ICCS 2009 Technical Report - IEA

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The sampling variance SV mis calculated as the average of the sampling variance for eachplausible value SV P m :PSV µ = P1 S SVPp=1 m .Use of the P plausible values for data analysis also allows one to estimate the amount of errorassociated with the measurement of civic knowledge. The measurement variance or imputationvariance IV p is computed asPIV p =1P-1 S (µp–µ p=1 q q )2.Here, µ p is the statistic of interest computed on each plausible value p and µ is the meanq qstatistic based on all P plausible values.The estimate of the total variance TVµ, consisting of sampling variance and imputationvariance, can be computed asTV µ = SV µ + (1+ P 1 )IV µ .The estimate of the final standard error SE µ is equal toSE µ = TV µ.Table 13.3 shows the average scale scores as well as their sampling and overall standard errors.It also records the number of students that were assessed in each country. The comparisonbetween sampling and combined standard error shows that most of the error was due tosampling and that only a small proportion could be attributed to measurement error.Use of the IEA IDB Analyzer for estimating civic knowledge standard errors allowed bothsampling and imputation errors to be automatically calculated and combined. Alternativeapplications, such as the software package WESVAR (Westat, 2007) or the ACER SPSSReplicates Module, have similar features that make it possible to take the imputation error intoaccount when analyzing the plausible values.Reporting of differencesSignificance tests were conducted for:• Differences in population estimates between countries (multiple comparisons);• Differences between a country and the international average;• Differences in population estimates between subgroups within countries; and• Differences between population estimates in ICCS and in CIVED (estimation of changes).Differences between two score averages (or percentages) a and b were considered significant(p < 0.05) when the test statistic t was greater than the critical value, 1.96. The calculation of twas conducted by dividing the difference by its standard error, SE dif_ab :t = (a-b)SE dif_ab .In the case of differences between score averages from independent samples (evident, forexample, with respect to comparisons of country averages), the standard error of the differenceSE dif_ab can be computed as:SE dif_ab = SE 2 a + SE 2 b.Here, SE a and SE b are the standard errors of the means from the two independent samples a and b.SCALING PROCEDURES FOR ICCS questionnaire ITEMS265
Table 13.3: National averages for civic knowledge with standard deviations, sampling, and overall errorsCountryCivic Knowledge Sampling Error Combined Standard Number ofScore Error Assessed StudentsAustria 503 3.90 3.98 3,385Belgium (Flemish) 514 4.65 4.67 2,968Bulgaria 466 5.03 5.03 3,257Chile 483 3.48 3.54 5,192Chinese Taipei 559 2.40 2.44 5,167Colombia 462 2.92 2.95 6,206Cyprus 453 2.38 2.41 3,194Czech Republic 510 2.36 2.38 4,630Denmark 576 3.51 3.59 4,509Dominican Republic 380 2.41 2.41 4,589England 519 4.39 4.39 2,921Estonia 525 4.49 4.54 2,743Finland 576 2.33 2.39 3,307Greece 476 4.37 4.39 3,153Guatemala 435 3.77 3.78 4,002Indonsia 433 3.43 3.43 5,068Ireland 534 4.51 4.56 3,355Italy 531 3.25 3.29 3,366Korea, Republic of 565 1.87 1.92 5,254Latvia 482 3.97 3.99 2,761Liechtenstein 531 3.22 3.31 357Lithuania 505 2.74 2.84 3,902Luxembourg 473 2.20 2.23 4,852Malta 490 4.30 4.45 2,143Mexico 452 2.76 2.79 6,576New Zealand 517 4.94 4.97 3,979Norway 515 3.29 3.41 3,013Paraguay 424 3.41 3.41 3,399Poland 536 4.64 4.66 3,249Russian Federation 506 3.76 3.77 4,295Slovak Republic 529 4.39 4.49 2,970Slovenia 516 2.64 2.65 3,070Spain 505 4.11 4.13 3,310Sweden 537 3.08 3.10 3,464Switzerland 531 3.74 3.78 2,924Thailand 452 3.64 3.65 5,263Countries not meeting sampling requirementsHong Kong SAR 554 5.65 5.68 2,902Netherlands 494 7.54 7.62 1,969266ICCS 2009 technical report
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School sampling design 63Within-sch
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6ICCS 2009 technical report
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Table 9.9: Numbers of NRC responses
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Table 12.37: Item parameters for sc
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Figure 12.7: Confirmatory factor an
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Table B.21.1: Allocation of student
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ICCS collected data from more than
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• A 30-minute school questionnair
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ReferencesAmadeo, J., Torney-Purta,
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Table 2.1: Test development process
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PanelingPaneling is a team-based ap
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Development of constructed-response
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Table 2.6: Field trial item mapping
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Released test itemsTwo clusters of
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32 ICCS 2009 technical report
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• Civic identities, comprising tw
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The context of the wider community
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The international options offered t
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Some of the constructs measured thr
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Discussion with national centers an
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was that the test would focus on kn
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Asian questionnaire developmentThe
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Of these, the survey instruments (c
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Adaptation of the instrumentsIn the
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International translation verifiers
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Quality control monitor reviewIEA h
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Teacher target populationICCS defin
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Table 6.1: Population coverage and
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Table 6.2: School, student, and tea
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The team next selected a sample fro
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Systematic sampling was used for se
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In a small number of countries, the
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Class non-response adjustment (WGTA
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Teacher non-response adjustment (WG
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Calculating participation ratesFor
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Table 7.1: Unweighted participation
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The unweighted overall participatio
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Table 7.4: Weighted participation r
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Table 7.5: Categories into which co
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Table 7.7: Participation by country
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• The School Sampling Manual (ICC
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School coordinators were required t
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For countries administering the sch
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Scoring the ICCS assessmentThe succ
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Quality control throughout the data
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Table 8.3: Weighted percentages of
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ICCS International Study Center (20
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They received an overview of the st
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Survey administration activities du
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Table 9.3: Percentages of IQCM resp
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Table 9.9: Numbers of NRC responses
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Table 9.12: Numbers of NRC response
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The majority of countries used the
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ReferencesICCS International Study
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After the item-statistics review ha
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Documentation and structure checkFo
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Filter questions, which appeared in
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SummaryTo achieve a high standard o
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Test coverage and item dimensionali
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Table 11.1: Item total-score correl
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Assessment of scorer reliabilitiesT
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Table 11.3: Gender DIF estimates fo
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Table 11.4 shows the percentages of
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fell below 70 percent were removed.
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Table 11.6: National items excluded
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Table 11.7: Final item parameters u
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Table 11.9: Median test reliabiliti
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The approach chosen was essentially
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Figure 11.6: Scatterplot for link i
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Here, s 2 represents the variance o
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Table 11.15: Reliabilities for Euro
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ReferencesAdams, R. (2002). Scaling
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their parents’ levels of educatio
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Teacher questionnaireIndividual tea
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In the case of items with more than
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Figure 12.1: Summed category probab
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Table 12.1: Reliabilities for scale
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Table 12.4: Item parameters for sca
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Table 12.9: Reliabilities for scale
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Students’ attitudes toward instit
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Table 12.17: Reliabilities for scal
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Table 12.21: Factor loadings and re
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In Question 19, teachers were asked
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Figure 12.15: Confirmatory factor a
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Teachers’ reports of teaching civ
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School questionnairePrincipals’ r
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Page 263 and 264: Table 13.1: Numbers of sampling zon
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Page 273 and 274: Table 13.4: Coefficients of missing
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Page 281 and 282: SummaryThe jackknife repeated repli
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Page 285 and 286: Republic of KoreaTae-Jun KimKorean
Page 287 and 288: Appendix B: Characteristics of nati
Page 289 and 290: Table B.3: Allocation of student sa
Page 291 and 292: B.6. Colombia• Night schools, wee
Page 293 and 294: Table B.8.2: Allocation of teacher
Page 295 and 296: B.12. Estonia• Schools for adults
Page 297 and 298: B.14. Greece• Night schools and s
Page 301 and 302: B.20. Korea• Special education sc
Page 303 and 304: B.23. Lithuania• Special needs sc
Page 307 and 308: Table B.29.1: Allocation of student
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Page 311 and 312: B.34. Slovenia• Dislocated units
Page 313 and 314: B.36. Sweden• Special needs schoo
Page 315 and 316: B.38. Thailand• Special education
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Table C1: Descriptions of cognitive
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Table C1: Descriptions of cognitive
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Table D.1: List of international an
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Table D.3: Years of further schooli
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