Title Northern Lights on TIMSS and PISA 2018 English 2.4 MB 224
##### Document Text Contents
Page 1

Northern Lights
on TIMSS and
PISA 2018

http://crossmark.crossref.org/dialog/?doi=10.6027/TN2018-524&domain=pdf&date_stamp=2018-09-04

Page 112

110 Northern Lights on TIMSS and PISA 2018

and lower-performing students might, for example, have reported high levels of self-
efficacy without this being evidenced in their performance on the PISA test, and there
might be other variables that are also important for explaining the science performance
of modern youth.

Table 4: Regression coefficients and amount of variance explained (R2), science performance as the
dependent variable. Results from PISA 2006 and PISA 2015 for the Nordic countries

Predicted variable:
Science performance

Instrumental
motivation

Enjoyment of
learning science

Science self-efficacy All variables
R2

Country and year 2006 2015 2006 2015 2006 2015 2006 2015

Denmark 0 −1 14 19 34 15* .22 .15
Finland 13 3* 12 22* 32 16* .24 .14
Iceland 2 0 25 20 24 8* .28 .14
Norway 0 −4 24 24 22 14* .21 .17
Sweden 7 −2* 15 23* 27 13* .21 .15

Note: Statistically significant regression coefficients are indicated in italic. When the difference between
the coefficients within a country is significant between 2006 and 2015, this is indicated with an
asterisk on the 2015 value.

Italic = p < .01, meaning that the value is statistically significant at the 1% level.

* = change in coefficient between 2006 and 2015 is significant.

The values in Table 4 are b-coefficients from the regression analysis, together with R2,
which is a measure of how much of the variation in the data can be explained by the
regression model. The b-coefficients can be interpreted as follows. A one-step increase
of the value in the respective interest index (for example, enjoyment of learning science)
will result in a performance increase corresponding to the value of the b-coefficient. An
increase in the enjoyment of learning science index in Denmark in 2006 from 0.5 to 1.5
will have a positive effect on science performance, which will increase the PISA score
by around 14 points according to the model (an increase of 30–40 points on the PISA
test is generally regarded as corresponding to one additional year of schooling). An
increase in the instrumental motivation index in Denmark 2006, on the other hand, will
not have any significant effect on science performance according to the model.
Therefore, even if instrumental motivation is significantly related to performance when
other interest variables are not accounted for, this relationship disappears when
controlling for the other interest variables. This result was obtained for all Nordic
countries and for both years, except for Finland in 2006. We also tested whether the

Page 113

Northern Lights on TIMSS and PISA 2018 111

regression coefficients were significantly different (p < .01) between the two years and
in all Nordic countries, and the b-coefficient for science self-efficacy was significantly
smaller (although still significant) in 2015 than in 2006. For Sweden and Finland, there
were also significant changes in the coefficients for the variables instrumental
motivation and enjoyment of learning science, while this was not the case in Denmark,
Iceland, or Norway. Thus, in the Nordic countries, in particular the effect of science self-
efficacy on science performance was significantly lower in 2015 than in 2006. At the
same time, students in all Nordic countries except Finland reported higher levels of
science self-efficacy in 2015 (Table 3).

In summary, a student who enjoys science and trusts in their ability to solve science-
related questions (self-efficacy) tends to score better on the PISA test. This was true in
2006 as well as in 2015.

4.3.5 Science-related career expectations

Over the past several years, there has been an emphasis on the importance of recruiting
more individuals to education and careers in science and technology. Therefore, the
relation to science and technology. In both PISA 2006 and PISA 2015, the students were
asked to respond to an open-ended question: What kind of job do you expect to have
when you are about 30 years old?

The students’ responses were given in their own words and could be any job title or
description. All responses were classified according to the International Standard
Classification of Occupations (ISCO-08). However, many students at this age are unsure
of what profession they expect to have, and many students did not answer or indicated
that they were undecided. In this context we focused only on student responses that
were well-defined expectations of a science-related career, defined as those career
expectations that require the study of science beyond compulsory education. These
responses were categorized into the following major groups: science and engineering
professionals; health professionals; science-related technicians and associated
professionals; and information and communication technology professionals (see
OECD, 2016a, Annex A1 for more details).

Page 224

Nordic Council of Ministers
Nordens Hus
Ved Stranden 18
DK-1061 Copenhagen K
www.norden.org

Northern Lights on TIMSS and PISA 2018
The results from PISA 2015 and TIMSS 2015 were published in November
and December 2016. All the Nordic countries participated in PISA.
Denmark, Finland, Norway and Sweden participated in TIMSS grade 4
and Norway and Sweden participated in TIMSS grade 8.

The Nordic countries have similarities but also differences, which makes
it interesting and valuable to carry out analyses in a Nordic perspective.
In this report researchers from all the Nordic countries have done
in-depth analyses on different policy relevant themes based on the results
presented in 2016. The purpose of this report has been to present policy
relevant analyses of TIMSS and PISA in a way that is accessible for
policy makers on different levels in the Nordic countries, with the aim to
contribute to further development in the education area.

http://www.norden.org