The Industrial University is a Dead End
Why Efficiency Has Become Higher Education’s Greatest Vulnerability
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Over the past several months, I have published a series of articles exploring what AI-resistant assessment might look like in an era of machine automation. Many solutions I have proposed, such as authentic assessments rooted in specific contexts or dialogic assessments built on sustained conversation, share a common thread. They demand something that our current educational infrastructure was explicitly designed to minimize: extended, individualized human contact between teachers and students.
The response to these proposals has been consistent and predictable. In conference discussions, comment sections, and email exchanges, educators have asked me some variation of the same question: “This sounds wonderful, but can I implement dialogic assessment when I teach three sections of 120 students each?”
My answer, increasingly, is that you cannot.
This is not a failure of imagination or pedagogical skill. The incompatibility runs deeper. What the emergence of AI has made acutely visible is that the strategies required to preserve meaningful education in an age of automated content production are fundamentally incompatible with the industrial model of education that has shaped our institutions for more than a century. This incompatibility is therefore not a pedagogical problem. It is an economic one. Understanding why requires examining how we arrived at this particular structural arrangement in the first place.
The Architecture of Scale: How Education Became Industrial
The modern university did not develop naturally into its current form. It was engineered according to specific principles borrowed from industrial manufacturing, principles that prioritized standardization and scalability above all else. The system we inhabit today is an artifact, constructed through deliberate choices made over decades. To understand its current fragility, we must first understand its construction. The following historical analysis tells the story of the US higher education system, but the same principles apply globally.
Prussian Foundations: The Standardization of Time
The American adoption of the Prussian educational model in the mid-19th century introduced what manufacturing would call “batch processing” to schooling. When Horace Mann, Secretary of the Massachusetts Board of Education, visited Prussia in 1843, he observed a system that had solved the logistical challenge of mass education through standardization. Students were sorted by age, moved through a uniform curriculum in annual cohorts, and assessed using common measures.
Prior to this intervention, education was erratic and individualized. The Prussian innovation made universal education administratively possible by treating students as interchangeable units moving through a standardized sequence. Every tenth-grader reads the same text at the same time, making it efficient to assess them all using the same techniques. The system assumed that if inputs (curriculum) and processes (time in class) were standardized, outputs could be standardized as well.
This structure enabled scale. Without uniform processing of students, the massive expansion of public education envisioned by democratic reformers would have been logistically impossible. But it also embedded a fundamental dependence: the entire system’s efficiency relied on the premise that standardized assessments could reliably measure learning.
The Cult of Efficiency: When Schools Became Factories
The decisive transformation occurred in the early 20th century during what historian Raymond Callahan documented as the “Social Efficiency Movement.” Influenced by Frederick Winslow Taylor’s principles of scientific management, which sought to optimize industrial production by breaking work into its smallest measurable components, educational administrators began viewing schools as factories and students as raw materials to be processed into finished products.
Taylorism demanded the separation of planning from execution. In factories, this meant managers designed workflows while laborers executed them. In schools, this produced a hierarchy where administrators set policy and teachers implemented standardized curricula, transforming faculty from autonomous intellectuals into managed laborers.
The efficiency movement required measurement. Schools were evaluated through surveys that assessed cost per student and facility utilization rather than intellectual depth or student growth. Standardized testing proliferated because it provided the quantifiable data needed to show efficiency to boards and taxpayers. This shift privileged forms of knowledge that were easily measurable—recall or procedural application—over those that were complex and idiosyncratic, such as critical thinking, synthesis, or creativity.
The system was optimized for assessability. The five-paragraph essay, the problem set, the research paper with standardized citation format—these artifacts were designed to be efficiently graded at scale. Their form mattered more than their substance, because form could be evaluated consistently across thousands of students by interchangeable graders.
The Currency of Scale: The Carnegie Unit
If the factory model provided the structure, the Carnegie Unit provided the currency. Introduced in 1906 by the Carnegie Foundation for the Advancement of Teaching as a mechanism to standardize faculty pensions, it defined academic credit based on “seat time”—approximately 120 hours of contact per year.
This invention accomplished three things, each with lasting consequences. First, it established time as a proxy for learning, decoupling credit from demonstrated competence and attaching it instead to exposure. You earn credit for being present, not for what you can do. Second, it made education interchangeable. Credits became commodities that could be banked, transferred, and accumulated across institutions. Third, it created the Student Credit Hour, the fundamental unit for state funding, faculty workload calculation, and tuition revenue. Universities could now treat education as inventory, calculating capacity by multiplying classroom seats by contact hours.
This infrastructure enabled the dramatic expansion of higher education in the 20th century. It also created a system where success was measured by throughput rather than transformation. When education is measured in seat time and demonstrated through standardized outputs, the system can scale indefinitely, as long as those outputs remain credible proxies for learning.
The Economic Trap: Commodifying the Inefficient
A key issue with the industrial model, which worsened in the late 20th century, was that efforts to make teaching more efficient risked undermining the quality of education. This phenomenon, known as Baumol’s Cost Disease, explains why higher education costs have risen inexorably even as class sizes have grown.
