Why Data?

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Why Data?

• Dr. Laura Tanner-McBrien
• Coordinator
• Department of Prevention and Intervention
• Fresno Unified School District
• Fresno, California

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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.

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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

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Financial Benefits

• Grants
• District Funds
• District Support
• Community Donations or Support

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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.

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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)

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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
•  
•  

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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

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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
• dmeyers_at_mars-group.com
• 559-261-2220

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ATLAS



Add new record Refresh
Service Eligibile Participation Begins Expires Code Modified By Modified Date  
Project ACCESS - Homeless False False 07/01/10 08/25/10 D Laura Tanner-Mcbrien 8/25/2010 40138 PM Edit
Project ACCESS - Homeless True True 08/25/10 U Laura Tanner-Mcbrien 8/25/2010 40151 PM Edit
Student Attendance Review Board False False 07/01/09 07/12/09 1   9/2/2010 12436 PM Edit
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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

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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

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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

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Data Collection Cont.

• Behavioral Data Meaning
• Behavior Behavior log data
• Supensions Number of suspensions
• Expulsions Number of expulsions

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Data Reporting

• Data Share
• Graphs and Charts
• Formal Evaluations
• Special Projects
• Dissertation

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Quantitative Results
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Quantitative Results Cont.
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Quantitative Results Cont.
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Quantitative Results Cont.
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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

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Quantitative Results Cont.
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Quantitative Results Cont.
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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

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Dissertation Results

• Impact of School Mobility on Academic
• Achievement for Homeless, Foster, and
• Housed Students
• Dissertation, 2009
• CSU Fresno
• UC Davis

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Purpose of Study

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

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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

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Variables

• Dependent Variables
• GPAs
• Math CST Scores
• LA CST Scores
• Attendance
• Credits Earned
• Suspensions

• Independent Variables
• School Moves
• Address Moves

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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?

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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?

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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

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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

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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

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Findings Continued

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

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Findings Continued

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

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Findings Continued

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

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Findings Continued

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

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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

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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

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Limitations

• Reasons for School Moves are Not Known
• Pre-mobility Issues are not Considered
• Two Years of Data
• Missing Data

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Implications for Further Research

• Qualitative Study Component
• Interviews with youth
• Housing Situation Comparison
• Foster Care Placement Comparison
• Transportation Services as a Factor

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Questions

• Why Data?

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Contact Information

• Laura Tanner-McBrien, Ed.D.
• 1350 M. St., Building B
• Fresno, CA 92721
• Phone [phone]
• Fax [phone]
• laura.mcbrien_at_fresnounified.org