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Learning Mathematics for Life

A Perspective from PISA

image of Learning Mathematics for Life

People from many countries have expressed interest in the tests students take for the Programme for International Student Assessment (PISA). Learning Mathematics for Life examines the link between the PISA test requirements and student performance. It focuses specifically on the proportions of students who answer questions correctly across a range of difficulty. The questions are classified by content, competencies, context and format, and the connections between these and student performance are then analysed.

This analysis has been carried out in an effort to link PISA results to curricular programmes and structures in participating countries and economies. Results from the student assessment reflect differences in country performance in terms of the test questions. These findings are important for curriculum planners, policy makers and in particular teachers – especially mathematics teachers of intermediate and lower secondary school classes.

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Annex A5

Analysis of Variance Related to Item Format

This annex provides technical details for the analysis of variance performed for the item format section of Chapter 5. In all cases a Full Factorial ANOVA was performed in SPSS using a univariate GLM procedure. The dependent variable in all cases was defined as item difficulty in logits centered at 0 for each country. The two factors in all cases were the same: country and item-format. In the first case no other factors were added (see Table A5.1), in the subsequent cases one of the following factors were added (Table A5.2-Competency, Table A5.3-Context, and Table A5.4-Word-Count). Table A5.5 presents the distribution of items by item format and traditional topic groupings. Please note that interactions between topics and item format were not considered due to the very small number of items in each cell (see Table A5.5). Table A5.6 presents post hoc comparisons for item format mean difficulties using the Bonferroni adjustment for multiple comparisons. In addition to the F statistics, that shows significance of main effects and interactions, partial ..2 is also provided to assess for the percent of total variance in the dependent variable accounted for by the variance between categories (groups) formed by the independent variable(s).

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