U.S. News & World Report and other organizations provide rankings of national universities, liberal arts colleges and regional universities, as well as specific colleges such as medicine, engineering, law and business. These rankings are very popular among prospective students, to discern which places to apply and which offer to accept. Alumni are also interested, given that the school that they graduated from has value based on its reputation and rank.
Yet all such rankings are fundamentally flawed and have limited value beyond the perception that they provide.
Rankings are based on scores computed from a set of attributes. Many of these attributes are quantitative, like graduation and retention rates, faculty resources and student selectivity. Other are qualitative, like academic reputation based on peer assessment.
The problem is that all such attributes must be combined into a single score using weights, which of themselves are highly subjective. This means that a different set of weights would produce a different score and a different ranking. The same holds true with the choice of attributes included in the rankings.
Some attributes are more favorable to private schools versus public schools, as well as the size of the school. Trying to define a single score across the diversity of colleges and universities is futile, and ultimately, misleading.
The rankings also do not take into account the margins of error with all scores, which means that schools 10 or more places apart in the ranking may not be all that different in terms of the quality of education that they provide. This difference may also be driven by just one attribute that may have little value to some students.
The problem becomes even more troubling when assessing colleges like medicine, engineering, law and business.
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Take for example colleges of engineering graduate schools. Attributes that compromise the score includes both total research expenditures and research expenditures per faculty, student-to-faculty ratios and percentage of faculty in the National Academy of Engineering. These are quantifiable measures that every college of engineering can compute. They can also be gamed based on how the denominator (number of faculty) are defined.
There are also qualitative factors like peer assessment and recruiter assessment scores.
The problem with many of these attributes is that they are based on averages. Focusing on averages guarantees mediocrity. Excellence is achieved at the extremes, not with averages. Faculty who are high end outlier performers enhance and elevate the reputation of a college.
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Maximizing these “average” attributes may also become the goal of a college, rather than the byproducts of striving for excellence. As now defined, the attributes can drive incentives and programs that are not fully aligned with achieving excellence.
The other factor that the attributes do not capture is diversity of thought. Faculty are independent thinkers. Defining a rigid set of attributes that do not capture the diversity of activities and contributions of faculty and programs hinders innovation and creativity. The net cost of such rigidity is a movement towards group thinking, which further guarantees mediocrity.
Top ranked engineering schools such as MIT and Stanford do not need rankings to measure the excellence that they offer. At the same time, for some talented students, other schools may be a better fit for them, based on alternative attributes that fit their persona.
There is a need for students to evaluate every school they are considering. If all rankings magically disappeared, what could fill the resulting void?
Instead of combining a laundry list of attributes into a single score, provide students with the ability to pick those attributes that are important to them and create a pool of schools that have favorable scores for those attributes.
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If a person wants a low student-faculty ratio, then smaller private schools will likely be attractive. If they want a large and active Greek system, then large public schools may be a good choice.
When students seek to get into the best school they can, they must define what they mean by best. If they do not, then the ranking organizations are doing it for them.
Rankings provide bragging rights for some schools. Yet they do a disservice for obfuscating the best features that make every school special and unique in some way. Creating a data base of numerous attributes allows prospective students to better evaluate prospective schools and shine a bright light on those that best serve their interests and needs.
Sheldon H. Jacobson, Ph.D., is a professor in computer science at the University of Illinois Urbana-Champaign. A data scientist, he applies his expertise in data-driven risk-based decision-making to evaluate and inform public policy.
