Test Scores — Optional or Not? Data on Outcomes Can Help You Decide

Steve Hahn, Ben Chrischilles

In Brief

6-Minute Read

The pandemic year put the standardized test requirement debate into a new context. Fewer opportunities for students to take the SAT or ACT meant many colleges and universities eliminated score requirements for applications, inadvertently adding themselves to the “test-optional” discussion. Many have already adopted or are considering adopting a test-optional policy going forward. At last count, nearly 1,350 colleges and universities have become test-optional or no longer require standardized test scores; some states are actively considering legislation to eliminate test score requirements at public systems.

Key Takeaways

  • Proponents of the test-optional approach say that standardized assessments result in score patterns that reveal more about K-12 educational opportunities than ability.

  • Critics suggest that scores are a way to measure academic aptitude that can be used to predict collegiate success and determine grants and financial aid.

  • Determining whether a long-term test-optional strategy is right for an institution depends on its specific mission and goals but should utilize existing and new data and modeling scenarios.

Proponents of the test-optional approach argue that standardized assessments have long been known to accentuate differences associated with socioeconomic backgrounds, resulting in score patterns reflecting different K-12 educational opportunities. In response, some believe that removing test scores from admissions reviews would level the playing field.

Others suggest that scores remain important as one element among available diagnostic tools for assessing applicants. These proponents maintain that scores offer a measure of academic aptitude that is predictive of collegiate success as well as objective criteria for determining grants and financial aid. In addition, there are practical concerns attendant to recruiting and yielding students when many more of them than before are not including themselves in standardized testing (and demographic) data traditionally sent to schools throughout the year.

There are compelling cases for each viewpoint, and what’s right for one institution may not be right for another. When assessing whether to adopt a permanent policy with respect to test scores in the admission application process at your institution, consider data-driven insights about the student body, as well as academic portfolio and peer benchmarks, to make strategic decisions that both align with your institution’s specific goals and mitigate the risks of potential bias.

Capitalize on New Data to Focus on Outcomes

The 2021 entering freshman class can now serve as a critical benchmarking opportunity for assessing the effects of a test-optional approach for institutions that currently have the data to examine over time.

Institutions that laid the foundation last year (or have access to recent data) can establish baseline admissions criteria and then track the experiences and success of incoming students who applied with and without test scores as they progress through their collegiate experiences. To gauge how students admitted without the use of scores during the test-optional period compare with students who matriculated before the pandemic, colleges and universities must determine which criteria should be used to contrast the two populations fairly.

The institutions that can monitor and track these two populations will emerge better prepared to admit future incoming classes and make more informed decisions about whether a test-optional policy makes sense.

Ask Strategic Questions

Removing SAT and ACT scores from admissions criteria led many schools to have an influx of applications from students who might not otherwise have applied. This is a positive outcome if institutions thoughtfully consider new approaches to the available admissions data and have a strategy for assessing applicants that adequately serves the best interests of both the students and the institution. Criteria can include more nuanced reviews of high school GPAs, careful calibration of school rankings, the number of Advanced Placement courses taken, insightful assessment of extracurricular activities and other factors.

Still, some speculate that removing test scores might set both the student and the institution up for failure by opening the door for some students who are less prepared to handle academic rigor, leading to increased student stopouts and poorer graduation rates. Another perspective suggests that it might reveal test scores were not a strong predictor of student success at institutions after all, thereby opening opportunities for new cohorts of students both now and in the future.

Now is the perfect time to begin the assessment of these competing hypotheses. Anticipating the long-term impacts of whether a test-optional policy is right for your institution involves asking stakeholders key questions:

  • What data have already been used holistically in the absence of test scores? How might the institution weigh alternate criteria?
  • Did your institution attract students who would not have previously applied?
  • How can stakeholders fairly compare classes formed during a test-optional period against previous classes? What changes in the class composition should be measured?
  • Should the institution use optional standardized test scores as a recruitment strategy rather than an admissions requirement?
  • What other criteria could be used to determine scholarships and financial aid awards?
  • What are the reputational impacts of this decision long term?
  • What are competitors/peer institutions doing, and how might their strategies affect your institution?
  • What will test-optional students’ outcomes look like? Have they struggled to keep up or had higher dropout rates, or are there no significant differences so far? (Remember that a year of largely remote classes will not make for exact comparisons.)
  • How might this decision impact your institution’s long-term enrollment goals?

Using a data-driven approach to answer these questions can help align campus leaders and boards, as well as set institutions and their students up for long-term success.

Model Scenarios and Benchmark

When considering whether to adopt a test-optional policy permanently, it is critical to model a range of scenarios. How might using GPA and high school rankings as proxies for standardized test scores affect graduation and retention rates? Do those rates differ if the institution uses a different set of selection criteria? If our competitors remain test-optional, how might that affect our applicant pool and/or enrollments?

Educational leaders can find answers to these questions and others by merging historical student data with predictive analytics, to project both near-term enrollments and long-term outcomes. The approach involves assessing the data objectively, overlaying peer benchmarks, extrapolating impacts and aligning recommendations based on the institution’s specific mission and goals.

Determining whether a long-term test-optional strategy is right for an institution depends on its specific mission and goals. Last year’s entering class presents a unique opportunity to track and measure the success of students admitted; therefore, it is important that leaders lay the framework today for acquiring data that will be instrumental in shaping the future.


To prepare for a new landscape where some institutions will be implementing a test-optional policy in the future, leaders must:
  • Think differently.
    Consider what new approaches to existing admissions data may be available to develop an expanded strategy for assessing applicants. Evaluate the impact of these new practices to adequately serve the best interests of students and the institution.
  • Plan differently.
    Engage relevant stakeholders, including academic and student support leaders, in determining the implications of possible changes in student needs and academic preparation associated with changes in the admissions evaluation process.
  • Act differently.
    Build a robust data analytics model into the evaluation of student characteristics and academic needs to provide your institution with durable insights into student success characteristics.

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