Analyzing Pre-ID Data

1. Analyzing Pre-ID Data Demographic Information that can affect accountability measures Doug Wells Lake Elsinore Unified School District Riverside County Assessment Network December 10, 2010

2. Importance of Accurate Pre-ID Data • Missing or inaccurate data usually affects accountability negatively • Accountability measures often are determined by a small number of students • True measure of what is going on in the schools • Not all fields are essential for accountability

3. Some Considerations • Student information systems • Personnel who enter demographic data • Who extracts demographic data? • Who reviews demographic data? • Is accurate in January accurate in May?

4. English Learner Related Pre-ID Data: New Students • Date entered U.S. schools • Less than 12 months = student not in calculations • Begins March 15 of the previous year • March 15, 2010 for the 2010-2011 testing cycle • A student who enters March 12 – not in scores • A student who enters March 16 – in scores

5. English Learner Related Pre-ID Data: R-FEPs • R-FEP Information • Typically are successful on state tests • R-FEP YES = scored Prof/Adv in ELA three times after reclassification • Student will not be in EL Subgroup • R-FEP NO = not scored Prof/Adv in ELA three times after reclassification • Student will be in EL Subgroup • District R-FEP determination may not match accountability determinations • LEUSD example • Considerations for R-FEPS • Three year determination begins after reclassification • A June 2010 reclassification would not utilize the spring 2010 CST scores • Three years Prof/Adv do not need to be consecutive • Things to watch for with R-FEPs • Elementary and middle school R-FEP YES? • Rare at a middle school; Almost impossible at an elementary school • School may never know a student as an EL • Important that teachers and administrators know who their R-FEPs are

6. Special Education Related Pre-ID Data • CMA/CAPA • Know early who the students are • Can use a CST label on a CMA or CAPA answer sheet • One message • Disability codes • Speech and Language, Autism, Orthopedic Impairment, Visual Impairment • Special Ed exit dates • Students counted in SWD subgroup for two years after exiting services • March 15, two years prior (March 15, 2009 for 2011 STAR) • Can be difficult data to obtain • Keep separate records

7. Socioeconomically Disadvantaged Pre-ID Considerations • Students are in the SED subgroup if: • Parent education level is less than a high school graduate • Student is on the National School Lunch Program • Communicate with teachers and principals who the SED students are • Cannot provide lists of NSLP students • Provide SED subgroup inclusion without identifying determining factor • NSLP data not typically kept with other data • This data is always changing • Economy • Divorce • Jobs • In subgroup because of current situation • Parent education levels are not always accurate • Education levels can be “inflated” • Ask the questions several ways

8. Race/Ethnicity Indicator • A student is either Hispanic or they aren’t • If His = Yes, nothing else is considered • If His = No, another field must be completed • No “decline to state” • Consider two-or-more races • In 2010, could not make safe harbor; no previous year data to compare growth

9. Pre-ID Considerations for all students • CBEDS • If a student enters the school district after October 6, 2010 = CBEDS NO for school and district • Student’s scores will not be in API/AYP calculations • Student will be in participation calculations • If a student moves from one school to another within the district = CBEDS YES for district; but CBEDS NO for any school • Data can be difficult to keep accurate • Difficult to compile for an entire year • Collect and maintain on a regular basis (weekly) • Site personnel do not make determinations; just ask questions and records answers

10. Pre-ID Considerations for all students • Labels vs. Documents • SSID well under 3% missing • Hand-bubbled answer sheets can push you over 3% limit • New students may not have an SSID at the time of testing\ • Need to be below 3% or will have to correct in summer • Extended Data Corrections • Free • Monitor demographic data from date of Pre-ID extract through testing • Make changes on ongoing basis – not at the end • System can be slow, especially in April, May • Fall Data Corrections • Review reports to determine number of students a target may be missed by • In smaller subgroups, a few students can make a large difference in percentages • Cost – but cheaper than Program Improvement if it can be avoided

11. Some things to Think About as STAR and CAHSEE Approach… • How much do you rely on your Student Information System for accurate data? • Do you trust that every clerk at a site is doing a great job (regardless of training)? • Who reviews demographic data – IT or Accountability? • Has every student’s demographic data been reviewed by an accountability expert? • Who answers to the Board, Cabinet, Principals and teachers in July?

12. Questions? Doug Wells Administrator: Assessment & Accountability Lake Elsinore Unified School District doug.wells@leusd.k12.ca.us (951) 253-7118