How Misunderstanding Diagnostic Assessments Leads to Poor Data Use and Lower Student Outcomes

In today’s educational landscape, precision in diagnosing student needs is paramount. As an educational test developer dedicated to providing highly diagnostic assessments in math and reading, I am acutely aware of the discrepancies in the market regarding what constitutes a “diagnostic” test. The term “diagnostic” is often misappropriated by companies whose assessments are summative in nature. This mislabeling misguides educators, who in turn start using the term inaccurately as well.  Ultimately, it leads to a slow degradation of the term and culminates in the hindering of student progress. 

Many educational assessment companies market their tests as diagnostic, but their technical manuals often define these assessments differently. For instance, one big company produces a test that only takes 15-20 minutes but advertises their assessment as diagnostic, designed to be short and quick. Conversations with their technical teams often reveal that they in fact consider their products to be screeners. Nevertheless, the marketing and product materials frequently refer to “diagnostic” reports and provide “recommendations,” thus leading to confusion.

Upon closer examination of the data these assessments produce, it becomes evident that they offer broad-scale scores in subject strand areas like “Numbers and Operations,” “Measurement,” “Geometry,” and “Data Analysis” for math, or “Readability Level” and “Reading Level” for reading. These scores are summative: designed to measure student growth over time but falling short in identifying the specific areas where students struggle and why.  

True diagnostic assessments delve deeper, offering insights into the precise skills and concepts that a student has or has not mastered. This level of detail is crucial for informing instruction and intervention. For example, rather than simply showing that a student is below grade level in reading or has a low readability score for their grade, a diagnostic assessment might reveal that the student struggles with phonemic awareness, short vowels, or specific comprehension strategies. In math, instead of a broad “below proficient” rating, a diagnostic assessment would pinpoint difficulties within fractions, identifying specific concepts and skills that are in need of work, such as equivalent fractions or multiplying fractions.

The misdirection caused by mis-labeled diagnostic tests can lead to ineffective teaching strategies and wasted instructional time. When teachers rely on summative scores disguised as diagnostics, they may not receive the actionable data they need to address students’ specific learning needs. Often district administrators will force the use of district-wide broad-based measures on special education departments.  These students may already be behind and thus are not likely to do well on such assessments. This practice reduces the time teachers need to find students’ true strengths and deficits, resulting in blanket interventions that are not tailored to individual students and potentially widening achievement gaps rather than closing them.

An additional consequence of mis-labeled diagnostic tests is the creation of personalized learning lessons or courses based on summative data. The vast majority of ed-tech companies do this.  Technically, students within grade level may not be harmed by following this practice, but any student with significant gaps will be hurt. This is equality without access. These learning paths will usually miss the mark because summative scores are not granular enough to inform effective individualized instruction. As a result, at-risk students may receive lessons that are too difficult, overwhelming them cognitively and leading to frustration, or too easy, thus wasting precious instructional time. This issue not only hampers learning but also contradicts the principles of Universal Design for Learning (UDL), equity, and access. It is arguably unethical to develop learning paths or make instructional recommendations based on predictions rather than on accurate, diagnostic data.

Our precision diagnostics offer a solution to this problem. By providing detailed insights into students’ strengths and weaknesses, our assessments empower educators to make informed decisions about instruction. For instance, if a student struggles with multiplication, our diagnostic assessment would not only identify this issue but also suggest targeted instructional strategies to help the student master this skill. This level of precision is essential for fostering student growth and improving outcomes.

The mis-labeling of summative assessments as diagnostic is a significant issue that can mislead educators and hinder student progress. True diagnostic assessments, like our precision diagnostics, provide the detailed, actionable data that teachers need to understand why students are struggling and what to do next. By distinguishing between summative and diagnostic assessments, educators can better support their students and drive meaningful improvements in learning outcomes. Moreover, ensuring that personalized learning paths are based on accurate diagnostic data is crucial for maintaining ethical standards and promoting equity in education.