FAQs
EVAAS reports are about the growth students make, rather than their level of achievement. This takes into account where each student starts the school year as compared to where he or she ends the school year. While one cohort of students may end the school year with similar testing results (i.e. achievement levels) as another cohort of students, those students may have started the year at an entirely different level of achievement than the other cohort, and therefore the amount of growth the two cohorts made during the course of that school year would have been entirely different.
If students were initially high achieving and yet did not make the expected growth (based on what students similar to them, academically, made in the average teacher's classroom in that same subject), the effect would be negative. If they made more than average growth, it would be positive. The following questions and responses may be helpful in speaking to your teachers.
What is the difference between growth and achievement?
Achievement is what is measured by a test score. Growth is determined by comparing students against themselves and the amount of progress they have previously made across all tested grades and subjects.
Value-added modeling is not about one student on one day. It’s about looking at the growth of an entire group of students over time.
In fact, value-added modeling does not provide growth measures for individual students. It only provides a growth measure for groups of students. Growth models look well beyond what students do on just one day by looking for a pattern across multiple years of growth estimates and multiple years of student test scores to see whether students, on average, made expected growth.
- Low achieving or high achieving?
Yes, value-added modeling is fair even if students are low achieving or high achieving. Value-added modeling is based on growth, not proficiency or achievement. The growth expectation for each student is based on each student’s own previous achievement. Regardless of whether students are proficient or not, the value-added model will estimate whether, on average, students met the growth expectation. - Part of a certain socioeconomic/demographic group?
Yes, value-added modeling is fair even if students are part of a certain socioeconomic/demographic (SES/DEM) group. The value-added model uses all student testing history and includes students even if they have missing data so that, in essence, each student serves as his or her own control. In other words, a student’s SES/DEM status is usually quite consistent from year to year. The student has been testing with those same personal variables in place, in addition to many other variables that can impact academic performance. Therefore, the impact of those variables has already been captured in the student’s previous test results. - 3.) Highly mobile?
Yes, value-added modeling is fair even if your students are highly mobile. The value-added model does not require that students have scores for all prior tests or even that students have the same set of prior tests. Students are included in the analysis, even if they are missing test scores, so long as they meet all other criteria for inclusion. This means that highly mobile students can still be included in the value-added model. - 4.) Identified as a student with a disability?
Yes, value-added modeling is fair even if your students are identified as a student with a disability. The value-added model only uses the regular versions of the tests, not the alternate assessments. That said, value-added modeling is based on growth, not proficiency or achievement. The growth expectation for each student is based on each student’s own previous achievement. Regardless of whether students are proficient or not, the value-added model will estimate whether, on average, students met the growth expectation for a class or school.
Value-added is not about students passing or failing. This is about how much progress students made. Value-added modeling is based on growth, not proficiency or achievement. The growth expectation for each student is based on each student’s own previous achievement. Regardless of whether students are proficient or not, the value-added models estimate whether, on average, students met the growth expectation for a school or division.