framework sets a strict equity boundary: remove exclusionary friction (accessibility barriers) while intentionally preserving productive friction (schema construction).