The hallmark of a Harvard education, it is argued, is its commitment to a liberal arts curriculum—one that is not wedded to preprofessional or vocational utility, but the development of the well-rounded individual. In the words of the Final Report of the Task Force on General Education (Gen Ed), a liberal arts education aims to “unsettle presumptions, to defamiliarize the familiar, to reveal what is going on beneath and behind appearances, to disorient young people and to help them find ways to reorient themselves.” To that end, the new program in General Education seeks not only to push students to understand material outside their concentration, but also to provide a curriculum that is “responsive to the conditions of the twenty-first century.”

Regardless of what we choose to concentrate in, this liberal arts curriculum purports to challenge us to confront different cultures and beliefs, to parse through ethical dilemmas, to reason with empirical evidence, to learn about the sciences of the physical worlds, and to reflect upon our country’s relationship to the rest of the world. To equip us to tackle these subjects, we are required to take Expository Writing in our first year, in addition to a foreign language—both of which allow us to better engage with most areas of Gen Ed’s inquiry. But for too many students, one area of knowledge remains unexplored—mathematics.

Trapped between Core Courses that too often skirt rigorous mathematics and intimidating departmental courses, students in non-quantitative disciplines are largely ill-equipped to work with numbers.

By contrast to concentrators in the natural sciences who are exposed to literature and social theory, those in the softer sciences and humanities can, and too often do, spend their four years fleeing natural logs and derivatives. What distinguishes this problem from the converse—of math and science concentrators in humanities and social science classes—is not only the poor content of Quantitative Reasoning (QR) Core courses, but also the extent to which mathematical knowledge relies largely upon the ability to execute certain basic numerical techniques.

Students unfamiliar with literary theory can still engage with texts written in a language they understand, but those rusty on their calculus are perplexed by basic notation like delta, theta, and epsilon. As a result, many literature and history Core courses are deemed substantive enough to qualify for departmental credit. But no QR Core makes the cut for the math or statistics departments.

While previous generations may not have required a strong background in math and science to be considered informed citizens, today’s world has lived up to the vision of H.G. Wells: It is one in which statistical thinking is “as necessary for efficient citizenship as the ability to read and write.” The relevance of mathematics to understanding contemporary policy issues, healthcare, and the modern conception of human nature is increasingly clear. Students who want an in-depth understanding of everything from behavioral economics to education policy require more than a superficial level of proficiency with numbers.

Now more than ever, people employ data-backed arguments, even to tackle the problems once addressed by the other fields. Just 100 years ago, the mystery of human happiness was a question for poets and theorists, but today, we take heed of empirical studies correlating happiness to job security and relative wealth. Now, even the moral dilemmas of altruism are modeled by behavioral economists interested in quantifying the extent to which people are averse to inequality. In order for the social theorist or ethicist to develop such models, however, certain foundational mathematical skills are necessary. Questions of scientific inquiry—from global climate change to the impact of cell phone usage on brain tumors—have become ever relevant to our daily lives; if we are to make informed decisions about issues at the intersection of science and policy, we can’t be daunted by empirical argumentation.

The College, however, does little to prepare students for this charge. While the current core’s QR requirement boast classes such as QR50: Medical Detectives and QR46: The Visual Display of Numbers, no class teaches a range of foundational topics—from statistical reasoning to model building—for the non-concentrator to learn. Introductory statistics courses, which are required by many empirical social sciences, cover the former, but leave one unacquainted with the calculus needed to build models. Math departmental courses, on the other hand, are heavy on calculus, usually so much so that students who don’t have an intense interest don’t bother to take the class. These two poles leave students lacking a middle ground between the courses aimed at concentrators and fluffier Core classes that do little to prepare students for subsequent coursework.

Rather than banish students to this no man’s land, the Faculty should aim to develop a foundational course required of all students not exempt from their QR requirement. Such a course would be devoted to equipping students with both the statistical vocabulary and the higher math techniques needed to navigate both policy- and model-oriented courses. Taken during students’ first year, this course would prepare students for the twenty-first century.

Hope may lie in the new Gen Ed program, whose requirements recognize that “empirical reasoning is not a discrete body of knowledge” but “a set of related conceptual skills that guide valid reasoning and decision-making.”

Until the Faculty really adopts such an initiative, however, our optimism must be tempered. The reported inertia and apathy in new course development may yet condemn students to recast versions of the hollow Cores. As of yet, no new courses have been created under this Gen Ed category. Of existing courses approved to count for credit, only one, Mathematics 154: Probability Theory (which even Gen Ed Committee chair Jay R. Harris admits most students are never going to take), is not a hold-over from the Core.

If the University is truly committed to a liberal arts education, it can no longer afford to ignore the growing importance of mathematics and statistics. Literacy as a prerequisite to good citizenship in modern society must expand its demands, such that even scholars of postcolonial theory or adherents of Rawls remember how to manipulate simple derivatives and infer conclusions from a statistical t-test.

Ramya Parthasarathy ’09, a Crimson editorial chair, is a social studies concentrator in Winthrop House.

Regardless of what we choose to concentrate in, this liberal arts curriculum purports to challenge us to confront different cultures and beliefs, to parse through ethical dilemmas, to reason with empirical evidence, to learn about the sciences of the physical worlds, and to reflect upon our country’s relationship to the rest of the world. To equip us to tackle these subjects, we are required to take Expository Writing in our first year, in addition to a foreign language—both of which allow us to better engage with most areas of Gen Ed’s inquiry. But for too many students, one area of knowledge remains unexplored—mathematics.

Trapped between Core Courses that too often skirt rigorous mathematics and intimidating departmental courses, students in non-quantitative disciplines are largely ill-equipped to work with numbers.

By contrast to concentrators in the natural sciences who are exposed to literature and social theory, those in the softer sciences and humanities can, and too often do, spend their four years fleeing natural logs and derivatives. What distinguishes this problem from the converse—of math and science concentrators in humanities and social science classes—is not only the poor content of Quantitative Reasoning (QR) Core courses, but also the extent to which mathematical knowledge relies largely upon the ability to execute certain basic numerical techniques.

Students unfamiliar with literary theory can still engage with texts written in a language they understand, but those rusty on their calculus are perplexed by basic notation like delta, theta, and epsilon. As a result, many literature and history Core courses are deemed substantive enough to qualify for departmental credit. But no QR Core makes the cut for the math or statistics departments.

While previous generations may not have required a strong background in math and science to be considered informed citizens, today’s world has lived up to the vision of H.G. Wells: It is one in which statistical thinking is “as necessary for efficient citizenship as the ability to read and write.” The relevance of mathematics to understanding contemporary policy issues, healthcare, and the modern conception of human nature is increasingly clear. Students who want an in-depth understanding of everything from behavioral economics to education policy require more than a superficial level of proficiency with numbers.

Now more than ever, people employ data-backed arguments, even to tackle the problems once addressed by the other fields. Just 100 years ago, the mystery of human happiness was a question for poets and theorists, but today, we take heed of empirical studies correlating happiness to job security and relative wealth. Now, even the moral dilemmas of altruism are modeled by behavioral economists interested in quantifying the extent to which people are averse to inequality. In order for the social theorist or ethicist to develop such models, however, certain foundational mathematical skills are necessary. Questions of scientific inquiry—from global climate change to the impact of cell phone usage on brain tumors—have become ever relevant to our daily lives; if we are to make informed decisions about issues at the intersection of science and policy, we can’t be daunted by empirical argumentation.

The College, however, does little to prepare students for this charge. While the current core’s QR requirement boast classes such as QR50: Medical Detectives and QR46: The Visual Display of Numbers, no class teaches a range of foundational topics—from statistical reasoning to model building—for the non-concentrator to learn. Introductory statistics courses, which are required by many empirical social sciences, cover the former, but leave one unacquainted with the calculus needed to build models. Math departmental courses, on the other hand, are heavy on calculus, usually so much so that students who don’t have an intense interest don’t bother to take the class. These two poles leave students lacking a middle ground between the courses aimed at concentrators and fluffier Core classes that do little to prepare students for subsequent coursework.

Rather than banish students to this no man’s land, the Faculty should aim to develop a foundational course required of all students not exempt from their QR requirement. Such a course would be devoted to equipping students with both the statistical vocabulary and the higher math techniques needed to navigate both policy- and model-oriented courses. Taken during students’ first year, this course would prepare students for the twenty-first century.

Hope may lie in the new Gen Ed program, whose requirements recognize that “empirical reasoning is not a discrete body of knowledge” but “a set of related conceptual skills that guide valid reasoning and decision-making.”

Until the Faculty really adopts such an initiative, however, our optimism must be tempered. The reported inertia and apathy in new course development may yet condemn students to recast versions of the hollow Cores. As of yet, no new courses have been created under this Gen Ed category. Of existing courses approved to count for credit, only one, Mathematics 154: Probability Theory (which even Gen Ed Committee chair Jay R. Harris admits most students are never going to take), is not a hold-over from the Core.

If the University is truly committed to a liberal arts education, it can no longer afford to ignore the growing importance of mathematics and statistics. Literacy as a prerequisite to good citizenship in modern society must expand its demands, such that even scholars of postcolonial theory or adherents of Rawls remember how to manipulate simple derivatives and infer conclusions from a statistical t-test.

Ramya Parthasarathy ’09, a Crimson editorial chair, is a social studies concentrator in Winthrop House.

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