Knowledge as a Social Symphony
The Detection Deception, Chapter 6
Fellow Augmented Educators,
Welcome to week six of ‘The Detection Deception’ book serialization. This week’s installment concludes the second part of the book by examining how the dialogic nature of human understanding renders AI-generated work fundamentally different from authentic learning. Drawing on Mikhail Bakhtin’s theory of dialogism, it argues that thinking itself is not an isolated mental activity but emerges through social interaction and conversation.
Last week’s chapter explored problem-posing education as an alternative to the banking model. This chapter deepens that foundation by showing why dialogue is not merely a teaching technique but the very medium through which understanding develops. This has profound implications for how we respond to AI. If knowledge emerges through irreducibly human dialogue rather than individual text production, then our obsession with policing final essays has always been misguided.
Thank you for reading along! See you in the comments.
Michael G Wagner (The Augmented Educator)
Contents
Chapter 1: The Castle Built on Sand
Chapter 2: A History of Academic Dishonesty
Chapter 3: The Surveillance Impasse
Chapter 4: Making Thinking Visible
Chapter 5: The Banking Model and Its Automated End
Chapter 6: Knowledge as a Social Symphony
Chapter 7: A Unified Dialogic Pedagogy
Chapter 8: Asynchronous and Embodied Models
Chapter 9: Dialogue Across the Disciplines
Chapter 10: The AI as a Sparring Partner
Chapter 11: Algorithmic Literacy
Chapter 12: From the Classroom to the Institution
Chapter 6: Knowledge as a Social Symphony
In the fall of 1929, a young Russian scholar named Mikhail Bakhtin gathered with friends in a small apartment in Leningrad to discuss literature, philosophy, and the nature of human consciousness. These informal seminars, conducted under the shadow of Stalinist surveillance, would produce insights that challenge how we think about thought itself. Bakhtin and his circle were wrestling with a question that seems almost quaint in our age of artificial intelligence: what makes human understanding distinctively human? Their answer was radical then and remains so now. Thinking, they argued, is not something that happens inside individual heads but between people in dialogue.
This notion might have remained an obscure theoretical curiosity, buried in Soviet-era literary criticism, except for one thing: it offers a profound response to our current educational crisis. If understanding emerges not from isolated minds but from social interaction, then the entire infrastructure of individual assessment looks not just outdated but misconceived. The following exploration examines what it might mean to take dialogue seriously as the basis for learning. It considers how classrooms function as unique meaning-making communities, how knowledge emerges through collective inquiry rather than individual production, and why our obsession with final products blinds us to the actual processes through which understanding develops. This is not simply about adding more discussion to existing curricula. It is about recognizing that when students gather to think together, they create something no AI can replicate or replace: a living conversation where meaning emerges, develops, and transforms through the irreducibly human experience of minds meeting across difference.
No Thought Is an Island: The Power of Dialogism
The traditional classroom operates on a fundamental assumption that most of us never question: thinking happens inside our heads, and speaking is merely the external expression of those internal thoughts. We imagine ideas forming privately in the silence of our minds, complete and whole, before we share them with others. This model of cognition treats the classroom as a collection of individual thinkers who occasionally report their private mental contents to one another. Yet what if this entire framework rests on a critical misunderstanding of how human consciousness actually works?
The Russian literary theorist Mikhail Bakhtin offers us a radical alternative vision. Writing in the Soviet Union during the early twentieth century, Bakhtin developed a philosophy of language and consciousness that challenges our individualistic assumptions about thought. His theory of dialogism suggests that meaning and understanding are not private possessions we carry around in our heads, but rather emerge in the dynamic space between speakers. This is not merely meant as a poetic metaphor but as a serious claim about the nature of human cognition, which has profound implications for how we understand learning. This is particularly true in an age where machines can generate text with no consciousness at all.
To grasp Bakhtin’s revolutionary idea, consider a simple example. When a student in a literature class says, “I think Hamlet is basically just depressed,” this sentence appears to be a straightforward report of an internal thought. But Bakhtin would argue that this statement is actually far more complex. The student’s words are shaped by everything they have heard before about Hamlet—perhaps a parent’s casual comment years ago, a film adaptation they once saw, or fragments of classroom discussion from previous weeks. Their statement also anticipates how others might respond. Will the teacher approve? Will classmates think this interpretation is too simplistic? The meaning of their utterance does not reside solely in the words themselves or in the student’s private intention, but emerges from this complex web of past voices and expected responses.
Bakhtin describes this phenomenon through his concept of the “utterance” as the basic unit of communication. Unlike a sentence, which is a grammatical abstraction, an utterance is always embedded in a specific context of actual dialogue. Every utterance has what Bakhtin calls “addressivity”—it is oriented toward someone, shaped by our relationship with them, and colored by our expectations of their response. When we speak, we are not simply encoding our thoughts into words. We are participating in what Bakhtin calls the “chain of speech communion,” where every word we use carries the traces of its previous uses and anticipates its future reception.
This interconnectedness of all speech leads Bakhtin to his most radical claim: consciousness itself is dialogic. We do not think in isolation and then express our thoughts to others. Rather, our very ability to think depends on our internalization of social dialogue. The voice in our head that we experience as thinking is actually composed of the many voices we have encountered throughout our lives. When we engage in internal deliberation, weighing different options or arguing with ourselves, we are conducting an internalized version of social dialogue. In Bakhtin’s memorable phrase, “I live in a world of others’ words.”
The implications for education are transformative. If thinking is inherently dialogic, then the traditional model of assessment that focuses on individual, isolated production misunderstands the nature of learning. When we ask a student to write an essay alone in their room, we are asking them to perform an artificial extraction from the ongoing dialogue that makes up their understanding. The resulting text may show certain skills, but it cannot capture the dynamic, responsive nature of genuine comprehension.
This becomes particularly relevant when we consider the challenge posed by generative AI. A large language model can produce text that appears meaningful, drawing on patterns from billions of documents to construct grammatically perfect and topically relevant responses. But this text is fundamentally monologic in Bakhtin’s terms. The AI has no genuine addressivity—it is not truly oriented toward anyone, shaped by no actual relationship, colored by no real anticipation of response. It has not internalized voices through lived experience but merely identified statistical patterns in text. Most crucially, it has no stake in the ongoing conversation. When a student uses AI to generate an essay, they are not just outsourcing the work of writing. They are attempting to substitute a monologic artifact for what should be a dialogic performance.
The distinction becomes clearer when we consider how meaning emerges in actual classroom discussion. Imagine a seminar where students are discussing climate change policy. One student mentions their grandmother’s stories about how winters used to be colder. Another connects this to a graph they saw in their economics class. A third challenges the reliability of anecdotal evidence. The teacher introduces a concept from the reading that reframes the entire discussion. In this moment, understanding is not located in any individual mind but is actively being constructed through the interaction. Each contribution gains its meaning partly from how it responds to what came before and how it shapes what comes after.
This is what Bakhtin means when he writes about the “dialogic overtones” that surround every utterance. Words do not have fixed meanings that we can simply look up in a dictionary. Their significance emerges from the specific context of their use, the relationships between speakers, and the ongoing flow of dialogue. A phrase like “That’s interesting” can mean anything from genuine fascination to polite dismissal, depending on the tone, the context, and the relationship between speakers. This contextual, relational aspect of meaning is precisely what AI cannot grasp, trained as it is on decontextualized text stripped of its living dialogic situation.
The dialogic nature of understanding also helps explain why certain kinds of learning experiences are so powerful. When a student has that “aha” moment during a discussion, it is rarely because they received a piece of information they were missing. More often, it is because something someone else said reframed their existing understanding and allowed them to see connections they had not noticed before. This is not a transfer of knowledge from one container to another but a collaborative construction of meaning that could not have happened in isolation.
Bakhtin’s insight also illuminates why teaching through pure lecture, what Paulo Freire called the “banking model,” is so limited. When an instructor simply deposits information into passive students, they are treating knowledge as a commodity that can be transferred intact from one mind to another. But if understanding is dialogic, then this model fundamentally misrepresents how learning actually occurs. The students are not empty vessels waiting to be filled but participants in an ongoing conversation, bringing their own voices, experiences, and anticipations to every encounter with new ideas.
This dialogic view suggests that we think not to produce thoughts but to participate in thinking. The goal is not to have the right answer stored away in our minds but to engage productively in the ongoing dialogue through which understanding emerges. This shifts the fundamental question of education from “What do students know?” to “How can students participate in knowledge construction?”
The implications extend beyond individual learning to the very nature of knowledge itself. In fields from science to literature, what we call knowledge is not a collection of facts stored in textbooks but an ongoing conversation among practitioners. Scientific knowledge advances through dialogue—through conferences, peer review, and debate. Literary interpretation develops through scholars responding to and building upon each other’s readings. Even mathematics, seemingly the most abstract and isolated of disciplines, progresses through mathematicians engaging with each other’s proofs and conjectures.
Understanding Bakhtin’s dialogism reveals why authentic learning feels different from mindless memorization. When we truly understand something, we do not just possess information about it. We can enter dialogue about it, responding to questions we have not anticipated, making connections to contexts we have not previously considered. This dialogic flexibility distinguishes understanding from mere information storage. It is also what current AI systems cannot achieve. They can retrieve and recombine information in impressive ways, but they cannot genuinely enter dialogue, cannot be surprised by a question, and cannot have their thinking transformed by an unexpected response.
The Classroom as a Unique Universe of Meaning
Every September, something remarkable happens in classrooms around the world. A collection of strangers enters a room, and over the course of weeks and months, they develop something that cannot be found in any textbook or downloaded from any database: their own unique intellectual microculture. By November, a simple phrase like “Remember what happened with the potato example?” can send the entire class into knowing laughter, recalling not just the content of a lesson but the specific moment when a student’s unexpected question about agricultural economics somehow led to a breakthrough in understanding monetary policy. This shared reference means nothing to anyone outside that room, yet within it, the phrase carries layers of meaning that have accumulated through weeks of dialogue.
This phenomenon points to something profound about the nature of learning that Bakhtin’s dialogic theory helps us understand. Each classroom develops what we might call its own “semantic atmosphere”—a unique configuration of meanings, references, and ways of speaking that emerge from the particular mix of voices present. This is not simply a matter of inside jokes or shared memories, though these play a role. It is about the gradual development of a collective intellectual vocabulary that shapes how the group thinks together.
Consider how this process unfolds in practice. In the first week of a philosophy seminar, students might struggle with the concept of “false consciousness.” The term feels abstract, foreign, something from a textbook. But then one student relates it to their experience working in retail, describing how they found themselves defending company policies they actually disagreed with. Another student challenges this interpretation, wondering if that’s really false consciousness or just pragmatic survival. The instructor introduces a distinction that complicates both views. Someone references a film everyone happened to have seen. Through this dialogue, “false consciousness” stops being an abstract concept and becomes interwoven with the specific experiences and debates of this particular group.
By mid-semester, when someone in this class uses the term “false consciousness,” they are not just referencing Marx or the textbook definition. They are invoking the entire history of how this concept has been explored, challenged, and reconstructed within their unique dialogic community. The meaning has been enriched and particularized through their collective engagement. An AI system, no matter how sophisticated, cannot access this localized, emergent meaning. It knows the textbook definition, perhaps thousands of scholarly discussions of the term, but it cannot know what “false consciousness” means in the context of this specific classroom’s ongoing dialogue.
This localized meaning-making extends beyond individual concepts to encompass entire ways of thinking and arguing. Each class develops its own intellectual style, its own standards for what counts as a good argument, its own recurring themes and concerns. A literature class might develop a running debate about whether authorial intention matters, with certain students becoming known for particular positions, creating a complex dialogic backdrop against which every new text is read. An engineering course might establish particular ways of approaching problems, shorthand notations that make sense only to those who were present when they were developed, shared assumptions about what kinds of solutions are elegant versus merely functional.
The temporal dimension of this process is crucial. Unlike a textbook or an online course, which presents information in a fixed sequence, classroom dialogue unfolds in real time with all the contingency that entails. A question asked at just the right moment can redirect an entire semester’s worth of inquiry. A misunderstanding that gets worked through collectively can become more instructive than any planned lesson. The specific order in which ideas are encountered, the particular connections that get made, the unexpected tangents that prove fruitful—all of this creates a learning trajectory that could not have been predicted in advance and cannot be replicated.
This is what Robin Alexander captures in his framework of dialogic teaching when he emphasizes the “cumulative” nature of classroom talk. Learning in a dialogic classroom is not a series of discrete lessons but a continuous building process where each conversation adds layers to what came before. Tuesday’s discussion is shaped by Monday’s, and Wednesday’s will build on both. This cumulative quality means that missing a class is not just missing information, it is missing a step in an ongoing collective thought process.
The social dynamics of the classroom add another layer of complexity that no AI can navigate. Students develop intellectual relationships with each other. They learn whose perspectives tend to challenge their own productively, whose questions usually lead to interesting places, or whose confusions mirror their own. They anticipate how certain classmates will respond to particular ideas and adjust their own contributions accordingly. A student might think, “I know Sarah will push back on this interpretation, so let me prepare for her objection,” or “This connects to what David was saying last week about alienation.”
These intellectual relationships are not incidental to learning but fundamental to it. When students know they will be engaging with the same group of peers over time, they invest differently in the dialogue. They build on each other’s ideas, return to unresolved questions, and develop shared intellectual projects. The classroom becomes a site of collaborative thinking where understanding emerges not from individual effort alone but from the sustained interaction of multiple perspectives.
The role of the instructor in this dialogic space is radically different from the traditional model of the teacher as information transmitter. Instead of being the sole source of knowledge, the instructor becomes what we might call a “dialogue facilitator” or “conversation architect.” They create the conditions for productive dialogue, introduce concepts and texts that will generate meaningful discussion, and guide the conversation in fruitful directions without dominating it. They model intellectual curiosity, demonstrate how to build on others’ ideas, and show what it means to change one’s mind in response to a compelling argument.
This shift requires instructors to embrace a certain intellectual humility. In a truly dialogic classroom, teachers must be prepared to have their own understanding transformed by student contributions. A student’s unexpected interpretation of a text the instructor has taught for years might reveal dimensions they had never considered. A question from someone new to the field might expose assumptions the expert has stopped noticing. This openness to being surprised, to learning alongside students rather than simply teaching to them, is essential to creating genuine dialogue rather than pseudo-dialogue where student contributions are merely opportunities for the instructor to deliver predetermined points.
The physical space of the classroom also plays a role in creating this unique universe of meaning. The arrangement of seats, the acoustics of the room, even the view from the windows become part of the shared context. Students develop preferred seats not just for comfort but because certain positions in the room afford particular kinds of participation. The student who sits where they can see everyone’s faces might become the one who notices and articulates emerging consensus. The one near the board might naturally take on the role of visual note-taker during complex discussions.
Even disruptions and failures become part of the classroom’s unique narrative. The day the technology failed and the class had to proceed without slides might become the day of the best discussion. The heated disagreement about interpretation that never got fully resolved might become a touchstone the group returns to throughout the semester. These shared experiences of working through difficulty together create bonds that are intellectual but also affective, generating the trust necessary for students to take intellectual risks.
The “supportive” principle in dialogic teaching is not just about being nice to each other. It is about creating an environment where students feel secure enough to think out loud, to offer half-formed ideas, to admit confusion, to change their minds publicly. This psychological safety is not a feel-good add-on to the actual work of learning but a fundamental prerequisite for the kind of exploratory dialogue through which understanding develops. Students need to know that their contributions will be taken seriously, that confusion is acceptable, that changing one’s mind is a sign of intellectual growth rather than weakness.
This supportive atmosphere stands in stark contrast to the adversarial dynamic created when education relies on algorithmic detection. Given the documented failures of such systems, the classroom shifts from a space of intellectual adventure to one of defensive performance, eroding the trust necessary for genuine dialogue.
The uniqueness of each classroom’s dialogic space also has implications for how we understand curriculum and standards. While learning objectives and outcomes can be standardized across institutions, the actual learning that occurs is always particular to the specific dialogic community in which it unfolds. Two sections of the same course, taught by the same instructor using the same materials, will develop different collective understandings based on the different configurations of voices present. This is not a failure of standardization but a recognition that deep learning is always contextual, always embedded in particular relationships and conversations.
This contextual embeddedness becomes a powerful tool for designing assessments that are inherently resistant to AI substitution. When assignments require students to engage with the specific dialogue of their classroom, generic AI-generated responses become immediately apparent as foreign intrusions. An essay prompt that asks students to “respond to the objection Miguel raised in Thursday’s discussion about whether art can be separated from the artist” cannot be meaningfully addressed by an AI that was not present for Miguel’s specific formulation of this concern, did not hear the examples he used, does not know the particular way this question has been explored in this classroom’s ongoing dialogue.
Assessing the Symphony, Not Just the Soloist
The traditional academic essay sits on a desk, complete and static, waiting to be graded. It represents what its author knew or thought at the moment of submission, frozen in twelve-point Times New Roman. The instructor reads it in isolation, perhaps weeks after it was written, divorced from the context of its creation. This document, we are told, demonstrates learning. But if Bakhtin is right about the dialogic nature of understanding, then this method of assessment is like judging a musician’s ability by examining a photograph of them holding their instrument. We see the pose but miss the performance. We evaluate the artifact but lose the music.
Robin Alexander’s framework of dialogic teaching offers a practical bridge between Bakhtinian theory and classroom practice. Alexander, a British educationalist who has spent decades studying classroom talk across cultures, identifies five principles that characterize genuinely dialogic teaching: it should be collective, reciprocal, supportive, cumulative, and purposeful. Each principle illuminates a different facet of how knowledge emerges through social interaction rather than individual production.
The collective principle recognizes that learning is a shared endeavor. Students and teachers address learning tasks together as a group rather than in isolation. This does not mean that individual thought disappears, but that it develops through participation in collective thinking. When a class works through a complex problem together, each person’s understanding is shaped by the contributions of others. A student might begin with a vague intuition that becomes clarified through another’s question, refined through a peer’s challenge, and crystallized through the group’s collective effort to articulate it precisely.
The reciprocal principle emphasizes that genuine dialogue requires participants to listen to each other, share ideas, and consider alternative viewpoints. This reciprocity distinguishes dialogue from serial monologue, where speakers simply take turns stating their pre-formed positions. In true dialogue, participants allow their thinking to be influenced by what they hear. A student enters a discussion believing one thing and leaves believing something more complex, not because they were told they were wrong but because the dialogue revealed dimensions they had not considered.
The supportive principle creates the conditions where students feel free to express ideas tentatively, to articulate confusion, and to take intellectual risks without fear of embarrassment. But this supportive atmosphere does not mean avoiding intellectual challenge. The most productive dialogic classrooms combine high support with high challenge, creating what we might call “demanding warmth.” Students feel safe enough to venture uncertain thoughts but are also expected to refine and defend them through reasoned argument.
The purposeful principle ensures that classroom dialogue has educational goals, though these goals may emerge and evolve through the dialogue itself rather than being rigidly predetermined. The teacher guides the conversation toward productive areas while remaining open to unexpected directions that prove fruitful. This requires a delicate balance between structure and spontaneity, between having clear learning objectives and allowing space for discoveries that could not have been expected.
But it is the cumulative principle that most directly challenges traditional assessment methods. Alexander emphasizes that dialogic teaching involves students and teachers building on their own and each other’s ideas, chaining them into coherent lines of thinking and understanding. Each lesson connects to previous ones, ideas develop over time, and understanding deepens through sustained engagement rather than one-off performances.
Consider how this cumulative building could happen in a semester-long seminar on environmental ethics. In week two, a student mentions their discomfort with putting economic value on endangered species. This comment sparks a discussion about different frameworks for valuing nature. By week five, when the class encounters a reading on ecosystem services, that prior discussion has become part of the shared intellectual background. Someone says, “This connects to what we were struggling with about economic valuation,” and everyone knows exactly what moment is being referenced. In week eight, a guest speaker’s presentation on indigenous land management practices causes the class to revisit and complicate their earlier conclusions. By week twelve, when students are developing their final projects, the phrase “the valuation problem” has become shorthand for a complex set of questions the class has been exploring all semester.
This cumulative development cannot be captured within a single final exam or paper. It exists in the progression, in the way understanding has been built through sustained dialogue. An AI system might write an essay about environmental ethics and economic valuation, drawing on countless sources. But it could not write about “the valuation problem” as this particular class has come to understand it through their specific journey of collective inquiry.
The temporal dimension of cumulative learning reveals why dialogue cannot be compressed or accelerated through technological shortcuts. Understanding develops through what we might call “intellectual seasons”—periods of growth, dormancy, breakthrough, and consolidation that follow their own organic rhythm. A concept introduced in September might lie dormant until November, when suddenly a new reading or discussion brings it back to life, now seen from a different angle. This kind of deep, transformative learning cannot be rushed. It requires the sustained engagement over time that dialogue provides.
The supportive principle deserves deeper examination because it addresses a common misconception about academic rigor. Some educators worry that emphasizing support and psychological safety leads to intellectual softness, a reluctance to challenge ideas or maintain standards. But Alexander’s research, along with decades of work in educational psychology, shows the opposite. Students take greater intellectual risks when they feel supported. They are more willing to engage with challenging ideas, to admit confusion, to change their minds when they trust that their struggles will be met with help rather than judgment.
This has profound implications for classroom dynamics in an age of algorithmic monitoring. Given the documented failures of detection software, the supportive foundation necessary for dialogue crumbles when students fear false accusations. They become guarded, strategic, and focused on avoiding suspicion rather than exploring ideas.
The reciprocal nature of dialogue also highlights what is lost when students outsource their thinking to AI. Reciprocity requires genuine responsiveness, the ability to be surprised, to have one’s thinking changed by an encounter with another perspective. When a student uses AI to generate a response to their peer’s ideas, they are not truly engaging in reciprocal dialogue. They are inserting a sophisticated but ultimately unresponsive piece of text into what should be a living conversation.
Furthermore, the collective nature of dialogic learning means that when one student uses AI to substitute for their own thinking, they deprive not just themselves but the entire learning community. Every genuine contribution to classroom dialogue potentially influences everyone else’s understanding. When someone offers an unexpected interpretation or makes a surprising connection, they create opportunities for collective discovery. An AI-generated contribution, no matter how polished, cannot provide this because it emerges from statistical patterns rather than a genuine engagement with the specific dialogue of the classroom.
The purposeful principle helps us understand why simply adding discussion to a traditional curriculum is not enough to create dialogic learning. Purpose in dialogue is not just about covering prescribed content but about pursuing understanding wherever it leads. This requires flexibility in curriculum design, allowing space for the unexpected directions that genuine inquiry might take. A literature class studying postcolonial fiction might find itself deep in discussion about contemporary immigration policy, not as a distraction but as a necessary exploration of how the literary texts speak to lived experience.
Alexander’s framework also helps us recognize that different types of dialogue serve different purposes in learning. There is exploratory talk, where students think aloud together, trying out ideas without yet committing to them. There is presentational talk, where students share more polished thoughts with an audience. And then there is evaluative talk, where the group assesses ideas and arguments. Each type requires unique skills and serves different functions in the cumulative building of understanding. Traditional assessment typically only values presentational talk in its written form—the polished essay—while ignoring the exploratory and evaluative dialogue through which understanding actually develops.
This interconnectedness of ideas in dialogue points to a fundamental issue with algorithmic approaches to academic integrity. Given the documented failures of AI detection, the very features that might trigger false positives, which include the integration of multiple perspectives, the echo of other voices, or the building on shared ideas, are actually signs of successful participation in dialogue.
The Problem with the Final Product
A student submits their final essay on economic inequality. The document is polished, properly cited, and argues persuasively that wealth concentration undermines democratic institutions. The instructor reads it, assigns a grade, and returns it with marginal comments. This transaction, repeated millions of times each semester across the globe, represents the dominant model of academic assessment. Yet from a Bakhtinian perspective, this entire process fundamentally misunderstands what learning is and how understanding develops.
The essay, sitting in the instructor’s inbox or on their desk, is what we might call a “frozen moment” in an ongoing process of meaning-making. It captures what the student could articulate at one particular point in time, under specific constraints, and divorced from the living dialogue that shaped their understanding. The text presents itself as complete, but understanding is never complete. It presents itself as individual, but understanding is always social. It presents itself as static, but understanding is inherently dynamic.
To grasp what is lost in this freezing process, consider the journey that likely preceded the essay’s creation. The student’s understanding of economic inequality did not spring forth fully formed. It developed through multiple conversations, both in and outside of class. Perhaps it began with a personal observation about their own community. This observation gained conceptual depth through engagement with course readings. Class discussion revealed complexities they had not considered. A peer’s question forced them to refine their position. The instructor’s feedback on an earlier draft pushed them to consider counterarguments. All of these dialogic encounters shaped the understanding that eventually found expression in the essay.
But the essay itself contains only traces of this rich dialogic process. The genuine intellectual work, the struggling with confusion, the moments of breakthrough, the productive disagreements, or the gradual refinement of ideas through social exchange—all that remains invisible. What gets assessed is not the learning process but its fossilized remains. The instructor evaluates the artifact without access to the intellectual journey that produced it, like a paleontologist trying to understand a living ecosystem from scattered bones.
This problem becomes more acute when we recognize that the traditional essay format actively obscures its dialogic origins. Academic writing conventions demand that students present their ideas as if they emerged through pure individual reasoning. The required authoritative voice suppresses uncertainty and exploration. The linear argument structure artificially smooths over the recursive, often messy process through which understanding actually developed.
Consider how differently we might understand a student’s learning if we had access to the full dialogic process. Imagine being able to trace how their position on economic inequality shifted through engagement with different voices. Perhaps they began with a simplistic view that inequality was purely negative. Through dialogue with conservative classmates, they came to understand arguments about incentives and innovation. Engagement with historical texts revealed how different societies have conceptualized fairness. Discussions with international students exposed them to different cultural perspectives on individual versus collective responsibility. The final essay might reach nuanced conclusions, but without seeing this dialogic journey, we cannot appreciate the depth of learning that occurred.
The temporal compression involved in essay assessment also distorts our understanding of student learning. The essay presents ideas as if they all exist simultaneously in the student’s mind, ready to be downloaded onto paper. But understanding develops through time, with ideas building on each other, earlier insights being revised by later ones, and connections emerging gradually through sustained engagement. The final document smooths over this temporal development, presenting a false simultaneity that masks the actual learning process.
Furthermore, the individual authorship assumed by the traditional essay misrepresents how understanding emerges in dialogic learning environments. In a vibrant classroom, ideas develop through collective inquiry. One student’s insight builds on another’s question, which was prompted by a third student’s confusion. The understanding that emerges belongs to the group as much as to any individual. When we demand that students write essays that are entirely “their own work,” we force them to artificially extract their thinking from the social matrix in which it developed.
The static nature of the essay also cannot capture the dynamic quality of genuine understanding. Real comprehension is not a fixed state but an ongoing capacity for dialogue. A student who understands economic inequality is not someone who possesses correct information about it but someone who can engage productively in ongoing conversations about it, responding to new perspectives, incorporating new evidence, and refining their position through continued dialogue. The essay, frozen at a moment in time, cannot demonstrate this dialogic capacity.
This critique extends to how essays are read and evaluated. The instructor, reading in isolation, brings their own dialogic history to the text. They interpret the student’s words through their own understanding, shaped by years of engagement with the topic. But without access to the specific dialogic context in which the student’s understanding developed, misinterpretation is almost inevitable. A phrase that seems clichéd to the instructor might represent hard-won insight for the student. An argument that appears underdeveloped might actually be sophisticated within the context of the classroom’s ongoing dialogue.
The problem is not simply technical but philosophical. The traditional essay embodies what Bakhtin would call a “monologic” conception of knowledge. It represents the idea that understanding can be contained within a single, unified voice. But if Bakhtin is correct that all understanding is dialogic, then this monologic form misrepresents what it claims to assess.
This philosophical mismatch helps explain why essay assessment has become so vulnerable to AI disruption. If we assess learning through individual, static textual products, then any technology capable of producing such products can substitute for the learning process. An AI system can generate an essay on economic inequality that meets all the formal requirements: clear thesis, supporting evidence, logical structure, proper citations. What it cannot do is participate in the dialogic process through which genuine understanding develops.
These limitations of final product assessment become even clearer when we consider what kinds of intellectual work it cannot recognize. The student who asks the question that redirects the entire class’s thinking receives no credit in traditional assessment. The student whose confusion leads to productive clarification for everyone goes unrecognized. And the student who excels at synthesizing diverse perspectives during discussion but struggles to write formal academic prose appears deficient. All of these valuable contributions to collective knowledge-building remain invisible when assessment focuses solely on individual final products.
This invisibility has ethical dimensions. When we assess only final products, we implicitly devalue the collaborative, social dimensions of learning. We send the message that the only intellectual work that matters is what can be claimed as individually authored. This not only misrepresents how understanding develops but also promotes an individualistic, competitive model of education that undermines the collaborative inquiry through which knowledge actually advances.
The focus on final products also creates perverse incentives for students. If only the essay counts, then the rich dialogue of the classroom becomes merely instrumental, valuable only insofar as it helps produce better individual writing. Students have little incentive to contribute to collective understanding if such contributions go unrecognized. They learn to hoard insights rather than share them, to view peers as competitors rather than collaborators.
These problems are not merely pedagogical but have broader implications for how students understand knowledge itself. When education consistently assesses learning through individual, static products, students internalize a model of knowledge as something to be possessed rather than something to participate in. They learn to think of understanding as having the right answers rather than being able to engage in productive dialogue.
This critique does not mean that writing has no place in education. Written reflection can be valuable for consolidating understanding, and the discipline of articulating ideas clearly in writing develops important capacities. But when the essay becomes the sole or primary form of assessment, when it is treated as the definitive demonstration of learning rather than one limited trace of a much richer process, we fundamentally misunderstand what education is about.
The alternative is not to abandon assessment but to develop forms that better recognize the dialogic nature of learning. This might involve assessing students’ participation in ongoing dialogue, their ability to build on others’ ideas, or their capacity to have their thinking transformed through engagement with different perspectives. It might mean evaluating portfolios that capture the development of understanding over time rather than single moments of production.
The rise of AI makes this shift from product to process not just pedagogically desirable but practically necessary. As machines become increasingly capable of generating polished textual products, the ability to produce such products becomes an increasingly poor proxy for genuine learning. But the capacity for authentic dialogue, for participating in the collective construction of meaning—these remain irreducibly human capabilities that no current AI can replicate.
Thank you for following Chapter 6 of this journey to its conclusion. If this chapter resonated with you, I hope you’ll continue with me as we explore what these dialogic principles mean in practice.
Next Saturday we begin Part 3 of the book, entitled “The Dialogic University,” with Chapter 7: ‘A Unified Dialogic Pedagogy.’ Having examined Socratic inquiry, Freirean problem-posing, and Bakhtinian dialogism across three separate chapters, we now draw these threads together into a coherent philosophy centered on a single powerful insight: authentic evidence of learning resides not in final products but in the process of articulation through which understanding emerges.
P.S. I believe transparency builds the trust that AI detection systems fail to enforce. That’s why I’ve published an ethics and AI disclosure statement, which outlines how I integrate AI tools into my intellectual work.