School Level Data DiveLEADING WITH DATA

School Level Data Dive Outcomes

Reflect on the power of

leading with data to drive

rigorous instruction for

all students

Explore research on Howard

County student outcomes that

supports a pathway to college and

career readiness

Deepen a skill set for analyzing

data to drive rigorous

instruction

Driving Continuous Improvement with Data

Understanding research-based

trends

Analyzing school data

Interpreting the data

Connecting the data to rigorous

instruction

Monitoring progress

toward college readiness

Refining actions

and plans

Understanding Research-based Trends

• Students who achieved a PSAT ≥ 145 in Grade 10 were 13 times more likely to be college ready and enroll in college immediately following high school

• HCPSS students who participated in an advanced math course by Grade 8 (Algebra 1) are 3 times more likely than their peers who did not participate in Algebra 1 to be college ready

Indicators of College Readinessscore conversion chart

Gr. 5 Above (CC6)

Gr. 6 CC 7

Gr. 7CC 8

Gr.8Algebra 1

Gr. 9 Geometry

Gr. 10 Algebra 2

Gr. 11 Pre-Calculus

Gr. 12 AP Calculus AB

Making Connections: Math Progression

Gr. 5 CC 5

Gr. 6 CC 6

Gr. 7CC 7

Gr.8CC 8

Gr. 9Algebra 1

Gr. 10 Geometry

Gr. 11 Algebra 2

Gr. 12 AP Statistics

Across levels, we are looking to build an academic profile of students who meet our

Preliminary Performance Benchmarks and using this information to increase

rigor for all students.

Making Connections

Beginning with School-Level Data

Analyzing/Interpreting Data

OPEN EXPLORATION:Orienting to the School-Level Data

Description of Dataset–At least 3 years of data–Data reported by student group–Note the sheets/tabs at the bottom

Dataset Codebook– School-Level Data Reference Guide

OPEN EXPLORATION:Orienting to the School-Level Data

Activity 15 minutes (share at your tables)1. Pick a tab/sheet.2. What trends do you notice?3. How are these trends changing?4. Or not changing?5. What surprised you?6. What might you want to explore further?7. What other data would be helpful?

Analyzing/Interpreting School-Level Data

We know: HCPSS students who participated in an advanced math course by G8 (Algebra 1) are 3 times more likely than their peers who did not participate in Algebra 1 to be college ready.

Question: How can understanding the academic profile of these students who meet this Benchmark help us increase access to rigor for all students starting in elementary school?

Analyzing/Interpreting School-Level Data

Exercise 1:

1. Go to GT Participation tab2. Filter for “All Students” in Student Group3. Filter for Grade “5”

Q1) What number and percentage of your Grade 5 students are participating in G/T Math?

Q2) What is the trend across time?

Analyzing/Interpreting School-Level Data

Exercise 2:1. Clear the Student Group filter.2. Filter for Year “2014” + Grade “5.” Look at your

data by Student Group.Q3) What do you notice about each student

group’s G/T Math participation in SY 2014?Q4) Select Year “2013.” Do you see similar trends

across groups over time? Repeat for another year.

Be prepared to share out

Analyzing/Interpreting Data

Diving into Student-Level

Data

From School- to Student-Level Data

School-level data are your back story/context

Student-level data are your actionable data

OPEN EXPLORATION:Orienting to the Student-Level Data

Description of the Dataset– SY 2014 Grade 5 students– Current and prior years’ data– Each line represents one student

Dataset Codebook– Student-Level Data Reference Guide

Activity 5 minutes– Explore the variables– Use your filters, freeze top row

Analyzing/Interpreting Student-Level Data

We know: 1) Based on research, Algebra 1 by G8 is linked to

college readiness and college enrollment2) Based on HCPSS math course progression, student

needs to be in above-grade level or G/T Math by G5 to be able to take Algebra 1 by G8

Question: How can understanding the academic profile of the students who meet this PPB help us increase access to rigor for all students starting in elementary school?

Analyzing/Interpreting Student-Level Data

Exercise 1: Filter for students who are in Above Grade Level Math (GRD5_MATH_INSTR_LEVEL_Q2: “Above”)

1. How many students do you have? 2. Describe their academic profile.

a. Performance-based factors (e.g., CogAT, MAP, MSA, SCAT, report card grades)

Analyzing/Interpreting Student-Level Data

Exercise 2: Clear the “Above” filter; filter for “On” Grade Level(GRD5_MATH_INSTR_LEVEL_Q2: “On”)1. Do you have students who have a similar

academic profile that you have just identified but are not in “Above” Math?

Analyzing/Interpreting Student-Level Data

Question: How do we support struggling students with different needs (e.g., On or Above Math but poor grades; Below Grade Level Math)?

Exercise 3: Students in AGL Math but poor gradesFilter for students who are in Above-grade-level Math (GRD5_MATH_INSTR_LEVEL_Q2 “Above”) andHave a report card grade lower than B (REPORT_CARD_MATH_Q2 “B”)

1. How many students do you have? 2. Describe their academic profile.

Exercise 4: Performing well in current Math, not in AGL Math• Filter for students who were “Advanced” on MSA Math

in Grade 4 (GRD4_MSA_MATH_LEVEL) and • Are being instructed “On” Grade Level Math

(GRD5_MATH_INSTR_LEVEL_Q2) and• Add a filter for students who earned an “A” in Math in

Quarter 2 (REPORT_CARD_MATH_Q2). Q1) What is their academic profile? Q2) What contributed to their current math instructional level

placement?

Analyzing/Interpreting Student-Level Data

Exercise 5: Below Grade Level MathFilter for students who are being instructed “Below” Grade Level Math (GRD5_MATH_INSTR_LEVEL_Q2)Q1) What is their academic profile like? Historical

data?Q2) What might rigorous instruction look like for

these students?

Analyzing/Interpreting Student-Level Data

TABLE TALKHow will you use this data exercise, the

Preliminary Performance Benchmarks, and the resources to support college readiness

to lead with data?

Connecting the Data to Rigorous Instruction