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Why Data?. Dr. Laura Tanner-McBrien Coordinator Department of Prevention and Intervention Fresno Unified School District Fresno, California. Objectives. Participants will gain an understanding of how data can be gathered for homeless education and other district programs.

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Why data

Why Data?

Dr. Laura Tanner-McBrien

Coordinator

Department of Prevention and Intervention

Fresno Unified School District

Fresno, California


Objectives
Objectives

  • Participants will gain an understanding of how data can be gathered for homeless education and other district programs.

  • Participants will understand the importance of a data-driven program for students in achieving academic success.

  • Participants will understand the financial benefit of having a strong data component.

  • Participants will gather information to assist them in their own program implementation.


Why code students
Why Code Students?

  • For Identification

  • For Delivering Services

  • For Monitoring Academic and Behavioral Success

  • To Track Student Success

  • To Report Out the Success of a Program


Financial benefits
Financial Benefits

  • Grants

  • District Funds

  • District Support

  • Community Donations or Support


Coding of students in fusd
Coding of Students in FUSD

Codes in ATLAS

Project ACCESS codes can be found under the Student Services tab. Four options for services qualify under Project ACCESS. The codes are entered by Project ACCESS Staff.

  • Project ACCESS – Homeless

  • Project ACCESS – Neglected and Delinquent

  • Project ACCESS – Foster Youth – Out of County Placement

  • Project ACCESS – Foster Youth – Fresno County Placement

    A weekly update from the Department of Children and Family Services automatically changes the foster codes. The homeless codes are updated as parents or schools inform Project ACCESS staff of any changes.


Coding of homeless youth
Coding of Homeless Youth

Project ACCESS – Homeless Codes

A AWAITING FOSTER CARE

D LIVING IN A DOUBLED-UP SITUATION

F FORMERLY HOMELESS – Do Not Qualify for Services

M LIVING IN A MOTEL

O OTHER, HOMELESS ACCORDING TO HSS

R RUNAWAY, POSSIBLY STAYED AT THE SANCTUARY

S LIVING IN A SHELTER

T TRANSIENT (many moves)

U UNACCOMPANIED YOUTH (Caregiver Affidavits)


Coding of foster youth
Coding of Foster Youth

Project ACCESS – Foster Care Codes

Foster Family Agency 11

Relative Home 21

Guardian Home 22

Tribe Specified Home 23

Foster Family Home 31

Foster Family Agency Certified Home 32

Small Family Home 41

County Shelter/Receiving Home 51

Group Home 52

Court Specified Home 53


Purpose of a data base
Purpose of a Data Base

  • History or Pattern of Services

  • Gather Information About a Family

  • Track Services Provided to a Family

  • Evaluate Services Provided to Families

  • For Program Evaluation


Fusd data base
FUSD Data Base

  • MARS Data Base

  • Communicates With Student Information System

  • Two Data Bases; One for Homeless, and One for Foster Youth

  • Contact Information:

    • David K. Meyers

    • MARS Group

    • [email protected]

    • 559-261-2220



Data collection
Data Collection

Data Fields Meanings

  • ID Identification Number

  • Last Name Last Name

  • First Name First Name

  • School School Number

  • Grade Grade Level

  • Gender Male or Female

  • Ethnic Ethnicity

  • DOB Date of Birth

  • Speced Special Education Code 61, 66, 91

  • Migrant Migrant Program

  • Gate Gate Code

  • Lang Home Language Spoken

  • ELD English Language Development Level

  • AVID Advancement Via Individual Determination


Data collection cont
Data Collection Cont.

Program Fields Meaning

  • Program Program Title

  • Beginning Date Date Began Program

  • Level of Service Active or Not

  • Ending Date Date Services Ended


Data collection cont1
Data Collection Cont.

Academic Data Meaning

  • AGPA Academic Grade Point Average

  • Addrcnt Number of addresses in a school year

  • Enrcnt Number of enrollments in a school year

  • Credearn Number of credits earned in Semester

  • Pctattn Percent Attendance

  • CSTeps CST English Proficiency Score

  • CSTess CST English Standard Score

  • CSTmps CST Math Proficiency Score

  • CSTmss CST Math Standard Score

  • CAHSEE M Math CAHSEE Score

  • CAHSEE LA Language Arts CAHSEE score


Data collection cont2
Data Collection Cont.

Behavioral Data Meaning

  • Behavior Behavior log data

  • Supensions Number of suspensions

  • Expulsions Number of expulsions


Data reporting
Data Reporting

  • Data Share

  • Graphs and Charts

  • Formal Evaluations

  • Special Projects

  • Dissertation






Quantitative results cont3
Quantitative Results Cont.

Suspensions

  • 24% of Foster Youth had at least one suspension

  • 184 Foster Youth

  • N = 778

  • 20% of Homeless Youth had at least one suspension

  • 433 Homeless Youth

  • N = 2,194




Qualitative results
Qualitative Results

Survey Results for Tutorial

  • 80% responded they attended for credit retrieval

  • 50% responded they attended for homework

  • 50% rated the tutorial the top score of “10”; all rated the tutorial as a “5” or better

  • 65% of the youth indicated they had a great chance of graduating high school due to the help given.

  • 40% rated the tutoring as a way they earned higher grades and more credits

  • 40% responded that they would feel comfortable going to their tutorial teacher with a question or problem


Dissertation results
Dissertation Results

Impact of School Mobility on Academic

Achievement for Homeless, Foster, and

Housed Students

Dissertation, 2009

CSU Fresno

UC Davis


Purpose of study
Purpose of Study

To explore the ramifications of school mobility on academic achievement for homeless and foster youth


Methodology study groups
MethodologyStudy Groups

  • 7th – 12th Grade Homeless Students

  • 7th – 12th Grade Foster Youth

  • 7th – 12th Grade Non-Mobile or Housed Comparison Group

  • 6th Grade Students were included in the 2006-2007 data for comparison with 7th Grade 2007-2008 data


Variables
Variables

Dependent Variables

  • GPAs

  • Math CST Scores

  • LA CST Scores

  • % Attendance

  • Credits Earned

  • Suspensions

Independent Variables

  • School Moves

  • Address Moves


Specific research questions
Specific Research Questions

Specifically, the following research questions were addressed:

1. Are there differences in California Standards Test scores between homeless, foster youth, and non-mobile students?

2. Are attendance rates, grade point averages, credits earned, and suspensions different for homeless and foster youth than for housed youth?


Research questions cont
Research Questions Cont.

3. Does the number of schools a student attends correlate with their grade point average?

4. Do student behaviors (ie. suspensions) correlate with school mobility?

5. Is there a relationship between academic variables and mobility variables?


Statistical analysis
Statistical Analysis

Descriptive Statistics

Means, SD

Series of 11 Multivariate One-Way ANOVAs

ELA and Math CST scores by grade and year

Series of four 3 x 2 Way Repeated Measures ANOVAs

Academic variables by group and year

Correlation Coefficients

Canonical Correlation

Academics with mobility


Findings
Findings

Research Question 1: Are there differences in California Standards Test scores between homeless, foster youth, and non-mobile or housed students?

11 Multivariate One-Way ANOVAs

  • Homeless and foster youth were more similar than different

  • Scores for homeless and foster youth were statistically different from housed students

  • CST scores in 9th – 11th grades were inconsistent


Findings continued
Findings Continued

Research Question 2: . Are attendance rates, grade point averages, credits earned, and suspensions different for homeless and foster youth than for housed youth?

Four 3 x 2 Repeated Measures ANOVAs

  • Homeless and foster youth were more similar than different

  • Scores for homeless and foster youth were statistically different from housed students


Findings continued1
Findings Continued

Figure 1. Plot of academic GPA by year for housing status


Findings continued2
Findings Continued

Figure 2. Plot of percent attendance by year for housing status


Findings continued3
Findings Continued

Figure 3. Plot of number of suspensions by year for housing status


Findings continued4
Findings Continued

Figure 4. Plot of credits earned by year for housing status


Findings continued5
Findings Continued

Research Question 3: Does the number of schools a student attends correlate with their grade point average?

Research Question 4: Do student behaviors (ie. suspensions) correlate with school mobility?

Correlation Coefficients

  • Found statistically significant correlations between mobility variables and academic variables


Findings continued6
Findings Continued

Research Question 5: Is there a relationship between academic variables and mobility variables?

Canonical Correlation

  • Housing and School moves accounted for 21% of the variance between academic variables in 2006-2007

    and 20% of the variance between academic variables in 2007-2008


Limitations
Limitations

  • Reasons for School Moves are Not Known

  • Pre-mobility Issues are not Considered

  • Two Years of Data

  • Missing Data


Implications for further research
Implications for Further Research

  • Qualitative Study Component

    • Interviews with youth

  • Housing Situation Comparison

  • Foster Care Placement Comparison

  • Transportation Services as a Factor


Questions
Questions

Why Data?


Contact information
Contact Information

Laura Tanner-McBrien, Ed.D.

1350 M. St., Building B

Fresno, CA 92721

Phone: 559-457-3359

Fax: 559-457-3372

[email protected]


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