Data-Driven Decision Making

Data-Driven Decision MakingAmy ReitzManager, Consulting ServicesHobsons K-12

Agenda

Overview of Data Driven

Decision Making

Building a Data Culture

• Staff Workshops

• Student Workshops

Overview of Data-Driven Decision Making

Data-Driven Decision Making is…

DDDMD3M

The collection and analysis of data to make decisions that improve student success.Continual evaluation accompanied by incremental changes.Translation of data into knowledge and actionable strategies.Collaboration and communication throughout the school, district and community.

Theme 1: Use data to make decisions

Data Decisions

What we want to happen

Helpful Data

I need to…

What happens in reality

Teacher Evaluations

Partner Assessments

SAT

GPA

ACT

Attendance

Activities

Standardize

d

Test Sco

res

Demographics

Classro

om

Activit

ies

PSAT

AP

IBIEP

Course Plan

School History1600

4.0

32

1.7

365

???

Theme 2: Focus on outcomes

How do you measure success?

Staff and students have completed all of their assigned tasks.

Students are career and college ready.

Productivity Outcome

Theme 3: Dig deeper

Illustrated via an example:

If staff members from a school attend NSI, is the Naviance

student usage at that school positively affected?

Following slides are from a case study for a large urban district with staff members attending NSI 2012.

Impact of NSI on Student Usage

*Active Student User = Student that has logged in at least once.

Dig deeper

What is wrong with this analysis?• It doesn’t consider the past.• Schools with NSI attendees could have

already had higher usage.How can it be improved?• Compare growth rates.


*Active Student User = Student that has logged in at least once.

Dig deeper

What is wrong with this analysis?• It doesn’t consider other support.• Schools with NSI attendees could have had

additional support from Naviance staff.How can it be improved?• Include another variable: interaction with a

consultant.


Average Logins per Student

*Average logins per student include students with 0 logins.

Schools without NSI Attendees

Schools with NSI Attendees

Schools without Consultant Interaction

Schools with Consultant Interaction

1.5 2.9

4.7 5.8

Dig deeper

What is wrong with this analysis?• It doesn’t consider more than 2 variables.• Schools with NSI attendees could have had

additional training or other student variables could influence usage.

How can it be improved?• Analyze multiple variables to build a

predictive model.

Multivariable Regression

y = 10x + 2w – 5z

outcome variables

coefficients


Output of Multi-Variable Regression for Unique Logins:

Positive Coefficients


Output of Multi-Variable Regression for Total Logins:

*Total logins for students with 1+ login.

Positive Coefficients

Statistically Insignificant(p > 0.05)


Regression Coefficients

Unique Logins Total Logins

NSI 0.012 0.96

Consulting 0.122 2.78

Training 0.321 N/A

Dig deeper

What is wrong with this analysis?• It doesn’t consider individual student

variables.- Did an analysis with gender and class year, but

they were statistically insignificant. Still many other variables that could be included.

How can it be improved?• Additional variables.• Sensitivity analysis and other statistical

models.• Larger sample size across multiple schools,

districts, and regions.

Building a Data Culture

DDDM is a culture

To be truly effective, DDDM needs input from everyone.

Everyone needs to see value and be invested in collecting and analyzing data.

Staff need to openly collaborate and take action based on data.

In some cases, this requires a huge attitudinal shift. Be prepared to facilitate.

Building a Data Culture: Staff Workshops

Staff Workshops

Involve multiple staff members from various roles in the development of data processes.

Collaborate to make the best possible decisions.

Use data for decisions and information, not just compliance.

Staff Workshop: Report Review

Purpose: Review the reports in Naviance and identify needs.Activities:

• Review reports in Naviance.• Identify helpful reports.• For each report, determine:

- Audience: Who should receive this report?- Parameters: Which students/tasks/variables should be

included?- Frequency: When and how often should this report be run?

Next Steps:• Determine data needed to populate report.

- Ensure data is collected during activities throughout the year.

• Customize and schedule reports in Naviance.

Staff Workshop: KPIs & Outcomes

Purpose: Define the key performance indicators and outcomes that are important.Activities:• Brainstorm student outcomes. What does it

mean for students to be successful?• For each outcome, determine associated KPIs.

- Appendix: Key Performance IndicatorsNext Steps:• Document and communicate KPIs and

outcomes.• Map KPIs and outcomes to Naviance activities

and reports.

Staff Workshop: Identify Variables

Purpose: Identify variables that should be tracked to link to outcomes and KPIs.Activities:

• Review identified outcomes and KPIs.• Brainstorm variables that could impact outcomes.• Determine how variables are tracked and stored.

- SIS- Naviance Activities- Naviance Surveys- Other

Next Steps:• Incorporate into Naviance activities and data

collection.- Appendix: Data Collection in Naviance

• Develop maintenance plan.

Staff Workshop: Survey Development

Purpose: Create surveys to collect data and inform decisions.Activities:• Review previously identified needs.

- Direct data collection.- Indirect collection through reflection and and

feedback.• Brainstorm and organize questions.

Next Steps:• Setup surveys in Naviance.• Incorporate survey(s) into activities throughout

the year.

Staff Workshop: Scope & Sequence

Purpose: Define a plan for the activities that need to occur throughout the year.Activities:

• Review available activities in Naviance.• Review previously identified data needs.• Review suggested activities in Naviance

Implementation Guide and Naviance Network.• Develop a plan for the activities to be completed by

students and staff throughout the year.Next Steps:

• Document and communicate scope and sequence.• Map to tasks in Success Planner and assign to

students.

Staff Workshop: Data Validation

Purpose: Review imported and input data to verify accuracy and completeness.Activities:• Review data import history in Naviance.• Review student profiles. Note inaccuracies or

incomplete entries.- For imported data, correct the source.- For input data, correct in Naviance.

• Review regular reports to verify accuracy.Next Steps:• Determine any patterns to identify processes to

be corrected.

Staff Workshop: Progress Reviews

Purpose: Regularly review progress against KPIs and scope and sequence.Activities:• Review regularly scheduled reports.• Identify successes and discuss lessons

learned.• Identify lagging indicators. Brainstorm

causes and discuss solutions.Next Steps:• Make changes to address challenges.

Staff Workshops

What else have you done at your school

or district?


or district?

Building a Data Culture: Student Workshops

Student Workshops

Get relevant input from students.

Help students understand data driven decision making.

Bolster college going culture.

Supplement college and career planning activities.

Student Workshop: Data Validation

Purpose: Verify student demographics, contact information, and other profile information.Activities:• Provide background on importance of profile

information.• Have students review their Naviance profiles

for incorrect information.- Add email addresses.- Note inaccuracies to be corrected in source by

staff (SIS).

Student Workshop: College & Career Survey

Purpose: Introduce students to basic principles of data collection in the context of post-secondary planning and readiness.Activities:• Provide background on survey basics: question

development, tools, distribution.• Students develop and distribute college and

career surveys.• Provide background on basic survey analysis.• Students analyze and present their results.

Student Workshop: Identify Variables

Purpose: Identify additional variables and challenge students to consider the challenges and steps leading to their post-secondary plan.Activities:• Provide students with an outcome to consider.• Provide background information about the

concept of variables and some possible variables affecting the identified outcome.

• Students brainstorm and present the variables they think are important.

Student Workshops


or district?


or district?

Questions & Discussion

Appendices

Key Performance Indicators

Data Collection in Naviance

Additional Resources

Your Feedback Matters!

Thank you for attending the Naviance Summer Institute 2013!

We greatly appreciate your feedback, please complete a brief evaluation for this session at:

http://go.naviance.com/evaluations

Appendix: Key Performance Indicators

Focusing your analysis

Outcomes are the ultimate goal.Variables are the many data points for each student. They include everything that affects a student’s outcomes.Key performance indicators are measurements to determine if you are on track to attain a particular outcome.This appendix includes suggested KPIs using data collected in Naviance.

Note: The source for the following slides in this appendix is the 2012 NSI presentation by Todd Bloom: KPIs for College and Career Readiness.

Student Growth & Proficiency

Grade Point Average

Test score averages• PLAN• PSAT• SAT• ACT• State assessment(s)

International Baccalaureate scores

International Baccalaureate scores by course

% of students who used PrepMe at least once

% of students who complete the learning style assessment

% of students who complete Do What You Are assessment

% of students who complete Career Key assessment

% of students who complete a Course Plan

Course Plan Rigor distribution

College Planning

College Power Score distribution

Alignment of Course Demand Forecast with college readiness curriculum determined by school/district

Student interest in specific courses that school/district indicate align with college readiness goals

Number of applications for individual colleges

Number of applications for individual colleges

% of students who submit one or more college applications

% of students admitted to one or more colleges

% of students who intend to attend college after graduation

Meaningful and up-to-date scholarship database available for student use

Career Planning

% of students who identify careers and career clusters of interest

% of students interested in professional careers

% of students interested in technical careers

% of students interested in careers with specific characteristics, such as STEM, that are determined by the school/district

Student Engagement

% of students who report they understand the knowledge and skills necessary for success in their careers of interest

% of students who set goals

% of students who met goal

% of students who completed tasks that align with college and career readiness as determined by the school/district(e.g. FAFSA completion, internship/ mentorship requirement)

% of students who report understanding their learning styles

% of students who report they have explored colleges and careers based on learning style assessment

% of students who report they understand the links between careers, preparation needed, college major and projected income

Alumni Performance

% of students who enrolled in college

% of students who completed college degrees

% of students who completed college degrees within a specified timeframe

% of students with positive perceptions of college and career readiness

% of students satisfied with teaching or other specified aspects of their K-12 experience

% of students who are satisfied with their post high school plans

% of students who enrolled in remedial college mathematics, English or other courses

% of students who completed remedial college math, English or other courses

Appendix: Data Collection in Naviance

Collecting Data in Naviance

Data comes into Naviance from various sources in multiple ways.This means that data quality can vary.Poor data quality means less accurate analysis.This appendix will cover some of the ways you can improve the quality of data you are collecting.Data is input into Naviance via various methods. Some methods include:

• Student Information (data import)• College Planning• Career Planning• Course Planning• Success Planning• Surveys

Collect Data: Student Info

Keep student data up to date.• Automate data import• Define a process for importing test scores

regularly• Import all data that would be helpful for analysis.

• Review data import and data import templates to determine what is missing and update.- Data import file: setup > data import > data

import history > view- Templates located in the Help Library.

Collect Data: College Planning

• Engage students before senior year to add colleges to their prospective list.

• Use Senior Survey to improve accuracy of outcome reports.

• Turn off the option to allow students to delete active applications.

• connections > family connection > select and update optional features > delete active applications

• Import college application data from previous years.

Collect Data: Career Planning

• Create a scope & sequence for career planning activities that students will complete in grades 6-12.• Use CCR Curriculum to improve rollout and

add context for students.• Leverage class or advisory time to work through

activities with students to ensure completion.• Setup computers at career fairs for students to

add careers to their list.

Collect Data: Success Planning

• Use Success Planning to assign tasks that improve career and college data.

• Link tasks to activities where possible.• For example, instead of manually marking

that a student completed a workshop, create a post-workshop survey and assign the survey as a task.

• Utilize the built-in tasks.• Schedule planner reports to regularly assess

progress.

Collect Data: Course Planner

• Configure the rigor levels for the College Power Score.• courses > configuration > total potential

course rigor• Configure the rigor level for courses in the

course catalog.• Can be included in the course catalog

import.• Can be set manually in Naviance

- courses > course catalog > edit > instructional level

Collect Data: Surveys

• Send out frequent, short surveys instead of long, annual surveys.

• Opt for question types that make aggregate analysis easier.

• Send surveys as a direct link via email (doesn’t require students to login).

• connections > e-mail > send email to a group of students and parents > select options and attach survey > preview and send > “check this box if you want to include a direct link to the survey”

• Appendix: Additional Resources

Naviance Resources

• Naviance Network Community Forums: http://community.naviance.com/t5/Community-Forums/ct-p/succeed

• Naviance Network Help Library, Reporting Section: http://community.naviance.com/t5/Reporting/tkb-p/Reporting%40tkb

Workshop Resources

• ATLAS – Looking at Data: http://www.nsrfharmony.org/protocol/doc/atlas_looking_data.pdf *

• Data.gov in the Classroom, Education Materials: http://www.data.gov/education/page/datagov-classroom

* Thanks to a participant in the NSI 2012 DDDM session for this suggestion.

MS Office Resources

• Office Support: http://office.microsoft.com/en-us/support/

• VLOOKUP (joining data in Excel): http://office.microsoft.com/en-us/excel-help/vlookup-HP005209335.aspx

• Excel Review, Duke University: https://faculty.fuqua.duke.edu/~pecklund/ExcelReview/ExcelReview.htm

Misc Stats and Analysis Resources

• Data Mining: The Tool of the Information Age Revolution, Rajan Patel, Stanford (recorded webinar): http://myvideos.stanford.edu/player/slplayer.aspx?coll=2e431434-84e4-4de0-81c9-76035c36a18f&co=12138da9-eab8-405b-a06f-cc11f12e5871&w=true

• Introduction to Statistics and Data Analysis, University of Michigan (open course materials): http://open.umich.edu/education/lsa/statistics250/spring2013

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