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

 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.

 For Identification  For Delivering Services  For Monitoring Academic and Behavioral Success  To Track Student Success  To Report Out the Success of a Program

 Grants  District Funds  District Support  Community Donations or Support

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.

Project ACCESS – Homeless Codes AAWAITING FOSTER CARE DLIVING IN A DOUBLED-UP SITUATION FFORMERLY HOMELESS – Do Not Qualify for Services MLIVING IN A MOTEL OOTHER, HOMELESS ACCORDING TO HSS RRUNAWAY, POSSIBLY STAYED AT THE SANCTUARY SLIVING IN A SHELTER TTRANSIENT (many moves) UUNACCOMPANIED YOUTH (Caregiver Affidavits)

Project ACCESS – Foster Care Codes Foster Family Agency11 Relative Home21 Guardian Home22 Tribe Specified Home23 Foster Family Home31 Foster Family Agency Certified Home32 Small Family Home41 County Shelter/Receiving Home51 Group Home52 Court Specified Home53

 History or Pattern of Services  Gather Information About a Family  Track Services Provided to a Family  Evaluate Services Provided to Families  For Program Evaluation

 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  

Add new record Refresh ServiceEligibileParticipationBeginsExpiresCodeModified By Modified Date Project ACCESS - Homeless False 07/01/1008/25/10D Laura Tanner- Mcbrien 8/25/2010 4:01:38 PM Edit Project ACCESS - Homeless True 08/25/10U Laura Tanner- Mcbrien 8/25/2010 4:01:51 PM Edit Student Attendance Review Board False 07/01/0907/12/091 9/2/2010 1:24:36 PM Edit

Data Fields Meanings  ID Identification Number  Last Name Last Name  First Name First Name  School School Number  Grade Grade Level  Gender Male or Female  EthnicEthnicity  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

Program Fields Meaning  Program Program Title  Beginning Date Date Began Program  Level of Service Active or Not  Ending Date Date Services Ended

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

Behavioral DataMeaning  Behavior Behavior log data  Supensions Number of suspensions  Expulsions Number of expulsions

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

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

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

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

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

 7 th – 12 th Grade Homeless Students  7 th – 12 th Grade Foster Youth  7 th – 12 th Grade Non-Mobile or Housed Comparison Group  6 th Grade Students were included in the data for comparison with 7 th Grade data

Dependent Variables  GPAs  Math CST Scores  LA CST Scores  % Attendance  Credits Earned  Suspensions Independent Variables  School Moves  Address Moves

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?

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?

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

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 9 th – 11 th grades were inconsistent

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

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

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

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

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

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

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 and 20% of the variance between academic variables in

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

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

Why Data?

Laura Tanner-McBrien, Ed.D M. St., Building B Fresno, CA Phone: Fax: