Demographic Information that can affect accountability measures Doug Wells Lake Elsinore Unified School District Riverside County Assessment Network December 10, 2010

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

 Student information systems  Personnel who enter demographic data  Who extracts demographic data?  Who reviews demographic data?  Is accurate in January accurate in May?

 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 testing cycle  A student who enters March 12 – not in scores  A student who enters March 16 – in scores

 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

 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

 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

 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

 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

 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

 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?

Doug Wells Administrator: Assessment & Accountability Lake Elsinore Unified School District (951)