Achievement data tells us whether students have reached a performance standard. Growth data helps us understand the progress students made along the way. 

Adequate Growth with standard error

Adequate Growth combines both Achievement and Growth to have a single metric showing if students are maintaining a level of proficiency or if students are growing enough towards proficiency to close the gab and reach proficiency soon. How we determine proficiency and how much is needed to justify growth towards proficiency is determined by the specific assessment cut-scores and standard measurement error. 

Every assessment has a standard measurement error that establishes a range the student is expected to score within if they took the assessment again. As an example, suppose the cut-score for proficiency was 1,000 scale score points and a student scored 1,005 one year and 998 the next year on a more advanced assessment on a common scale. The first year, the student was proficient by 5 points, however, the second year the student missed proficiency by 2 points. Did the student grow?

It depends, if it were the same test covering the same material, then no, the student lost 7 points. However, with most state level assessments on a common scale, the student scored near proficiency at the previous grade level content standards and when the student took a new test at a higher grade level content standards, the student again scored near proficiency. That is certainly growth!!!  A standard error helps to determine the necessary growth so the process can be automated using MS Excel or R Stats or another platform.