ICCS 2009 Technical Report - IEA

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Dimensionality was explored in terms of the ICCS assessment framework content dimensions(civic society and systems versus others) and the ICCS assessment framework cognitive dimensions(knowing versus reasoning and analyzing). Multidimensional IRT models using ACER ConQuesttypically showed latent correlations over 0.90, thus indicating high similarity between the itemsubgroups. Given these results, a decision was made not to include reports relating to the civicknowledge subscales in the ICCS 2009 international reports.Assessment of item fitGoodness of fit for individual items can be determined by calculating a mean square statistic(Wright & Masters, 1982). Reviewing this residual-based item fit gives an indication of theextent to which each item fits the item response model. However, there are no clear rules foracceptable item fit, and some statisticians recommend that analysts and researchers interpretresidual-based statistics with caution (see, for example, Rost & von Davier, 1994). It wasconsequently decided to use a range of item statistics to assess item fit.ACER Conquest, Version 2.0 software (Wu et al., 2007) was used to estimate the itemparameters and to conduct the analysis of item fit.Table 11.1 shows the (corrected) item-total correlations of correct responses (or partial credititems) and the weighted item fit statistics. Only two items (CI2MOM1 and CI2HRM2) haditem-total correlations below 0.2 (indicating low discrimination), and only CI2HRM2 showedrelatively poor residual-based item fit (weighted mean square fit statistic of 1.23).Conquest was also used to generate item characteristic curves (ICCs). These provide agraphical representation of item fit across the range of student abilities for each item, includingdichotomous and partial credit items.Figure 11.2 shows the ICC for item CI2MOM1. Although the discrimination is not entirelysatisfactory and although Category 2 attracted responses from students with higher ability, itstill shows that the students with higher levels of knowledge were those most likely to give thecorrect response (Option 4) and that the students with lower levels were those more likely tochoose the incorrect option (2). This outcome led to the decision to retain this item for scaling.Figure 11.3 shows the ICC for CI2HRM2, another item with relatively poor itemdiscrimination. In this case, the curves for the correct response (2) and the curves for thedistractor that attracted the most student responses (Option 4) run almost parallel. It wasaccordingly decided to exclude this item from the final scaling.The functioning of the partial credit scoring guides was further analyzed through a review ofthe proportion of responses in each response category and the correct ordering of mean abilitiesof students across response categories. This analysis confirmed that the scaling properties of allsix partial credit items could be satisfactorily included in the scaling of student test data.SCALING PROCEDURES FOR ICCS TEST ITEMS131
Table 11.1: Item total-score correlations and weighted item fit for international calibration sampleItemItem-Score Weighted Item Item-Score WeightedCorrelation Item Fit Correlation Item FitCI2COM1 0.39 0.94 CI2PFM2 0.39 0.98CI2MOM1 0.19 1.12 CI2PCM1 0.32 1.03CI2MLM1 0.40 0.95 CI2PCM2 0.38 0.96CI2MLM2 0.28 1.05 CI2VOM1 0.37 0.97CI2PDO1 0.43 1.02 CI2VOM2 0.33 1.02CI2RDM2 0.38 0.98 CI2VOM3 0.40 0.92CI2SHM1 0.44 0.91 CI2DLM1 0.36 0.98CI2SHM2 0.37 0.91 CI2HRM1 0.39 0.96CI2TGM1 0.33 1.02 CI2JOM1 0.31 1.02CI2TGM2 0.27 1.07 CI2WFO2 0.37 1.20CI2BPM1 0.33 1.02 CI2PGM1 0.37 0.98CI2BPM2 0.36 0.99 CI2PGM2 0.34 1.01CI2GFM1 0.31 1.02 CI2ECM1 0.42 0.93CI2BIO1 0.36 1.04 CI2ECM2 0.27 1.07CI2GLM1 0.35 0.99 CI2CEM1 0.37 0.97CI2GLM2 0.33 1.01 CI2CEM2 0.20 1.13CI2FDM1 0.39 0.97 CI2WFO1 0.40 1.05CI2FSM1 0.41 0.96 CI2ORM1 0.43 0.94CI2SCM1 0.41 0.95 CI2RCM1 0.36 0.99CI2SCM2 0.28 1.07 CI2PJM1 0.20 1.13CI2ASM1 0.35 1.00 CI2PJM2 0.41 0.93CI2ASM2 0.40 0.95 CI2REM2 0.29 1.05CI2CNM1 0.38 0.98 CI2REM3 0.39 0.96CI2CNM2 0.46 0.89 CI101M1 0.40 0.96CI2ETO1 0.36 1.04 CI109M1 0.38 0.98CI2ETM2 0.26 1.08 CI108M1 0.26 1.08CI2BCM1 0.39 0.98 CI128M1 0.40 0.96CI2PRM1 0.33 1.02 CI137M1 0.36 0.98CI2CCM1 0.36 0.99 CI110M1 0.42 0.95CI2CCM2 0.34 1.01 CI113M1 0.41 0.96CI2SRM1 0.36 0.99 CI104M1 0.37 0.99CI2SRM2 0.40 0.97 CI115M1 0.37 0.99CI2SRM3 0.30 1.05 CI119M1 0.44 0.93CI2OMM1 0.29 1.06 CI120M1 0.30 1.02CI2OMM2 0.49 0.89 CI121M1 0.25 1.09CI2OMM3 0.35 1.01 CI127M1 0.23 1.10CI2HRM2 0.09 1.23 CI132M1 0.32 1.03CI2RRO1 0.43 1.03 CI129M1 0.33 1.02CI2DCM1 0.44 0.92 CI130M1 0.48 0.89CI2PFM1 0.31 1.01 CI106M1 0.46 0.90Note: International calibration sample. Item-total correlations below 0.2 and item fit values below 0.8 and above 1.2 are shaded in grey.132ICCS 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
Page 81 and 82: The unweighted overall participatio
Page 83 and 84: Table 7.4: Weighted participation r
Page 85 and 86: Table 7.5: Categories into which co
Page 87 and 88: Table 7.7: Participation by country
Page 89 and 90: 88ICCS 2009 technical report
Page 91 and 92: • The School Sampling Manual (ICC
Page 93 and 94: School coordinators were required t
Page 95 and 96: For countries administering the sch
Page 97 and 98: Scoring the ICCS assessmentThe succ
Page 99 and 100: Quality control throughout the data
Page 101 and 102: Table 8.3: Weighted percentages of
Page 103 and 104: ICCS International Study Center (20
Page 105 and 106: They received an overview of the st
Page 107 and 108: Survey administration activities du
Page 109 and 110: Table 9.3: Percentages of IQCM resp
Page 115 and 116: Table 9.9: Numbers of NRC responses
Page 117 and 118: Table 9.12: Numbers of NRC response
Page 119 and 120: The majority of countries used the
Page 121 and 122: ReferencesICCS International Study
Page 123 and 124: After the item-statistics review ha
Page 125 and 126: Documentation and structure checkFo
Page 127 and 128: Filter questions, which appeared in
Page 129 and 130: SummaryTo achieve a high standard o
Page 131: Test coverage and item dimensionali
Page 135 and 136: Assessment of scorer reliabilitiesT
Page 137 and 138: Table 11.3: Gender DIF estimates fo
Page 139 and 140: Table 11.4 shows the percentages of
Page 141 and 142: fell below 70 percent were removed.
Page 143 and 144: Table 11.6: National items excluded
Page 145 and 146: Table 11.7: Final item parameters u
Page 147 and 148: Table 11.9: Median test reliabiliti
Page 149 and 150: The approach chosen was essentially
Page 151 and 152: Figure 11.6: Scatterplot for link i
Page 153 and 154: Here, s 2 represents the variance o
Page 155 and 156: Table 11.15: Reliabilities for Euro
Page 157 and 158: ReferencesAdams, R. (2002). Scaling
Page 159 and 160: their parents’ levels of educatio
Page 161 and 162: Teacher questionnaireIndividual tea
Page 163 and 164: In the case of items with more than
Page 165 and 166: Figure 12.1: Summed category probab
Page 167 and 168: Table 12.1: Reliabilities for scale
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Page 171 and 172: Table 12.4: Item parameters for sca
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Students’ attitudes toward instit
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Figure 12.9: Confirmatory factor an
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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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Principals’ reports on the local
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Principals’ reports on school cli
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Figure 12.24 shows the results of t
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All of the items associated with Qu
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Figure 12.28 shows the results of t
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In Question 4, students were asked
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Question 4 asked students to rate t
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Students’ perceptions of public s
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Table 13.1: Numbers of sampling zon
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Table 13.2: Example of computation
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Table 13.3: National averages for c
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The ICCS international report also
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The software package HLM 6.08 (Raud
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Table 13.4: Coefficients of missing
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During the multiple regression anal
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SummaryThe jackknife repeated repli
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Staff at the IEA Data Processing an
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Republic of KoreaTae-Jun KimKorean
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Appendix B: Characteristics of nati
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Table B.3: Allocation of student sa
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B.6. Colombia• Night schools, wee
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Table B.8.2: Allocation of teacher
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B.12. Estonia• Schools for adults
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B.14. Greece• Night schools and s
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B.20. Korea• Special education sc
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B.23. Lithuania• Special needs sc
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Table B.29.1: Allocation of student
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Table B.32: Allocation of student s
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B.34. Slovenia• Dislocated units
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B.36. Sweden• Special needs schoo
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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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