Renaissance

Owned by Kara Michelle Liu
Last updated: Jul 03, 2023 by Tara Chiatovich
3 min read

Academic Assessments

The current plan for academic assessments is to show the tier for each student for each assessment for which they have data. So, for example with the Belleville data, students in the older grades have assessment data for the Star Math and the Star Reading assessments. Tiering for students should happen separately for each assessment, meaning they could be in different tiers for Star Math vs. Star Reading. This point will be even more important when we have customers with more than one assessment for a given subject (e.g., a state standardized assessment for math and reading in addition to a national assessment for math and reading).

 

These instructions are intended for Belleville specifically. We also expect these instructions to apply to other customers using Renaissance STAR academic assessments. However, in the future, we will have customers who use other assessments, and the rules for how to determine which student are recommended for each tier will be different.

The following three files contain academic assessments data:

  • SEL.csv (early literacy assessment primarily for students in early grades)

  • SM.csv (math assessment scores for students in middle elementary grades and up)

  • SR.csv (reading assessment scores for students in middle elementary grades and up)

  • For each season (as defined by the column ScreeningPeriodWindowName), tiering will be based on the most recent value of the PercentileRank column for each student, where most recent is determined by the CompletedDateLocal column and each student is identified StudentUserID column. Note that in current designs (week of 06/19/23), information on tiering is provided for each season, so tiers should be shown separately by season. We specify to look at the most recent date in case a student completed the assessment twice in the same season.

     

    Here is the mapping for students for default tiers (see note below about when users change the default):

    Using the most recent date (as per the CompletedDateLocal column) within each student (as identified by the value in the StudentUserID column) and each value of ScreeningPeriodWindowName (so that students have a tier for each value of ScreeningPeriodWindowName):

    • PercentileRank < 10 = tier 3

    • For the case when PercentileRank >= 8 & PercentileRank < 10 the student will be assigned to tier 3 with an approaching indicator (such as an up arrow) showing that they are close to moving to tier 2

    • PercentileRank >= 10 & PercentileRank < 25 = tier 2

    • For the case when PercentileRank >= 10 & PercentileRank < 12 the student will be assigned to tier 2 with an at risk indicator (such as a down arrow) showing that they are close to moving to tier 3

    • For the case when PercentileRank >= 23 & PercentileRank < 25 the student will be assigned to tier 2 with an approaching indicator (such as an up arrow) showing that they are close to moving to tier 1

    • PercentileRank >= 25 = tier 1

    • For the case when PercentileRank >= 25 & PercentileRank < 27 the student will be assigned to tier 1 with an at risk indicator (such as a down arrow) showing that they are close to moving to tier 2

Important note: When a user changes from the default mapping for tiers, the at risk indicator (such as a down arrow) will apply when the student has the minimum PercentileRank or the minimum PercnetileRank +1 for tier 1 or tier 2. The approaching indicator (such as an up arrow) will apply when the student has the maximum PercentileRank or the maximum PercentileRank -1 for tier 2 or tier 3.

 

 

Dev Feedback

  • Include how to handle and empty state-images/text

  • How will we separate by districts-which column?

  • Include when we rename attribute column-shown in design

 

We need to map fields used in Renaissance to our Rethink Platform. Our goal is to provide users with recommendations for Tier selection based on Data Analytics calculations.

The areas to map include:

 

 

Suggestion for future development:

  • Take a second look at the data we have and how it can be used to further our product offerings: Example: InstructionalReadingLevel,EstimatedOralReadingFluency, Quantile, LiteracyClassification may be useful in connecting to Vizzle.

  • Consider StudentGrowthPercentileFallFall, and others for Winter and Spring which could be a graph that shows the student’s growth from year to year. (Reading, Math, Student Early Literacy)

  • Anticipate requests to customize test scores to reflect district decisions. DistrictBenchmarkCategoryName and RenaissanceBenchmarkCategoryName. Districts sometimes determine their own benchmarks so values in these two columns could be different for a specific student-This has been elevated. Idea: Create checklist for districts that are onboarding.

 

Column definitions documents:

 

Comprehensive help center site: Help Center shows cut scores

 

Customer-facing data sharing instructions:

New_DataSharing.pdf (widen.net)