Oficinas Comerciales del Perú en el Exterior – OCEX y Promoción

The PIRLS 2011 study assessed reading literacy – students’ ability to understand and use written language forms required by the society and valued by the individual (Mullis et al. 2009a, 11) – for Grade 4 in 45 countries, including the Nordic countries Denmark, Finland, Norway and Sweden. The TIMSS 2011 study, which assessed students’ learning out- comes in mathematics and science for Grade 4 and Grade 8 (Mullis et al. 2009b, 19–21) coincided with PIRLS, offering the opportunity for as- sessing the reading, mathematics and science performance of the same students Grade 4. Three Nordic countries, Finland, Norway and Sweden, chose this option, while Denmark decided to implement PIRLS and TIMSS studies with separate student samples. As a national option, Nor- way implemented PIRLS and TIMSS studies also for Grade 5 students2

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(see van Daal et al. 2012). Additionally, Finland, Norway and Sweden measured students’ basic decoding skills in relation to the PIRLS test to study to what extent the basic reading skills explain performance in PIRLS reading comprehension test.

The material used in the present study consists of the Danish, Finnish and Swedish PIRLS 2011 and TIMSS 2011 Grade 4 datasets and the com- parable Norwegian Grade 5 data. These data provide an opportunity to consider low and top performance especially from the perspective of early recognition and support for low performance. The datasets include the student achievement data but also a large amount of background infor- mation gathered from students and their parents, teachers and school principals. Table 1 summarises the number of students and schools in the PIRLS and TIMSS datasets considered. The Norwegian Grade 5 dataset is essentially smaller than the other countries’ datasets, which reduces the power of statistical analysis of Norwegian data compared to the others. This must be kept in mind when examining the results.

The purpose of this study is to describe the characteristics of the top and low performers in reading and mathematics in the four Nordic coun- tries. More specifically: which background variables predict low and top performance in reading and in mathematics?

Table 1: Schools and students in the PIRLS and TIMSS 2011 datasets in the Nordic countries

Number of schools partici- pating in PIRLS Students as- sessed in PIRLS Number of schools partici- pating in TIMSS Students as- sessed in TIMSS Denmark Grade 4 232 4,594 216 3,987 Finland Grade 4 145 4,640 145 4,638 Norway Grade 5 53 1,258 54 1,270 Sweden Grade 4 152 4,622 152 4,482

For the purposes of this study, the low performers were defined as stu- dents below the intermediate international benchmark (475 score points) in PIRLS and in TIMSS. These students have achieved only the low interna- tional benchmark (400), if even that. Although nearly all the students in the Nordic countries reached the low international benchmark in reading, the percentage of students staying at that level (and not reaching the in- termediate benchmark) varied (see Table 2 below). The top performers were defined as those achieving the advanced international benchmark

(625 score points) in PIRLS and in TIMSS. In this article, the students with scores between 475 and 625 are called intermediate performers. In every country, the majority of students belong to this category, which is used as a reference group when examining the specific characteristics of low and top performers.

The factors affecting and predicting low and top performance were ana- lysed by three-level3 _{logistic regression models. A preliminary collection of} variables stemming from the PIRLS and TIMSS background questionnaires were selected in the exploratory analyses of our study. The variables were chosen to cover student, home, teaching and school characteristics that have been found important in previous research. The complete list of the variables selected for modelling is given in the appendix. The first target was to find those background variables which statistically significantly dis- tinguish low performers from the reference group of intermediate perform- ers. The top performers were not included in this analysis. An analysis of the top performance was then carried out correspondingly. Here, the target was to find the background variables which significantly distinguish top performers from intermediate performers. The low performers were not included in this analysis. These preliminary analyses were carried out sepa- rately for each country. Throughout the analyses, we used the conventional 5% limit as the criterion of statistical significance.

On the basis of preliminary modelling results, we then defined the final list of explanatory variables for the logistic regression model. In this final list, we included only those variables which appeared significant in at least one country. In other words, the variables which did not show statis- tical significance in any of the countries were not considered any longer. A similar model, containing the remaining variables, was then fitted sepa- rately for each country, whenever possible.4 _{The country-specific results}

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3 _{The sampling design of PIRLS and TIMSS studies produced datasets with a hierarchical structure: From}

each sampled school (school level) 1–4 classes were sampled (class level) and the students of these classes were then measured (student level). Valid statistical analyses thus call for methodology taking the three-level data structure into account.

were eventually compared to illustrate similarities and differences be- tween the Nordic countries.