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Findings emphasize the role of interdisciplinary links while reaffirming the importance of student performance in each core subject, with discussion grounded in NAEP limitations and TIMSS matrix-sampling design.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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Ma†  \nThe United States invented a matrix sampling technique to impute five plausible scores of student performance in its National Assessment of Educational Progress. That approach was adopted by a Trend in Mathematics and Science Study (TIMSS) for international comparison. In this paper, baseline data from TIMSS 1995 are analyzed at the seventh grade to examine correlation of plausible scores between mathematics and science. Canonical correlation is introduced to address a nonadditive nature of correlation coefficient and reduce Type I error in the result aggregation. Besides revealing the impact of interdisciplinary correlation, this investigation reconfirms importance of student performance in each core subject.  \nKeywords: canonical correlation, math & science achievement, international comparison.  \nAn Examination of Plausible Score Correlation from the Trend in Mathematics and Science Study  \nIn 2014, 46 states have adopted Common Core Standards and two additional states were moving toward the same direction (Fensterwald, 2014) . As a result, school districts were given the authority to change mathematics and science curricula in K-12 education (Brugger, 2014; Will, 2014) . Meanwhile, National Science Foundation (NSF) integrated its funding across science, technology, engineering and mathematics (STEM) education (NSF, 2013) . Alphonse (2014) predicted that \"STEM skills may be required in as many as 50% of future jobs\" (p. 15) .  \nTo assess learning outcomes in each core subject, National Assessment of Educational Progress (NAEP) produced report cards in mathematics and science for more than four decades (Jacob & Ludwig, 2009) . However, mathematics and science scores were gathered from different students. Thus, no national indicators can be developed to correlate mathematics and science achievements in NAEP (Johnson, 1998) .  \nInstead of reinventing a wheel to fill this void, it was designed in this study to borrow the wheel, i.e., using the Trend in Mathematics and Science Study (TIMSS) to construct a correlation indicator between mathematics and science achievements in international context. Although Program for International Student Assessment (PISA) is another well-known project, similar correlation  \n􀀍  \n†  \nProfessor, California State University, USA. Professor, University of Kentucky, USA.  \n[https://doi.org/10.30958/aje.3-4-1](https://doi.org/10.30958/aje.3-4-1) doi=10.30958/aje.3-4-1  \nanalyses cannot be conducted on PISA because the assessment data are collected in one subject each year. Hence, TIMSS is the only large-scale study that concurrently includes both mathematics and science assessments in its data gathering.  \nTo date, no one correlated STEM performance in TIMSS. While researchers attempted to examine 4th grade performance across disciplines (Martin & Mullis, 2013), their report was focused on reading demand in TIMSS testing, and did not include a correlational study of academic performance between mathematics and science.  \nIn the United States and many western countries, TIMSS researchers reported that mathematics and science curricula were \"one mile wide and an inch deep\" (Jakwerth, 1996; Schmidt et al., 2001) . While lengthy tests were needed to cover the broad curricula, a time-consuming test is not feasible for TIMSS assessment. As a compromise, TIMSS designated booklets to split the entire tests in mathematics and science, and each student answered questions in one booklet (Foy, Arora, & Stanco, 2013) . Thus, matrix-sampling techniques were introduced to impute five plausible scores of student performance in mathematics and science (Cogan, 1996) . The imputed scores were aggregated for dissemination in international report cards (Beaton et al., 1996a; 1996b) .  \nUnder an assumption that countries can learn from each other, this study is designed to construct correlation indi","cbCais9RScZ4omdD","https://ap.wps.com/l/cbCais9RScZ4omdD","pdf",698331,12,"English","# Introduction\n## Motivation and background\n## Why TIMSS is used over NAEP and PISA\n# Literature Review\n## International studies and matrix sampling\n# Method and Conceptual Framework\n## Canonical correlation rationale\n## Interdisciplinary correlation indicators","[{\"question\":\"What problem does the paper address about correlating mathematics and science performance?\",\"answer\":\"It targets the lack of national indicators to correlate mathematics and science achievements when scores come from different students, as in NAEP, and the absence of STEM performance correlation analyses in TIMSS prior work.\"},{\"question\":\"Why does the study use canonical correlation?\",\"answer\":\"Canonical correlation is introduced to handle the nonadditive nature of correlation coefficients and to reduce Type I error when aggregating results.\"},{\"question\":\"How are plausible scores obtained for mathematics and science in TIMSS?\",\"answer\":\"TIMSS uses matrix-sampling techniques: test booklets split the full assessments so each student answers a subset, and plausible scores are imputed and then aggregated for international reporting.\"}]","An Examination of Plausible Score Correlation from the Trend in Mathematics and Science Study - read online free | PDF",1792075022]