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Larry Cuban, historian of education and former teacher, revisits a long-standing dilemma in public education: teaching to the middle of the class. While critics often equate this practice with mediocrity, Cuban argues that it reflects structural realities of U.S. schooling and the complex compromises teachers must make in age-graded, mixed-ability classrooms.
📖 Full article here: Larry Cuban on School Reform and Classroom Practice
Cuban begins with the voice of a middle school math teacher (2005) who recognized that, despite efforts to support all students, she often ended up teaching to the middle. She worried most about students at the bottom, who required extra guidance but often lacked motivation or strategies to succeed. While she tried small groups, extra credit, and one-on-one support, limited time and resources prevented her from fully meeting all students’ needs.
Cuban connects this reflection to his own experience as a high school teacher in the mid-20th century. Despite working in tracked schools—where students were divided into “Honor,” “College Preparatory,” “General,” and “Basic” tracks—he, too, unconsciously gravitated toward the middle. His lessons, questions, and pacing generally targeted students just above average, leaving some excelling without challenge and others struggling without enough support.
Cuban identifies the dilemma as deeply embedded in the DNA of U.S. public schools. Teachers balance three often conflicting values:
Equity: treating all students fairly.
Excellence: encouraging high achievement.
Community: building cohesive classroom environments.
In practice, age-graded schools with large classes and fixed schedules make it nearly impossible to achieve all three. Teachers must make trade-offs, and one compromise is aiming instruction at the middle.
Two powerful forces reinforce this tendency:
The bell curve mindset: Society equates the “average” with mediocrity, assuming unequal distribution of intelligence and performance is natural. Teachers internalize this, structuring classes with expectations that most students will land in the middle.
The grading system: Letter grades, honor rolls, and class rankings institutionalize stratification, rewarding a few at the top while implicitly labeling the majority as “average.”
Cuban rejects the idea that teaching to the middle is synonymous with mediocrity. He argues that mediocrity implies poor quality or lack of effort, while teaching to the middle reflects systemic constraints. Teachers are often doing the best they can within rigid structures of time, class size, and accountability demands.
He cautions against labeling “average” students—or the teachers who primarily serve them—as failures. Instead, he calls for acknowledging the compromises inherent in public schooling.
Cuban pushes educators to consider a larger issue: Does the structure of schooling reproduce inequality, or can it help reduce it?
Current systems—tracking, letter grades, age-based grouping—tend to reinforce social hierarchies. Yet Cuban argues schools also have the potential to disrupt inequality if structures were redesigned. For instance:
Flexible grouping strategies.
Alternative grading practices.
Rethinking age-based advancement.
Such reforms, however, require systemic changes far beyond individual teachers’ control.
Teaching to the middle is not failure. It’s a response to structural limits, not a sign of laziness or lack of talent.
Be intentional with supports. While teachers cannot fully individualize learning in current systems, small strategies—grouping, targeted feedback, enrichment projects—can reach more students.
Challenge the bell curve mindset. Valuing growth and effort over fixed distributions reframes what counts as success.
Advocate for systemic change. Real equity requires rethinking the structures that make teaching to the middle inevitable.
Ultimately, Cuban reminds us that teachers face an impossible balancing act, but their daily compromises reflect care and professionalism, not mediocrity.
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Prepared with the assistance of AI software
OpenAI. (2025). ChatGPT (4) [Large language model]. https://chat.openai.com
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