In most schools across the country, students are assessed by achievement tests. These tests are used for many purposes, including gauging students’ progress as well as judging teachers’ and schools’ performance. To do well on an achievement test requires practice on specific skills, from reading fluently to knowing times tables. Access to excellent teachers, strong curriculum and academic support at home can increase performance on achievement tests.
Because these scores are readily available, many schools try to use the same data for yet more purposes, including identifying students for advanced or accelerated learning opportunities. But there is growing evidence that relying on achievement data alone is not an equitable practice because it excludes too many students from enrichment and advanced academic opportunities and creates a unidimensional view of students’ capabilities.
Ability data, on the other hand, provides educators a fresh and meaningful way to understand each student’s unique potential for learning and enables differentiated instruction based on individual needs. A cognitive abilities test measures a students’ potential for learning, using word, number and spatial puzzles. Measuring a student’s ability– also called aptitude or student potential for learning – provides insight into students’ readiness to demonstrate creative problem-solving skills and learn in different situations and environments.
As educators, it’s time to flip the script on how we teach students. Let’s think less about retaining knowledge and mastering skills and more about how a student thinks and solves problems. This will lead to more confident learners, which drives greater personal growth and long-term success.
Combining Ability AND Achievement
Combining ability and achievement data yields powerful results. Together, these results help teachers understand gaps in potential and performance, which increases equity by gauging every student’s learning capacity.
If a student has high ability, does well in the classroom and their achievement scores are high, it is fairly easy to identify the student for advanced services, such as gifted education programs. Sometimes, however, student achievement data does not reflect cognitive talents.
Students with “mismatches” in potential and performance are often students who have different ways of learning, feel disenfranchised in the classroom or are impacted by home or socioeconomic challenges. In order to provide equal opportunities, it is critical to have multiple measures – such as ability testing alongside achievement data – to help properly assess all students.
From a broader perspective, understanding student ability data can help educators differentiate instruction to personalize the classroom and maximize students’ potential. If teachers have information about a student's current achievement level, as well as insight into their ability to learn, they can adjust teaching strategies and align instruction with how students learn best.
For example, teachers can leverage small groups and flexible-ability grouping, which enables students to work independently or with a small group of students that need similar types of instruction. Or, if there are students who are not meeting achievement goals and are slower learners in certain domains, teachers can provide personalized structure and support to achieve the desired goals.
How Understanding Ability Improves Equitable Instruction
Take, for example, two fifth-grade students, both African American boys. Low state achievement scores held them back, yet both are extraordinarily talented in different ways.
One student loves to read and loves science. His teacher has a hunch that he is more capable than his achievement scores demonstrated. He is likely a verbal learner. Yet, without ability data, there was no way to gain insights into which differentiated instruction approach would be best for him.
The other student loves to draw, make buildings and tell stories about his designs. He may not have strong achievement scores, but could demonstrate exceptional figural or spatial understanding.
Ability testing would illuminate these talents, and allow teachers to explain math in different ways, such as using manipulatives or suggesting visual strategies for learning, and providing extra time on assessments to create the “mental models” he needs to solve the problems.
In the end, definitive ability data on these students could help teachers adapt instruction to meet their learning needs. And, ultimately, they could have done much better on achievement assessments with instruction better aligned to the way they processed information.
Overcoming Testing Inequities
Tests are a mirror of society, so unfortunately the inequities in education and access to quality education are reflected in these exams. Some students are in educational environments that are less resourced or more focused on basic skills, just because of where they're born, the tax policies of their school district, their family, their race and their background.
As a result, the test results for many of these students reflect factors outside of their or their teacher’s control, and lead to less opportunity to achieve their full potential.
The value of assessment data should come with a footnote, acknowledging that it is never perfect or unbiased. Yet getting rid of a test does not eliminate inequity-- it simply reduces our ability to recognize and address these inequities.
Instead, using multiple indicators of student potential, like ability alongside achievement data, allows educators to detect unique learning needs, holistically understand student capabilities and ensure students reach their full potential.
Anna Houseman is a former elementary school teacher and regional Assessment Director in Newark, N.J. and Brooklyn, N.Y. She now heads up ability product and marketing at Riverside Insights, a leading developer of research-based assessments and analytics. Dr. Joni M. Lakin is a Professor at the University of Alabama and is co-author of the Cognitive Abilities Test™ (CogAT®) Form 8. She studies educational measurement issues related to test validity and fairness with a particular interest in the accessibility of tests for English-learner students.
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