260 likes | 391 Views
Data Collection for Homeless Education Programs. Diana Bowman, NCHE Carol Calfee, Santa Rosa School District (FL) Lynn Brown, Montgomery County Public Schools (MD) . Goals for Today’s Session. A brief overview of using data collection for program improvement:
E N D
Data Collection for Homeless Education Programs Diana Bowman, NCHE Carol Calfee, Santa Rosa School District (FL) Lynn Brown, Montgomery County Public Schools (MD)
Goals for Today’s Session A brief overview of using data collection for program improvement: • Standards and Indicators for quality MV programs • Planning for data collection • Analyzing data • Managing data National Center for Homeless Education • www.serve.org/nche
Standards and Indicators for Quality McKinney-Vento Programs • Developed in 2001 by representative task force • Included in U.S. Department of Education Guidance • Pilot tested in 2002-2004 • Guidebook developed based on pilot test group’s experiences • Revised in 2005 (http://www.serve.org/nche/products_list.php#st_and_ind_2006_rev ) National Center for Homeless Education • www.serve.org/nche
A Good Framework • 10 performance standards—3 groups: outcomes, school/LEA support, collaboration • Based on federal law • Reflect 5 years of effective practice in implementing the McKinney-Vento Act • Include items required for federal data collection (# enrolled, services, # tested, proficiency, services, # served pre-K - 12) • Utilize standard and indicator language that focuses on quantifiable outcomes • Suggested indicators for each standard National Center for Homeless Education • www.serve.org/nche
Revised Standards Student Achievement and Performance Outcomes 1. All homeless students, identified and enrolled at the time of the state assessment, take the state assessment required for their grade levels. 2. All homeless students demonstrate academic progress. National Center for Homeless Education • www.serve.org/nche
Standards cont. School/LEA Support Outcomes • All children in homeless situations are identified. • Within one full day of an attempt to enroll in school, homeless students are in attendance. • All homeless students experience stability in school. • All homeless students receive specialized and comparable services when eligible. National Center for Homeless Education • www.serve.org/nche
Standards cont. 7. All preschool-aged homeless children enroll in and attend preschool programs. 8. All homeless unaccompanied youth enroll and attend school. National Center for Homeless Education • www.serve.org/nche
Standards cont. Collaboration Outcomes 9. All parents (or persons acting as parents) of homeless children and youth are informed of the educational and related opportunities available to their children and are provided with meaningful opportunities to participate in their children’s education. 10. LEAs help with the needs of all homeless students through collaborative efforts both within and beyond the LEA. National Center for Homeless Education • www.serve.org/nche
Raising good questions • To what extent does our program align with the Standards for Quality McKinney-Vento programs? • Are numbers or percentages increasing or decreasing from year to year? What does that tell us? • How does performance compare to the school district average? • What strategies or activities support outcomes? Are the strategies and activities appropriate or sufficient? • Are current data sources sufficient for informing us about our program? National Center for Homeless Education • www.serve.org/nche
Planning for Data Collection • Get buy-in for data collection– “We’re direct service providers!” – Do your school district, funders, state department of education believe that this is time well spent? Do you? • Assess your time and resources available and develop a realistic plan to meet your needs and purposes Collect all the data and only the data that you will need. National Center for Homeless Education • www.serve.org/nche
Purposes for Data Collection Be explicit about intended uses of data • Accountability • Program improvement • Advocacy • Understanding trends and comparisons • Funding Develop a plan that matches purpose, audience, and data National Center for Homeless Education • www.serve.org/nche
Planning What Data to Collect • A logic model is a graphic representation of the relationships among the key elements of a project (impact, outcomes, activities). • Helps to articulate the key elements of the project. • Can lead to evaluation efficiency and effectiveness. • Promotes stakeholder buy-in by helping clarify how the project works. Coffman, J. (1999). Learning from Logic Models. Cambridge, MA: Harvard Family Research Project. National Center for Homeless Education • www.serve.org/nche
Logic Model for McKinney-Vento National Center for Homeless Education • www.serve.org/nche
Data Questions Based on the Logic Model Activity 1. Facilitate immediate enrollment • Are new program participants enrolled in school within one day? • Data needed: Date family first came to school to enroll the child; date child began attending classes Outcome A. Students do not miss days • How many days did students miss between schools? • Data needed: Last day attended school of origin and first day attended new school National Center for Homeless Education • www.serve.org/nche
Activity Using the Logic Model template provided and the handout on the MV Standards and Indicators, • Choose one outcome (Standard) • Identify activities that will lead to this outcome • Develop questions for one of the activities that would indicate (Indicators) that this activity is working • Identify data that would enable you to answer these questions • Share with your neighbor National Center for Homeless Education • www.serve.org/nche
Types of Data Quantitative Data Examples (How many) • Number of homeless students enrolled • Type and number of services provided Qualitative Data Examples (How well) • Open-ended responses to survey items • Interviews/Focus Groups • In-take forms “In our school district, 54 percent of students identified as homeless remained in their school of origin.” What questions does this data raise? What qualitative data would be helpful? By what methods could you collect it? National Center for Homeless Education • www.serve.org/nche
Types of Data Perceptive Data Examples (What do you see? What do people think?) • Likert Scale Surveys – SA-A-D-SD • Checklists Informal data • Five-minute conversations • Phone logs and emails Anecdotal data • Stories that create awareness • Affective National Center for Homeless Education • www.serve.org/nche
Analyzing Data When and how often should we analyze our data? Consider: • Purpose for data collection • Time when the data will be most useful to you • Questions you’re addressing • Resources and time available to analyze National Center for Homeless Education • www.serve.org/nche
Match the analysis to the type of data Quantitative – frequencies, percentages, distributions, averages, statistics Qualitative - simple coding, key words, identify themes and trends Perceptive – frequencies, percent, distributions Youth Survey 1. I feel like school is a place where I can find help with personal problems – SA(2)-A(5)-D(8)-SD(5) How would you analyze this data? What does this tell you about your program? National Center for Homeless Education • www.serve.org/nche
Managing Data Collection Ensure that quality data is collected – • Provide clear guidelines for data collection - provide training, guidebook • No estimates; avoid using “unknown” as a choice • Use a clear data collection form; easy input (online); pilot test your form and/or instrument • Clarify terminology and methodology when working with other agencies • Spot check for errors; provide analysis to submitters to review National Center for Homeless Education • www.serve.org/nche
Accommodate Changing Data Needs Set up a “flexible” database to meet changing needs and requirements • Federal requirements will change • Data needs for program decision making will change • Make changes before the school year begins National Center for Homeless Education • www.serve.org/nche
Working with Collaborators Strategies for sharing information across programs and agencies • Agree on what can and cannot be shared • Reinforce how all will benefit – “win-win” • Note where definitions align/differ • Create awareness of MV program and data needs • Be organized and efficient in order to make the smallest demands on their time National Center for Homeless Education • www.serve.org/nche
Accessibility Making data easily available for decision-making • Who has the data? Can we get it from one source? • What analyses and reports exist? • How quickly can the data be made available? Is it in a useful format? • Are there staff capacity issues for pulling data together? • Confidentiality issues? Are data-sharing agreements in place? • Are there data that have not been collected that we need to impact decision making? How might we obtain this data? (Short-term, long-term) National Center for Homeless Education • www.serve.org/nche
Would you be prepared? A local foundation that is setting its budget priorities for the year contacted you to ask for information on the needs of homeless youth. The board needs this information for a meeting by the end of the week. • What should you have on hand to provide on short notice? • What should be in place to ensure that you can access data quickly from various sources? • How can you ensure that the data would be in a usable format on short notice? National Center for Homeless Education • www.serve.org/nche
NCHE’s Data Collection Networking Group 2008 • Online meetings, trainings, panel discussions • Networking with colleagues • Guiding NCHE in technical assistance offerings in data collection for homeless education programs Email: dbowman@serve.org Deadline – December 10 National Center for Homeless Education • www.serve.org/nche
Presenter Contact Information Diana Bowman National Center for Homeless Education SERVE Center, UNCG dbowman@serve.org 336-315-7453 Carol S. Calfee Director of Federal Programs Santa Rosa District Schools (FL) 850-983-5001; (Fax) 850-983-5011 CalfeeC@mail.santarosa.k12.fl.us Lynn T. Brown, Ph.D. Coordinator of Enrollment and Attendance Compliance Department of Reporting and Regulatory Accountability Montgomery County Public Schools (MC) 301-279-3211; (Fax) 301-279-3849 Lynn_T_Brown@mcpsmd.org National Center for Homeless Education • www.serve.org/nche