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SECME Program Data Collection

SECME Program Data Collection

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SECME Program Data Collection

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  1. SECME ProgramData Collection SECME: STEMulating Minds September 23, 2010 Miami Dade College, North Campus Ava D. Rosales, PhD Instructional Supervisor Miami-Dade County Public Schools

  2. SECME: STEMulating Minds It takes (A)… Try it attitudeEnjoymentActionMotivation

  3. Mini-Grants SECME Model Student Scholarships National Level Scholarships to Summer Institute Professional Development District Olympiad Competition District Level Engineering Site Field Trip Networking with Teachers and Engineers Nationally Saturday Design Seminars National Student Competition Provides Engineer and University Support Sponsors National Summer Institute School Level Club meetings Sponsors Teachers to Summer Institute Classroom activities People and Expertise Teachers Counselors Administrators Parents Students Participate in Olympiad Shadow an Engineer Day Guest speakers Involve parents Resource and Materials Student , Parent and Teacher Recognition Student data Longitudinal Data Statistics Awards Banquet… M-DCPS Curriculum and Instruction, Science Education 2006 Communications Network

  4. M-DCPS SECME PROGRAMWhat makes it work? • Teacher, counselor, and parent resource • Engaging hands -on student activities that enhance mathematics, science, and engineering concepts • Collaboration with experts, colleges and industry • Student, teacher, parent motivation • District support - program coordination M-DCPS Curriculum and Instruction, Science Education 2006

  5. SECME ENHANCES MATHEMATICS AND SCIENCE CURRICULUM CURRICULUM SECME Inquiry based learning Mathematics and science applications to solving real world problems School to Career Initiative Engineering design seminars Engineering design and construction (bridges, mousetrap cars, egg drop containers, water bottle rockets, robotic hand) Workshops at Colleges, shadow an engineer day, engineering site field trips, guest speakers M-DCPS Curriculum and Instruction, Science Education 2006

  6. Saturday Design Seminar Dates • October 16 – Waterbottle Rocket @American High • October 16– Robotic Hand @American • October 30 – Mousetrap Car @UM • November 13 – Bridge @FIU College of Engineering • Weekly briefing will be sent to schools • Posted at District SECME Website • Posted at Professional Development portal

  7. Collaborative Consensus • What is your team name? • What will your team motto or slogan be? • Where would your team prefer to eat? • What is your team song? • What famous person would most likely join your team and why?

  8. District SECME Website

  9. Registration code for National Office FL19

  10. Norms • Don’t be afraid to ask the essential questions. • Actively participate. • Take time to observe, listen, and reflect. • Acknowledge individuality.

  11. Outcomes

  12. Please Do Now… List the reasons for analyzing student data. Y. Wongbundhit

  13. Reasons for Analyzing Student Data Assess the current and future needs of students. Decide what to change. Determine if goals are being met. Engage in continuous school improvement. Identify root causes of problems. Provide differentiated instruction for students. Y. Wongbundhit

  14. Collect Data Data Analysis System Plan and Question Use Results and Take Action Analyze and Interpret Data Y. Wongbundhit

  15. Y. Wongbundhit

  16. Steps at a Glance

  17. Why collect data?

  18. What Data Do I Need? Qualitative Quantitative

  19. Direct measures of student learning: • State and local standards-referenced assessment results • Norm-referenced test results • College and post-secondary examination scores • Vocational assessment results

  20. Indirect measures of student learning: • Course participation rates • Grade point • Rates of participation in advanced coursework or extended learning opportunities • Graduation rates • Post-secondary placement rates

  21. Demographic indicators that may affect student learning: • Behaviors  • Attendance rates • Dropout rates • Discipline and violence rates • Characteristics • Ethnicity • Gender • Socio-economic status • Language status • Disability status • Migrant status

  22. Context variables that may affect student learning: • School and class size • Teacher level of training and experience • Parent-school partnerships • School climate as perceived by students, staff, and community • Student pre-school experience • Student and staff mobility

  23. Always focus on the Goal(s)… • Focus on the ultimate outcome(s) of the SECME program. • Ask “What difference will SECME make in the long run?” e.g., What impact will it have on learners?

  24. Where’s the Data? • Data warehouses • District Assessment Office, State • School • Student records • Classroom • Gradebook • SECME events • Surveys, observations, questionnaires,

  25. What Next? • Disaggregate • Analyze

  26. Presentation Models

  27. Percentage of Title I SECME Schools • Total # of Participating SECME Schools 2004 - 2005 • 40 Elementary • 27 Middle • 22 Senior High • 1 K-8 Centers • 2 Alternative Note: Based on the number of Title I Schools in the District

  28. District and SECME Performanceon the 2005 FCAT SSS Mathematics, by Ethnicity, All Students Tested, Grade 5

  29. Site Visits and Seminars • Participating in SECME makes me feel: • “like I am a part of something special” –African American male SECME student, grade 11 • Participating in SECME makes me feel: • “like I can do something that I would never think I can”–African American female SECME student, grade 10

  30. Participating in SECME makes me feel: • “like an engineer”–Hispanic male SECME student, grade 8 • Participating in SECME makes me feel: • “like I’m an engineer in training!”–Hispanic female SECME student, grade 11

  31. “My son wants to be a rocket scientist. Before SECME he wanted to be a rapper.” -Elementary School SECME Parent

  32. Surveys Electronic – fast and efficient • District/Central Office website form-fill • Free Online Surveys • • Affordable Fee Online Surveys • Survey Gold • Zoomerang Paper/Pencil Surveys – accessible to all

  33. Look for the story in the data

  34. Contact Information Ava D. Rosales, PhD 305-995-4537