Marit Kjærnsli

Students’ Preference for Science Careers: International comparisons based on PISA 2006

This article deals with 15‐year‐old students’ tendencies to consider a future science‐related career. Two aspects have been the focus of our investigation. The first is based on the construct called ‘future science orientation’, an affective construct consisting of four Likert scale items that measure students’ consideration of being involved in future education and careers in science‐related areas. Due to the well‐known evidence for Likert scales providing culturally biased estimates, the aim has been to go beyond the comparison of simple country averages. In a series of regression and correlation analyses, we have investigated how well the variance of this construct in each of the participating countries can be accounted for by other Programme for International Student Assessment (PISA) student data. The second aspect is based on a question about students’ future jobs. By separating science‐related jobs into what we have called ‘soft’ and ‘hard’ science‐related types of jobs, we have calculated and compared country percentages within each category. In particular, gender differences are discussed, and interesting international patterns have been identified. The results in this article have been reported not only for individual countries, but also for groups of countries. These cluster analyses of countries are based on item‐by‐item patterns of (residual values of) national average values for the combination of cognitive and affective items. The emerging cluster structure of countries has turned out to contribute to the literature of similarities and differences between countries and the factors behind the country clustering both in science education and more generally.

PISA and scientific literacy: similarities and differences between the nordic countries

In this paper we have set out to search for similarities and differences between the Nordic countries concerning patterns of competencies defined as scientific literacy in the Programme for International Student Assessment (PISA) study. The first part focuses on gender differences concerning the two types of competencies, understanding of scientific concepts versus skills in scientific reasoning, based on analyses of sum scores of groups of items. The second part focuses on differences and similarities between countries based on item‐by‐item analyses. Correlations between each Nordic country (as well as the Nordic group as a whole) and every other country have been used to look for a Nordic pattern. In the last part cluster analysis has been used to see how countries establish clusters and whether these clusters represent meaningful groups in a geographical, cultural or political context.

Timss Science Results Seen from A Nordic Perspective

In this chapter we describe some characteristic features of the TIMSS science results as seen from a Nordic perspective, and in particular; Norway. Four out of the five Nordic countries participated in TIMSS: Iceland and the three Scandinavian countries, Denmark, Norway, and Sweden. (Finland did not take part, but participated as the only Nordic country in the repeat of TIMSS in 1999.) These four Nordic countries have much in common historically, culturally and politically. In the Scandinavian countries almost the same language is spoken, whereas Icelandic is different, but quite similar to the old common Nordic language. During the last six or seven hundred years Sweden and Denmark have rivaled each other for hegemony in the area, while Norway, Iceland, and Finland have been the smaller brothers in union with one or the other for most of the time. Today all Nordic countries are independent democracies with a strong social democratic tradition. They are relatively homogeneous societies with highly developed welfare systems. There are also strong and friendly cultural links among the Nordic countries, even if the European Union has split these countries into members (Denmark, Finland, and Sweden) and non-members (Iceland and Norway). Sweden has the largest population, eight million, whereas Denmark, Finland, and Norway all have between four and five million. Iceland has a small population, about 200,000. It should also be mentioned that the climate is similar in all of these countries. Denmark stands out from the other Nordic countries in two respects: firstly, due to its position closer to the other North European countries it appears more “continental” both in climate and culture; and secondly, its relatively high population density makes Denmark somewhat different from the typical Nordic countries which have wilderness within easy reach of even the largest cities.

Students’ test motivation in PISA: the case of Norway

ABSTRACT Do students make their best effort in large-scale assessment studies such as the Programme for International Student Assessment (PISA)? Despite six cycles of PISA surveys from 2000 to 2015, empirical studies regarding students’ test motivation and experience of the tests are sparse. The present study examines students’ test motivation in PISA, and how closely students’ achievement correlates with students’ reported test motivation. A total of 40 students from eight schools that participated in the PISA study in 2006, 2009 and 2012 were interviewed. In addition, questionnaire data from a total of 9400 students who participated in PISA 2009 and 2012 were collected. The findings of this study indicate that students overall were motivated to do their best in the PISA study, despite the fact that these low-stakes tests have no impact on students’ grades or future school entrance. In contrast to claims in the media, where it has been suggested that Norwegian students are more relaxed towards the PISA test than students in other countries, students report that they are motivated to do their best, but girls report significantly higher test motivation than boys. Despite the policy influence of PISA and the large number of countries participating, very few studies have reported findings from students’ perspectives regarding their test motivation and experience of the test. The present study aims to fill that gap.

Science Teaching and Learning in Schools: Theoretical and Empirical Foundations for Investigating Classroom-Level Processes

In order to develop students’ scientific competencies systematically, educational experiences in school, especially high-quality classroom level processes, are crucial. The integration of educationally-relevant teaching variables in International Large-Scale Assessments provides an opportunity to analyze components of instructional quality within and between countries. This chapter outlines pivotal considerations and challenges in developing constructs in the field of science teaching and learning in schools that were implemented in the Field Trial student questionnaire of the Programme for International Student Assessment (PISA). It aims to identify educationally relevant teaching variables based on the current theoretical and empirical background of research in science education. In addition, it proposes a framework for describing science teaching and learning in school, investigating country-specific profiles, and analyzing the relationship between science teaching and students’ cognitive and non-cognitive outcomes. The constructs for the Field Trial presented at the end, consider both design-related limitations and trend issues concerning previous PISA cycles.

Country profiles of scientific competence in TIMSS 2003

The aim of the present contribution is to investigate similarities and differences of strengths in science competences between countries, based on TIMSS 2003 data. Analyses are based on systematic investigation of patterns of p values for individual science items. Hierarchical cluster analysis was applied to establish meaningful groups of countries. The resulting pattern of how countries cluster together into groups of increasing size is presented and discussed. The features for each group of countries are described in terms of relative strengths according to item format, subject domain, and cognitive domain. Finally, the measures on relative strengths in subject domain were compared to the relative emphases in the intended curriculum and in the implemented curriculum (percentage of topics taught in the classroom). It turned out that the data on emphases in the classroom could explain more of the relative strengths and weaknesses than the intended curriculum.