Expensive assessment

One metric for evaluating automated scoring is to compare it against human scoring. For some domains and test formats (e.g., multiple-choice items on factual knowledge), automation has an accepted advantage in objectivity and reliability, although whether such questions assess meaningful understanding is often debated. With more open-ended domains and designs, human reading is typically considered superior, allowing room for individual nuance to shine through and get recognized.

Yet this exposé of some professional scorers’ experience reveals how even that cherished human judgment can get distorted and devalued. Here, narrow rubrics, mandated consistency, and expectations of bell curves valued sameness over subtlety and efficiency over reflection. In essence, such simplistic algorithms resulted in reverse-engineering cookie-cutter essays that all had to fit one of their six categories, differing details be damned.

Individual algorithms and procedures for assessing tests need to be improved so that they can make better use of a broader base of information. So does a system which relies so heavily on particular assessments that the impact of their weaknesses can get magnified so greatly. Teachers and schools collect a wealth of assessment data all the time; better mechanisms for aggregating and analyzing these data can extract more informational value from them and decrease the disproportionate weight on testing factories. When designed well, algorithms and automated tools for assessment can enhance human judgment rather than reducing it to an arbitrary bin-sorting exercise.

Standardized tests as market distortions

Some historical context on how standardized tests have affected the elite points out how gatekeepers can magnify the influence of certain factors over others– whether through chance or through bias:

In 1947, the three significant testing organizations, the College Entrance Examination Board, the Carnegie Foundation for the Advancement of Teaching and the American Council on Education, merged their testing divisions into the Educational Testing Service, which was headed by former Harvard Dean Henry Chauncey.

Chauncey was greatly affected by a 1948 Scientific Monthly article, “The Measurement of Mental Systems (Can Intelligence Be Measured?)” by W. Allison Davis and Robert J. Havighurst, which called intelligence tests nothing more than a scientific way to give preference to children from middle- and upper-middle-class families. The article challenged Chauncey’s belief that by expanding standardized tests of mental ability and knowledge America’s colleges would become the vanguard of a new meritocracy of intellect, ability and ambition, and not finishing schools for the privileged.

The authors, and others, challenged that the tests were biased. Challenges aside, the proponents of widespread standardized testing were instrumental in the process of who crossed the American economic divide, as college graduates became the country’s economic winners in the postwar era.

As Nicholas Lemann wrote in his book “The Big Test,” “The machinery that (Harvard President James) Conant and Chauncey and their allies created is today so familiar and all-encompassing that its seems almost like a natural phenomenon, or at least an organism that evolved spontaneously in response to conditions. … It’s not.”

As a New Mexico elementary teacher and blogger explains:

My point is that test scores have a lot of IMPACT because of the graduation requirements, even if they don’t always have a lot of VALUE as a measure of growth.

Instead of grade inflation, we have testing-influence inflation, where the impact of certain tests is magnified beyond that of other assessment metrics. It becomes a kind of market distortion in the economics of test scores, where some measurements are more visible and assume more value than others, inviting cheating and “gaming the system“.

We can restore openness and transparency to the system by collecting continuous assessment data that assign more equal weight across a wider range of testing experiences, removing incentives to cheat or “teach to the test”. Adaptive and personalized assessment go further in alleviating pressures to cheat, by reducing the inflated number of competitors against whom one may be compared. Assessment can then return to fulfilling its intended role of providing useful information on what a student has learned, thereby yielding better measures of growth and becoming more honestly meritocratic.

Using personalized assessment to change the high-stakes testing culture

Criticisms of high-stakes tests abound as we usher in the start of K-12 testing season. Students worry about being judged on a bad day and note that tests measure only one kind of success, while teachers lament the narrowing of the curriculum. Others object to the lack of transparency in a system entrusted with such great influence.

Yet the problem isn’t tests themselves, but relying on only a few tests. What we actually need is more information, not less. Ongoing assessment collected from multiple opportunities, in varied contexts, and across time can help shield any one datapoint from receiving undue weight.

Personalized assessment goes further in acknowledging the difference between standardization in measurement (valuable) and uniformity in testing (unhelpful). Students with different goals deserve to be assessed by different standards and methods, and not arbitrarily pitted against each other in universal comparisons. Gathering more data from richer contexts that are better matched to students’ learning needs is a fundamental tenet of personalization.