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Benchmark Data Reports
Benchmark Data Reports
Over the course of the 2019-20 school year, Assessment and Reporting Committee (ARC) teams in second and fourth grades developed and piloted cumulative math benchmark assessments. Through this journey, the teams generated a list of data sets to help them gather student progress at the point of administration (summative), make decisions on instruction moving forward (formative), and identified the available reports in DnA by Renaissance (formally Illuminate) which projected this data. Below are the reports teachers can access to find the data sets listed by the ARC teams.
Open Assessement> Select Reports Tab
Open Assessement> Select Reports Tab
Matrix Report
Matrix Report
Individual vs. class overall performance on an assessment
Student vs. class performance on items, standards, or question groups
Identification of common misconceptions and error patterns for an entire group
Student Responses
Student Responses
Overall class performance by student
Student raw response data for preview of download
Teacher Assessment Overview
Teacher Assessment Overview
Performance level and at or above grade level
Item Attribute Performance
Standard Level Performance
Teacher Peer Comparison
Teacher Peer Comparison
Whole class and student level analysis of performance by attribute and standard
Student Overview
Student Overview
Identifies a single student's overall score and proficiency level on a test.
Student and Parent Letters
Student and Parent Letters
A letter that provides information on a student's score, standard performance, performance level, question groups and answers on a specific assessment.
Multiple Assessment Performance Report
Multiple Assessment Performance Report
Identify performance by each subgroup over multiple assessments
Identify areas of opportunity for growth in state and federal accountability systems
Common Data Analysis Protocol
Common Data Analysis Protocol
Two Assessment and Reporting Committee (ARC) teams, grades two and four, dedicated a portion of their committee work in 2019-20 to designing a unified and fundamental approach to analyzing data. These teachers agreed to use a standardized approach to analyzing data from team designed benchmarks they were piloting to have “apples to apples” conversations. Each team used an exemplar data analysis protocol from the California Department of Education as a springboard to conversation on developing this process. Below are the steps, synthesized between the two teams, of a uniformed approach to analyze their data when collaborating.
Step 1: Predict Your Data
Step 1: Predict Your Data
Consider some of the following while formulating a prediction:
What standards have I taught to this point?
How have students been performing on my formative assessments to this point?
Student designations, performance in other content areas
Testing conditions
Step 2: Make your Data Visual
Step 2: Make your Data Visual
Print out, or make available for notes, any applicable:
Reports
Charts
Graphs
Previous data, if applicable
Step 3: Write Down the Facts
Step 3: Write Down the Facts
Write your observations and factual statements from the data, such as:
Numbers
Percentages
Avoid subjective statements
Step 4: Develop Your Inferences
Step 4: Develop Your Inferences
After reviewing your facts, numbers, etc., possible inferences include:
What’s working
What strategies students still need
What skills students still need
Why trends are happening
Step 5: Make a Plan
Step 5: Make a Plan
Make time to collaborate with your team using your data analysis to create an action plan from your results, with goals that are:
Specific
Measurable
Attainable
Relevant
Time bound
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