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Using International Benchmarking to Help Establish Internationally Competitive Performance Standards. Gary W. Phillips Vice President & Institute Fellow American Institutes for Research Next Generation Achievement Standard Setting Symposium CCSSO NCSA New Orleans LA June 25, 2014.
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Using International Benchmarking to Help Establish Internationally Competitive Performance Standards Gary W. Phillips Vice President & Institute Fellow American Institutes for Research Next Generation Achievement Standard Setting Symposium CCSSO NCSA New Orleans LA June 25, 2014
National and International Benchmarking • NAEP • TIMSS • PIRLS
International Benchmarking withPISA • The international benchmarking with PISA was replicated in in 2010 in three states (Hawaii, Oregon and Delaware) in three subjects (reading, mathematics and science). • The statistical linking with PISA was accomplished by embedding secure PISA items in the state assessment through a legally binding Memo of Understanding and Confidentiality Agreement between AIR and the OECD.
Common item Equating for PISA • About 30 items are embedded as field test items in the computer adaptive test in the state. • The computer adaptive field test algorithm randomly administered the PISA items. • Number items per student - If the state had F = 400 items for field testing, P = 30 PISA items, and the test length was L = 40, then the expected number of PISA items administered to each student was E( p ) = 1/F * L * P = 3. • Number students per item - If the student population size was N = 10,000, then the expected sample size per PISA item was E( n ) = 1/F * L * N = 1,000. • Number of items per student does not provide enough information per student to get estimates of PISA scores (i.e., distributions of PISA-plausible values). • Number students per item provides enough information per item to get good state-based estimates of the PISA item parameters.
