AI Session · NLU Doctoral Colloquium 2026
Pedagogical Friction · Tertiary Algorithmicity
Pedagogical Friction
and AI
Unproductive success, tertiary algorithmicity, and the human work of thinking and meaning-making.
Micah J. Miner, CETL, Ed.S.
Director of Innovation & Technology · Doctoral Student
Curriculum, Advocacy & Policy · National Louis University
Join the workshop
bit.ly/49Y5GEu
01 Two passages from a literature review
Both are competent. Something is different.
Selwyn (2024) and Jandrić (2023) converge on the postdigital condition as a frame for understanding AI in education, though they diverge on the question of agency. Where Selwyn locates resistance in institutional skepticism, Jandrić finds it in the recursive entanglement of human and machine practice. This study extends both by asking what remains pedagogically protected when the symbolic environment itself becomes algorithmically generative.
The literature on AI in education converges around several key themes including postdigital approaches, critical perspectives on technology, and questions of human agency. Researchers such as Selwyn and Jandrić have made significant contributions to this growing field, offering valuable insights into how educators can navigate the complex landscape of emerging technologies in learning environments.
Source anchors:
Selwyn 2024
Jandrić 2023
After two minutes of silent reading
What is different between these passages, and which one tells you the student understands the literature?
02 The question this session asks
What changes when the symbolic environment in which doctoral scholars think, read, write, and argue is increasingly organized by algorithmic systems, both in how content circulates and how content originates?
A 70-minute session in three parts
03 Roadmap · the next seventy minutes
Three parts. One question. Your work in the room.
i
The shift Ong's framework did not anticipate
~20 min
ii
Why the educational stakes are developmental
~15 min
iii
Pedagogical friction applied to your scholarship
~30 min
i
04 Section i · Theoretical foundation
The shift Ong's
framework did not
anticipate.
05 Ong · media restructure consciousness
Three stages, then two more.
Each transition is a cognitive event, not just a technological one. Each stage brings capacities the prior lacked and erodes capacities the prior sustained.
origination threshold
Primary orality
Memory-based, communal, situational. Knowledge preserved through repetition, formula, and rhythm. The word lives only in the existential present. There is no text to consult, no record to revise. To know something is to be able to say it now, in the company of others.
The stages overlap rather than replace one another. The dates mark when each condition became dominant, not a clean succession. The threshold marks a change in what is structurally possible: symbolic content can now originate algorithmically at scale.
06 The analytical hinge
Three assumptions in Ong's framework that no longer hold.
Click each assumption to see what generative AI breaks.
01
The first assumption
Humans originate symbolic content.
What AI breaks
Generative systems now produce text, image, and argument indistinguishable from human work. The source of symbolic expression is no longer necessarily human consciousness.
click to reveal
02
The second assumption
Distribution follows transparent logics.
What AI breaks
Editorial judgment and schedules were visible. Algorithmic curation makes distribution proprietary, opaque, and personalized. Two scholars open the same feed and encounter different literatures.
click to reveal
03
The third assumption
Consciousness encounters media as external environment.
What AI breaks
Books sit on shelves. Broadcasts emanate from elsewhere. Personalized environments now reflect the user's own patterns back to them, collapsing the distance between mind and medium.
click to reveal
07 Definition
Tertiary Algorithmicity
A media environment in which algorithmic systems both curate and generate symbolic content, making human authorship optional at scale.
The new axis: human vs. algorithmic origination
08 Three defining characteristics
Each maps to one of the ruptured assumptions.
Click a characteristic to see a concrete rupture in doctoral work.
Humans originate content
Expression no longer necessarily begins in a human mind.
Noetic displacement
Distribution is legible
Curation becomes opaque, personalized, and origin-uncertain.
Rhetorical saturation
Media remain external
The environment reflects the user's own patterns back.
Existential abstraction
ii
09 Section ii · Educational stakes
The threat is not
academic integrity.
It is unproductive success.
10 Kapur · four learning outcomes
Generative AI lands in one quadrant by default.
Correct performance
Incorrect performance
With understanding
Without understanding
The artifact is present. The cognitive development that produced it is not. The product looks like the product of understanding.
11 Recursive application
This is not about K-12 students.
It is about your dissertation.
Every doctoral scholar in this room makes a thousand small decisions a week about where to invite AI into their scholarship. The literature review you are drafting tonight. The committee feedback you have to address by Friday. The chapter you have rewritten six times. The question the framework asks of K-12 is the same question it asks of you:
When you delegate the interpretive labor, what happens to the thinker who would otherwise have done it?
iii
12 Section iii · Response framework
Pedagogical
Friction.
The intentional preservation of cognitive, rhetorical, existential, and infrastructural resistance under conditions where frictionless automation has become the default.
13 Four dimensions · click to apply to doctoral work
The head, the room, the world, the system.
i
Noetic friction
The head · internal cognitive resistance
Comprehending difficult text, synthesizing sources, building argument from evidence, revising your own thinking.
In your scholarship
Reading the source yourself before asking the AI to summarize it. Writing your first interpretation of a passage before checking what the model would say. The schema you build by struggling with Foucault at 11pm is not transferable to the model that produced the polished paragraph.
ii
Rhetorical friction
The room · social and dialogic struggle
Defending claims against another mind that disagrees, misunderstands, or pushes back in ways you cannot predict.
In your scholarship
Your committee meeting is rhetorical friction. So is the conference Q&A when someone has read your paper closely. The AI will not push back the way a chair does. It will not ask the question that exposes the soft assumption in chapter three.
iii
Existential friction
The world · embodied accountability
Presenting your own thinking, in your own voice, with your name attached.
In your scholarship
Your name on the dissertation. Your defense. The published article you will be asked about for the rest of your career. Existential friction is what makes scholarship a vocation rather than a deliverable.
iv
Infrastructural friction
The system · condition of possibility
The institutional conditions, policy, time, professional norms, that make the other three sustainable.
In your scholarship
Your IRB, your journal's AI policy, your program's expectations, your chair's stance. The infrastructure decides whether you can practice the other three friction dimensions, or whether the institution quietly pushes you to bypass them.
14 The equity test
Not all friction is productive.
An argument for preserving friction can become an argument for preserving inequity if it does not ask whose work a given difficulty supports.
Productive friction · builds capacity
- Wrestling with difficult theoretical text
- Drafting your own argument before consulting models
- Defending claims under genuine critique
- Revising chapters based on substantive feedback
- Struggle that prepares you for the next problem
Exclusionary friction · blocks access
- Language barriers imposed on content mastery
- Inaccessible formats unrelated to scholarly work
- Procedural hoops disconnected from learning
- "Rigor" that gatekeeps without building schema
- Difficulty treating one writing profile as the norm
The same tool can do both at the same time. Distinguishing them requires situated judgment.
14a Calibration · where is the line?
Place each case. You will disagree.
In groups of three, place each case on the line between productive friction and exclusionary friction. There is no answer key. Click a case to reveal why the room splits, but only after your group has committed to a position.
Productive · builds capacity
Exclusionary · blocks access
01
The case
A multilingual scholar uses AI to translate and smooth the prose of their literature review.
Why the room splits
It removes a language barrier unrelated to scholarly judgment, which looks like productive access. It can also flatten the scholar's own voice and the seams of the argument, which looks like a bypass of authorship. One act, both readings.
reveal the tension
02
The case
A scholar uses AI to code a set of qualitative interview transcripts.
Why the room splits
It relieves genuine tedium, which reads as productive. But the coding is the interpretive analysis. Hand it to the model and you may hand over the dissertation's central act of meaning making.
reveal the tension
03
The case
A scholar asks AI to draft the counterargument section of a chapter.
Why the room splits
It surfaces objections a tired writer would miss, which strengthens the work. It also outsources the labor of anticipating critique, which is exactly the muscle a defense will test.
reveal the tension
Report out: name the case your group split on, and the dimension that made it hard.
15 Apply the framework · your scholarly work
Choose a scenario. Audit the friction.
Each scenario is something a doctoral scholar in this room is doing this week. Pick one. Discuss in groups of three.
Synthesizing 40 articles for a literature review
You have forty PDFs in Zotero. Your committee wants a synthesis chapter by month's end. The AI can produce a competent thematic synthesis in twenty minutes.
Where productive friction lives
Reading the actual sources, marking what surprises you, writing your own synthesis of what these forty papers do and do not say. The schema you build here is the framework you will use to read the next forty.
Where exclusionary friction lives
Forty PDFs without retrieval-augmented search would be a procedural barrier unrelated to scholarly judgment. AI search and summary of long documents can be access scaffolding.
The hardest call
The line between "I used AI to find the relevant passages" and "I used AI to do the thinking about what those passages mean." You may need to do both, but only the second one is your dissertation.
16 Group discussion · 12 minutes
Three questions for your group.
i
Where in your own scholarship have you noticed AI offering to bypass exactly the cognitive work you most need to do?
ii
Where has AI legitimately reduced an exclusionary barrier in your work, and how do you know it has not also reduced productive friction?
iii
What infrastructural change at NLU would most strengthen the other three dimensions for doctoral scholars?
17 Closing synthesis
The educational problem posed by generative AI is the bypassing of interpretive labor, intellectual accountability, and the developmental conditions on which human learning depends.
Including yours.
18 Take this with you · questions welcome
A friction audit for your scholarship.
Use this one-page diagnostic on a chapter, article, methods section, or assignment you are designing.
i
NoeticWhat thinking must remain inside the scholar's own mind?
ii
RhetoricalWho or what will genuinely push back on the claim?
iii
ExistentialWhere does the work stay accountable to lived practice or consequence?
iv
InfrastructuralWhat condition, policy, scaffold, or access issue shapes the work?
✓
Design movePreserve productive friction, reduce exclusionary friction, and name the evidence of learning.
Companion artifacts
Micah J. Miner, CETL, Ed.S.
National Louis University