# Teacher Diagnostic Summary Report

## Technical Details

The Teacher Diagnostic Summary is a summary of a teacher's diagnostic reports for individual grades, subjects, and courses. No additional calculations are performed to generate the data in this report.

### Placing Students into Achievement Groups

Students are placed into three groups based on their achievement.

On the reports with five groups, group 1 includes students whose achievement falls into the lowest 20% of the state distribution, group 2 includes students whose achievement falls between the 20th and 40th percentiles, and so on.

For all assessments, more than a single test score is used to place students into groups. Using more data minimizes the effect of measurement error and helps ensure that students are placed into achievement groups appropriately.

#### Teacher Diagnostic

Students are divided into three equal groups based on where their achievement in the selected subject falls in the state distribution.

The model used to analyze the selected assessment determines how we define achievement. See assessments analyzed with the gain model and assessments analyzed with the predictive model.

 Model How Achievement is Defined Gain Model The average of a student's two most recent scores in the selected subject.For example, in a report for sixth-grade math, students are placed into achievement groups based on the average of their fifth-grade and sixth-grade math scores. If a student's fifth-grade math score is missing, that student is not placed into an achievement group on this report. Predictive Model Where the student's expected score falls in the state distribution for that grade and subject or course.Students who lack sufficient data do not have expected scores and therefore are not included in achievement groups on this report. For all tests, students must have three prior assessment scores across grades and subjects to have expected scores.
• Students Not Used in Analysis are not included in the Teacher Diagnostic Summary report, and not used in the Value-Added analysis. This can happen for several reasons. For example, it happens when students don't have sufficient past test scores, or their current-year scores had to be excluded for business reasons.
• Students Not Used in Report are not included in the Teacher Diagnostic report but are used in the Value-Added analysis. This happens when students who have sufficient past test scores for the analysis either don't have scores from the previous year, or their previous year's scores had to be excluded for business reasons.

#### Teacher Performance Diagnostic

Students are placed into three groups based on where their expected scores fall relative to the performance level ranges that are defined by the state. Expected scores are labeled as Entering Achievement because they reflect students' achievement before the current school year or when they entered a grade and subject or course. This method of placing students is used for all state assessments, regardless of whether the data is analyzed with the gain model or the predictive model.

A student must have three prior scores across grades and subjects for an expected score to be generated. If a student has fewer than three prior scores, no expected score will be generated, and the student will not be included in this report.

#### Teacher Custom Diagnostic

Students are placed into three equal groups based on where each student's achievement falls in the distribution of students that you selected. The Low group includes the students whose achievement falls into the lowest third of students you selected. The High group includes the students whose achievement falls into the highest third of students you selected.

The model used to analyze the selected assessment determines how we define achievement. See assessments analyzed with the gain model and assessments analyzed with the predictive model.

 Model How Achievement is Defined Gain Model The average of a student's two most recent scores in the selected subject.For example, in a report for sixth-grade math, students are placed into achievement groups based on the average of their fifth-grade and sixth-grade math scores. If a student's fifth-grade math score is missing, that student is not placed into an achievement group on this report. Predictive Model Where the student's expected score falls in the state distribution for that grade and subject or course.Students who lack sufficient data do not have expected scores and therefore are not included in achievement groups on this report. For all tests, students must have three prior assessment scores across grades and subjects to have expected scores.
• Students Not Used in Analysis are not included in the Teacher Diagnostic Summary report, and not used in the Value-Added analysis. This can happen for several reasons. For example, it happens when students don't have sufficient past test scores, or their current-year scores had to be excluded for business reasons.
• Students Not Used in Report are not included in the Teacher Diagnostic report but are used in the Value-Added analysis. This happens when students who have sufficient past test scores for the analysis either don't have scores from the previous year, or their previous year's scores had to be excluded for business reasons.

### Generating Growth Measures

Once students are placed into groups, a simple growth measure is generated for each group. A group must have at least eight students for a growth measure to be generated.

For all assessments, a growth measure of 0.0 represents meeting expected growth.

It's important to remember that these simple growth measures do not come from the robust analytic models that generate the growth measures on the value-added reports. As a result, you'll want to exercise some caution when interpreting the data. Specifically, focus on the relative pattern of growth across groups rather than rely too heavily on any one value. Because the growth measures are estimates, consider their associated standard errors as you interpret the values.

The model used to analyze the selected assessment determines how we generate growth measures. See assessments analyzed with the gain model and assessments analyzed with the predictive model.

 Model How Growth Measures are Generated Gain Model The growth measure is the difference between the group's most recent average score in this subject and its prior average score in the same subject. The growth measures for these assessments are expressed in state NCEs. Predictive Model The growth measure is the difference between the group's average score and their average expected score in the selected subject or course. The growth measures for these assessments are expressed in scale score points.

Students' NCEs might change from year to year for the following reasons:

• Exclusion rules might change. Exclusion rules for one year might include and exclude different students than the exclusion rules for another year. For example, if a business rule changed to include students that were previously excluded current and previous NCEs would be adjusted with this change.
• Each year we have more student assessment data. In some cases, this additional data enables us to know more about a student's cohort and testing history, which might impact which student data are included or excluded. For example, a student that was accelerated or retained and tested with a different grade level (cohort) in a prior year was excluded. In the current year, this student might be included now that they have assessment data with the student's new cohort.

These small differences in student counts within each year can cause slight shifts in the NCEs for prior years.