Using Data Throughout Your Organization Don’t Run, It’s Only Data Joel Staudter.

Using Data Throughout Your Organization

Don’t Run, It’s Only Data

Joel Staudter

Taking the fear out of data!

Agenda

Questions and Answers

Student Level, Building Level, District Level Data

Introduction to the presentation

Establishing why we Fundamentally Use Data

Pre Assessment/ Goal

A Common Data Vocabulary

Data Cycles and Identification of Owners

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Staudter, Joel

Pre-Assessment Please get out your cell phones

Two Questions:

1. What role do you fill in your organization?

2. What do you expect to learn from today’s presentation?

How To Vote via Texting

1. Standard texting rates only (worst case US $0.20)2. We have no access to your phone number3. Capitalization doesn’t matter, but spaces and spelling do

TIPS

EXAMPLE

Where do we go from here?

http://www.wordle.net/

http://www.wordle.net/

Don’t Confuse Me With The Facts! Why Do We Need All This Data?

Templates

Staudter, Joel

• Replace hunches and hypotheses with facts concerning what changes are needed

• Facilitate clear understanding of gaps between where the school is and where the school wants to be.

• Identify root causes of gaps, so the school can solve the problem, just not the symptom.

• Understand the impact on a student population.

-Victoria L. Bernhardt’s, Using Student Data To Improve Student Learning in High Schools. 2005

Don’t Confuse Me With The Facts! Why Do We Need All This Data?

Templates

Staudter, Joel

• Assess needs to target services • Eliminate ineffective practices• Efficiency uses of dollars• Show if school goals are being met • Generate answers for our community

-Victoria L. Bernhardt’s, Using Student Data To Improve Student Learning in High Schools. 2005

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Data Vocabulary

Hard Data: Quantifiable, with a given degree of specificity and tangibility

Norm-referenced tests: Used to compare the performance of an individual student with others across a larger population.

Criterion-referenced tests: Assessments created to determine student mastery of content.

James-Ward, Fisher, Frey, Lapp, Using Data To Focus Instructional Improvement, 2013

Staudter, Joel

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Data Vocabulary

Soft Data: Qualitative data, refer to information about student learning and instruction is acquired by observing actions in and out of the classroom.

Observation: No direct contact is needed; scoring can be as simple as tally marks.

Survey : Target questions focus on targeted groups.

Interview: Used when information is sensitive or complex.



The Great Debate

Formative vs. Summative

Summative Data: Describes the results of a process

Formative Data: Used to inform and adjust the process as it unfolds.


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Student Growth, Achievement, Mastery Hard Data

Staudter, Joel www.ohioleadership.org

http://www.ohioleadership.org/

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Building Level Data

Staudter, Joel

• Course Offerings: Course request sheet, preceding years grade distribution by course, graduation requirements, Standardized assessment scores, value added scores

• Program Offerings (CTE): Program Audit

• Intervention/ Extra Help: Progress Book’s ineligibility report, teacher assigned

• Subgroups

• Enrollment, Population Trends• Monthly enrollment reports• March-July, projected enrollment reports

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Building Level Data

Staudter, Joel

• Attendance (Staff and Students): Quarterly reports; share with the staff and students.

• Professional Development: Industry certification training (CTE), teacher evaluation rubric components, engagement, differentiated instruction practices, walk through hard/soft data, department analysis, discipline data

• Grade Card: New to CTE

• Master Schedule

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CTE Report Card Components

Staudter, Joel

Ohiocareertech.wordpress.com

Achievement Graduation Post-Program Outcomes

Prepared for Success

Perkins Performance

• Technical Skills Attainment

• 4-year Cohort graduation rate

• 5-year Cohort graduation rate

• Industry Credentials

• Post-Program

Placement

• Dual Enrollment• AP• IB• PSEO• CTE• Articulated credit

• Academic Attain: Reading• Academic Attain: Math• Technical Skills Attain• Secondary School Completion rates• Placements• Nontraditional Participation• Nontraditional completion

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Sample Building or District-wide Data Set

Staudter, Joel

Criterion Ineffective Developing Proficient Accomplished

Score Comments

Students testing

(Industry)(Due 5/1)

0-24% taking

industry tests

25-50% taking

industry tests

51-75% taking

industry tests

76-100% taking

industry tests

The number of students

tested, divided by the number of students

enrolledPassage

Rate(Industry

Test)(Due 5/1)

0-59% pass industry test

60-75% pass industry

76-91% pass industry

92-100% pass

industry

The number of students that passed, divided by the number of students

that took the assessment

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College and Career Readiness Definition

Staudter, Joel

"High School graduates have the necessary knowledge and skills to qualify for and succeed in entry level, credit bearing, college level courses; and post-secondary job training and education for a chosen career.“

Hard Data Correlations:Student Performance on: Junior and Senior Year Core Curriculum Class grade distribution sheet, ACT, SAT, Compass, Accuplacer, end of course assessments, quarterly assessments, curriculum

Soft Data Correlations: Observation of non-academic social interaction, interview survey to gain insight on a students: self-motivation, career goals, meaningful people’s expectations, post-secondary survey information.

District Level Data


tAre we serving our communities? (Survey, communication, participation in communities)

Voter registration

Where our faculty and staff live in our district

Facilities use

Perception of fiscal responsibility

State reporting

Student job and college readiness

External Internal Continuous Improvement

Student Performance

Staff Performance

Facilities Performance

Financial Performance

Building Performance

Course Performance

CTSO Performance

Transition Performance

Customer Service

Communication

Safety

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Four Annual Goals

Action Plan

Responsible person(s)

Expected date

Communication plan

Preliminary data source, data collection points/ dates, formative goal, final goals


• Identify data source (example: OGT Math)• Identify who will be responsible for collecting the

information (example: Mr. Jones)• Identify where it will be stored and in what format

(excel, common drive I:) • Identify date collection will occur (Oct 12)• Identify how it will be calculated! (volume of

takers, points gained, classes taken, remediation

Protocols for Accurate Data Collection Be Specific……………..


• Step 1: Collect Evidence of Student Learning

• Step 2: Analyze Assessment Results• Step 3: Plan for Instruction• Step 4: Implement with Fidelity• Step 5: Re-assess and Evaluate

Effectiveness

Ohio's 5-Step Process includes:Be consistent!


• Learn reporting periods, data sources and look at results prior to reporting.

• Learn the capabilities of the systems in place (Power school, DASL, Progress Book, Angel, Blackboard, other).

Hold Monthly Meetings with EMIS Person

• Data Alone Has Never Improved Anything…….

The Final Fact

Using Data Throughout Your Organization Don’t Run, It’s Only Data Joel Staudter.

Documents

Transcript of Using Data Throughout Your Organization Don’t Run, It’s Only Data Joel Staudter.