Interest of latvian and lithuanian students in science and mathematics

Abstract

Interest is one of the most important components for a successful teaching/ learning process; unfortunately, nowadays students’ interest in science and mathematics is decreasing. The aim of the research is to explore the cognitive interest of 15-year-old students in science and mathematics. Students in Latvia and Lithuania participated in the survey; the data show that students’ cognitive interest in this area in both countries is mediocre. The factor analysis was used to single out four main dimensions of the cognitive interest – interest in the context, interest in mathematics, inquiry interest and enthusiasm. Students’ interest is higher in issues connected with practical life, the solution of real problems, but much lower if the problem to be solved needs effort, if they have to use mathematical tools. Enthusiasm is not characteristic for students. Only few respondents are willing to engage in science and mathematics in their leisure time. Latvian and Lithuanian students show slight differences in their interests. There are more Lithuanian students, who like mathematics and who are not afraid of difficulties. Latvian students, in their turn, show greater enthusiasm.

Full text

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INTEREST OF LATVIAN AND
LITHUANIAN STUDENTS IN
SCIENCE AND MATHEMATICS
Dagnija Cēdere,
Inese Jurgena,
Vilija Targamadze
Introduction
The science and technology education is closely connected with the
society’s development; however, many international and national studies
reveal the contradiction between the increasing societal needs and the
insucient level of young people’s education in this eld (Birzina, Cedere,
2017; OECD, 2016).
Interest is one of the components of intrinsic motivation and one of the
reasons why students may enjoy learning. What distinguishes it from other
sources of enjoyment is that interest is always directed towards an object,
activity, a eld of knowledge or goal (OECD, 2016). Interest is a strong mo-
tivator, the emotional stress which helps indirectly the memory processes
and makes the learning considerably easier. Interest is caused both by what
has been recognized in the experience and the new, what does not yet exist
in the newly developed experience. Thus, the source of interest is both the
surrounding environment and the learner’s own experience (Žogla, 2001, p.
179). Student’s interest in learning or the cognitive interest is one of the most
important creators of the learning motivation that inuences students’ en-
gagement and achievement in learning (Schiefele, 1991). Interest-triggered
learning activities lead to a higher degree of deep learning (Krapp, Prenzel,
2011; Osborne, Simon, & Collins, 2003; Uitto, Juuti, Lavonen, & Meisalo, 2008).
The cognitive interest plays a key role in inuencing the students’ learning
behaviour and their intention to participate in building their future. It is
characterized by their learning motive (why students learn) and the teach-
ing/learning strategy (how they learn). It represents a specic relationship
between the developing personality and some content of his/her life-space
(Aikenhead, 2005).
Dagnija Cēdere, Inese Jurgena
University of Latvia, Latvia
Vilija Targamadze
Vilnius University, Lithuania
Abstract. Interest is one of the most impor-
tant components for a successful teaching/
learning process; unfortunately, nowadays
students’ interest in science and mathemat-
ics is decreasing. The aim of the research is
to explore the cognitive interest of 15-year-
old students in science and mathematics.
Students in Latvia and Lithuania partici-
pated in the survey; the data show that
students’ cognitive interest in this area
in both countries is mediocre. The factor
analysis was used to single out four main
dimensions of the cognitive interest – inter-
est in the context, interest in mathematics,
inquiry interest and enthusiasm. Students’
interest is higher in issues connected with
practical life, the solution of real problems,
but much lower if the problem to be solved
needs eort, if they have to use mathemati-
cal tools. Enthusiasm is not characteristic
for students. Only few respondents are will-
ing to engage in science and mathematics
in their leisure time. Latvian and Lithuanian
students show slight dierences in their
interests. There are more Lithuanian stu-
dents, who like mathematics and who are
not afraid of diculties. Latvian students, in
their turn, show greater enthusiasm.
Keywords: cognitive interest, science and
mathematics, teaching/learning process.

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Problem of Research
The degree to which students’ interest in science and mathematics has been roused at school exerts the
most direct impact on their further studies in the higher education institution. Despite the teachers’ attempts to
increase the young people’s interest, the science and technology studies, unfortunately, lack the popularity (Birzina
& Cedere, 2017; Osborne, Simon, & Collins, 2003).
The lack of interest in science is an old issue and it still exists (Cedere, Gedrovics, Bilek, & Mozeika, 2014; Potvin &
Hasni, 2014). As mentioned by J. Osborne (2014), science education often fails to attain the intended goals because
students lack interest in the science subjects. The interest in mathematics has been comparatively less studied;
however, the close connection bet ween the science teaching/learning process and mathematics indicates a similar
trend, which is proved also by PISA (The Programme for International Student Assessment) studies (PISA, 2015).
The research ndings emphasize that the formation of interest is a complex process; it can change depend-
ing on students’ age and the teaching/learning environment. Usually the interest in basic school is higher and it
gradually decreases in the secondary school. Although the cognitive interest is one of the most signicant learn-
ing incentives, the relation between the student’s cognitive interest and the learning progress cannot be valued
unambiguously (Osborne 2014; Krapp & Prenzel, 2011).
Research Focus
Nowadays the strategy of science and mathematics education envisages a close unity between the theory
and practice, trying to ensure students’ active and meaningful participation in the teaching/learning process. The
conceptual solutions meant for improving the quality of education are mainly grounded on the context-based
learning (Broman,Bernholt,& Parchmann, 2015), the inquiry-based learning approach (Graeber, 2012), argumen-
tation and decision-making skills (Osborne, 2014; Mörk, 2005). If sciences are taught so that students understand
the immediate connection of knowledge with the real life situations in which they are personally interested, then
there is a hope that their interest in sciences will remain stable or even will increase (Pilot, Taconis, & den Brok,
2016). The teaching/learning strategies in mathematics have a similar orientation (France, 2010).
The concept of interest is used in dierent ways in the literature on science education. The concepts of situ-
ational interest and individual interest (stable interest), which are frequently used in pedagogical studies (Krapp &
Prenzel, 2011; Elster, 2007) are used to assess the depth and stability of the interest. Besides, in science interest is
treated in accordance with the guidelines and aim of the learning process. A model to explore the students’ interests
in physics is developed according to this principle (Haeussler & Homann, 2000). This model distinguishes three
dimensions of the interest: 1) interest in the concrete topic of physics (content); 2) interest in the concrete context
in which the topic of physics is presented; and 3) interest in the concrete activity in which the student can engage
in relation to this topic. The bi-dimensional interest model, which singles out two areas of interest – interest in the
content and interest in the context (Elster, 2007), is also used in science.
Students’ learning activity and learning motivation has become the determinative guiding motive in educa-
tion in Latvia and Lithuania during the last 15 years. The main school subjects of the STEM area that the 15-year
old students of Latvia and Lithuania acquire are the science subjects – biology, chemistry and physics as well as
mathematics.
Seeing the essence and values of science subjects and mathematics for the future life promotes the context-
based and inquiry-based approach in learning. Both approaches help students to gain a deeper and broader
understanding about what we know and how we know it. The inquiry-based learning provides a more authentic
idea about what sciences are and how they function (Kalnina, 2008; Lamanauskas, 2012).
However, the research shows that students not always achieve the desired outcome in the science subjects
and mathematics. It was found out in the comparative research of Latvian and Lithuanian students that was per-
formed more than ten years ago (Lamanauskas, Gedrovics, & Raipulis, 2004) that students’ science knowledge in
the countries worsened. The youth perceive nature mainly in a utilitarian way giving preference to such science
issues that demand less eort. Students’ activities in nature are mainly connected with recreation, including sports,
shing, hiking but students’ various observations in nature are less popular. According to OECD PISA 2015 data in
Latvia and Lithuania in comparison with mean indicator of the OECD participant countries, there is approximately a
twice smaller number of those students whose achievement corresponds to a high achievement level (PISA 2015).
Another study performed at the same time in Latvia obtained a similar result in relation to the cognitive interest,
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namely, only the fth part of Grade 9 (15-years old) students showed a high level of cognitive interest in science
subjects and mathematics (Cedere, Jurgena, Helmane, Tiltiņa-Kapele, & Praulīte, 2015). These facts indicate that
achievement in learning is closely connected with the cognitive interest.
Our intention in this research was to nd out how 15-year old students in Latvia and Lithuania evaluate their
interest in science. As the education strategies regarding the science subjects in the countries actually do not dif-
fer (Science Education in Europe, 2011), the results are comparable. Additionally, the authors wanted to single out
the main elds of interest in order to gain a better understanding about the mutual correspondence between the
teaching/learning process and students’ interests.
The following research questions were put forward:
•Do 15-year-old students learn science subjects (biology, chemistry, and physics) and mathematics with
interest in Latvia and Lithuania?
•Which are the main features that characterize students’ cognitive interest about science subjects and
mathematics?
•Is there a dierence between the 15-year-old students’ cognitive interest in science and mathematics
in Latvia and Lithuania?
Methodology of Research
General Characteristics
This research was carried out in the period from 2015 to 2017 in Latvia (LV) and Lithuania (LT). A students’
survey that describes their cognitive interest in science and mathematics was used in the research. Students par-
ticipated in the survey based on volunteering principle. Data were collected from dierent basic and secondary
schools in dierent regions of Latvia and Lithuania.
The key guidelines of science (biology, chemistry and physics) and mathematics education and strategies for
solving the problems do not dier signicantly in Latvia and Lithuania (Mathematics Education in Europe, 2011;
Science Education in Europe, 2011). Mathematics in both countries as a separate subject is taught already from
Grade 1 (4-6 lessons a week), biology, chemistry and physics as separate subjects – from Grade 7 or 8 (each subject
is taught 2 lessons a week). These subjects as compulsory are included in the national curricula of both countries
(BUP 2015 2017 keitimas; Izvērsta informācija par izglītības programmām).
Sample
The total number of students involved in the research was 990, of them – 536 (54%) were from Latvia and 454
(46%) from Lithuania. Students of the same age from both countries who learn in Grade 9 in both countries) or
the rst year at the gymnasium (only in Lithuania) participated in the survey. The average age of the respondents
was 15.1 years (SD = 0.59). The distribution of respondents by gender – 572 (58%) girls and 418 (42%) boys. The
distribution per country - distribution by gender in Latvia – 328 (61%) girls and 208 (39%) boys; in Lithuania – 244
(54%) girls and 210 (46%) boys.
Instrument and Procedures
The survey used the questionnaire which included questions, how students evaluate their cognitive interest
in science and mathematics (Part A, 14 items), which the main themes of interest are (Part B, 16 items) and what
is the attitude to science and mathematics lessons (Part C, 4 items). Content-wise the questionnaire corresponds
to the skills and attitudes that are mastered at school in biology, chemistry, physics and mathematics. The survey
focussed on students’ awareness of the importance of knowledge and skills in science and mathematics in the real
life and their readiness to act. The questionnaire comprised questions where the answer options corresponded to
the four-value Likert scale: 1 – no, 4 – yes (Schreiner, Sjøberg, 2004).
The questionnaire that had been applied previously in the research of the cognitive interest of a small students’
sample in Latvia (Cedere, Jurgena, Helmane, Tiltiņa-Kapele, & Praulīte, 2015). The participation of the students from
two neighbouring countries has broadened the range of respondents in this research. It opens the possibility
for a more profound study of the students’ cognitive interest gaining more general and substantiated indicators
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showing the tendency of the cognitive interest. The questionnaire was prepared on the internet using the Google
disc; students answered questions online. A link was announced to teachers who had agreed to participate in the
organization of the study.
The reliability (inter-item consistency) of the questionnaire according to Cronbach’s alpha coecient was 0.91.
Data Analysis
The mean values of answers M (1 ≤ M ≤ 4) and standard deviations (SD) were used to describe the respon-
dents’ opinions. In order to assess the credibility of the dierences of mean values in two reciprocally independent
groups, the t test analysis of the independent samples was used. To describe the dierences of the distribution of
respondents’ answers in two dierent groups, Pearson Chi Square test was applied. Cohen’s d was calculated for
estimating the eect size for the dierence between two means.
The factor analysis allowed grouping the information from a large number of features into a few factors, thus
obtaining a more obvious information about the students’ interests. Principal component analysis (PCA) with vari-
max rotation was applied. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy tests and Bartlett’s tests
for sphericity were used in order to nd if the PCA was appropriate for these data sets. In order to determine the
correct number of factors that had to be preserved in the PCA analysis, the parallel analysis was applied (Hayton,
Allen, Scarpello, 2004; Watson, 2017).
Cronbach’s alpha coecients were calculated for stating the reliability of the questionnaire and the reliability
of extracted principal components.
One sample Kolmogorov-Smirnov test was applied to determine if the distribution showed a normal distribu-
tion before the analysis. It was determined that all the distributions showed normal distribution (p < .001).
The data analysis was performed using the statistical software SPSS 23 program.
Results of the Research
Students’ Attitude to Science and Mathematics Lessons
Students’ answers to the question Do you think with pleasure about the biology/ chemistry/ physics/ mathemat-
ics lessons? provided a general idea about the Latvian and Lithuanian 15-year old students’ attitude to science and
mathematics. The mean values of the answers M (1 ≤ M ≤ 4) are only just a little above the average quantity of the
scale 2.5 that indicates an average liking to these subjects (Table 1).
Table 1. Students’ liking in learning biology, chemistry, physics and mathematics.
Items N M SE SD
Biology (C1) 925 2.82 .032 0.962
Mathematics (C4) 935 2.73 .035 1.078
Chemistry (C2) 933 2.51 .034 1.038
Physics (C3) 932 2.47 .034 1.041
The questions were answered positively (yes and rather yes) about biology by 29% and 35%, about chemistry
by 22% and 26%, about physics by 20% and 29%, about mathematics by 31% and 30% of respondents.
Principal Component Analysis
The factor analysis was applied to nd out the most important features of the science interest. This was the
way to search for reciprocally non-correlating items, reducing the number of factors characterising respondents’
cognitive interest. Questionnaires Part A and Part B were used for factor analysis.
First, the appropriateness of data for performing the factor analysis was found out. The KMO and Bartlett’s
tests helped to prove that the data were meaningful and compatible to perform the factor analysis. The KMO
measure of sampling adequacy was 0.91 and Bartlett’s test of sphericity was signicant (c2(496)=4637.10, p < .001).
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The principal component analysis (PCA) was performed using the extraction method with the succeeding
rotation of varimax with Kaiser normalization. Items with the factor loading no less than 0.40 were subjected to
the analysis. A critical decision in exploratory factor analysis is to determine how many principal components to
retain. The parallel analysis (PA) was used for this purpose (Figure 1). As seen in Figure 1, four of the eigenvalues of
the real data are greater than the average eigenvalues of the PA mean.
Figure 1: Plot of real data (PCA) and randomly generated eigenvalues (PA).
The parallel analysis indicates that four components or factors should be retained which explain 47% of the
variance and do not correlate reciprocally. The ndings obtained in the PCA are summarized in Table 2; it includes
the 17 most important items with the factor loading values above 0.60. Thus, the factor analysis allowed reducing
the initial number of quantities describing the students’ interest from 30 to 17 (excluded items see in Appendix).
The established factors describe four main dimensions of students’ interest and their distribution does not overlap
in two or more factors.
Table 2. Results of the principal component analysis with a varimax rotation of items.
Items M SD
Rotated factor load values
Factor 1 Factor 2 Factor 3 Factor 4
B9. Warming of the water in the glass container 2.89 1.17 .72
B2. Features of the air after the thunderstorm 3.05 1.12 .72
B8. Features of the soap solution 2.30 1.16 .71
B3. Growing and reproduction of plants 2.34 1.12 .68
B10. Purication of the drinking water 2.90 1.15 .68
B13. The use of maths in solving practical problems 2.23 1.14 .74
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Items M SD
Rotated factor load values
Factor 1 Factor 2 Factor 3 Factor 4
B14. Composition of maths equations 2.52 1.21 .72
B11. Exploration of maths relations of real problems 2.25 1.15 .71
A11. Maths tasks in lessons 2.99 .95 .67
A4. Explanation of natural phenomena 3.00 .81 .76
A5. Finding out the causes of natural phenomena 2.88 .77 .73
A7. Solution of problems related to natural resources 2.41 .92 0.66
A6. Analysis of problems connected with the real life 2.83 .85 .64
A2. Suggestions made in lessons 1.80 .95 .70
A3. Cooperation with the teacher 2.11 1.03 .65
A8. Exploration of nature outside the school 1.87 .99 .63
A14. Devoting the leisure time to science exploration 1.84 .91 .60
% of variance explained 16 11 10 10
Eigenvalues 4.76 3.29 3.09 3.01
Cronbach’s alpha .81 .78 .76 .66
Cronbach’s alpha for the items listed in the table: α = .85
Total variance explained: 47%
Factor 1 combines the interest related to the nature and practical life, items connected with the solution of
complicated tasks and the application of mathematics correspond to factor 2, factor 3 describes the interest to
explore and solve real problems and factor 4 reects students’ self-initiative and enthusiasm. The interest dimensions
corresponding to obtained factors describe the respondents’ interest from the point of view of the teaching/learning
content and the process. Thus, the cognitive interest is described by four main features or the dimensions of interest.
Dimensions of the Cognitive Interest
First dimension. Interest in the context
Items loading on the dimension, which eigenvalue is 4.76 and Cronbach’s α = 0.81, explained 16% of vari-
ance. This dimension combines the features that characterize students’ interest about the everyday life topics, the
interest about the structure, features and processes of the surrounding environment /the material world. The items
included in this dimension show how important it is to connect the topic of learning to the practical application.
Second dimension. Interest in mathematics
Items loading on the dimension, which eigenvalue is 3.29 and Cronbach’s α = 0.78, explained 11% of vari-
ance. This dimension shows that students like to compose and solve mathematical tasks in order to solve some
real problem in nature or everyday life. They are interested in complex chemistry and physics tasks. They are not
afraid of diculties.
Third dimension. Inquiry interest
Items loading on the dimension, which eigenvalue is 3.09 and Cronbach’s α = 0.76, explained 10% of variance.
Students have the interest to solve problems, to analyse and explain the processes in nature and everyday
life, to nd out their causes. At the same time, this factor includes also students’ research skills that students have
acquired and are able to apply.
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Fourth dimension. Enthusiasm
Items loading on the dimension, which eigenvalue is 3.01 and Cronbach’s α = 0.66, explained 10% of vari-
ance. The feature of interest that describes perseverance, the willingness to engage in science also outside the
school, the willingness to delve into the process under the exploration and to complete the task. It characterises
the depth of the interest.
Comparing the mean values of answers (M) it is seen that students have relatively the highest interest about
the contexts (dimension 1) and about the research activity (dimension 3) (Table 2). The mean values of several
items in both dimensions are close to the rather agree. The interest about mathematical tasks is much lower (di-
mension 2). The lowest mean values of answers correspond to the dimension 4, which describes enthusiasm,
perseverance, willingness to explore some object or phenomenon outside the school and continue doing until
the work is completed.
According to the previously developed scale of the levels of cognitive interest in science and mathematics
(Cedere, Jurgena, Helmane, Tiltiņa-Kapele, & Praulīte, 2015) the interest dimensions 1 - 3 correspond to the average
level but the dimension 4 corresponds to a low level.
Comparison of the Cognitive Interest of Latvian and Lithuanian Students
In order to nd out whether there were dierences between the interests of Latvian and Lithuanian students,
items in each dimension were summed and the t test was performed to compare both independent sets (Table 3).
To evaluate the eect size of the dimension, Cohen’s d was used.
The obtained results show that dimension 2 and dimension 4 have statistically signicant interest dierences,
eect size (d = 0.32-0.46) for both dimensions can be assessed as medium eect (Becker, 2000), which serves as an
evidence for the dierences in the cognitive interest of students of both countries. Lithuanian students are more
interested in mathematics and they compose and solve complex tasks willingly; Latvian students, however, are
more enthusiastic and they cooperate more with the teacher. Similar statistically signicant interest dierences
can be seen between girls from both countries and boys in both countries, therefore these dierences are not
gender-specic (Table 3).
Table 3. Latvian and Lithuanian students’ interest in science and mathematics.
No Dimension Respondents Country M SE SD t df p d
1Interest in the
context
Total LV 26.84 0.38 7.55 -1.56 738 .12 .11
LT 27.69 0.39 7.24
Girls LV 27.36 0.46 7.25 -2.20 431 .03 .21
LT 28.89 0.54 7.04
Boys LV 26.01 0.65 7.95 -0.26 305 .80 .01
LT 26.23 0.58 7.22
2Interest in
mathematics
Total LV 16.86 0.28 5.40 -4.37 677 < .001 .34
LT 18.65 0.29 5.20
Girls LV 16.32 0.36 5.29 -3.10 385 .002 .32
LT 17.99 0.40 5.24
Boys LV 17.67 0.45 5.47 -2.82 290 .005 .33
LT 19.41 0.42 5.07
3 Inquiry interest
Total LV 13.84 0.16 3.15 -1.97 689 .06 .15
LT 14.31 0.17 3.00
Girls LV 13.52 0.21 3.12 -2.21 431 .03 .19
LT 14.07 0.21 2.73
Boys LV 14.30 0.25 3.13 -0.76 295 .45 .09
LT 14.59 0.27 3.29
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No Dimension Respondents Country M SE SD t df p d
4 Enthusiasm
Total LV 13.47 0.19 3.84 5.92 765 < .001 .43
LT 11.86 0.19 3.64
Girls LV 13.47 0.24 3.81 4.73 433 < .001 .46
LT 11.74 0.27 3.71
Boys LV 13.47 0.31 3.90 3.60 330 < .001 .40
LT 11.99 0.27 3.56
The distribution of respondents’ answers gives a more complete idea about the dierences between the stu-
dents’ interests in these countries, therefore the Chi Square test was performed for the selected items. Items with
the highest mean factor loading were chosen as examples from dimensions 2 and 4 (Table 4).
Table 4. Dierences between the students’ interests.
Item Country
Distribution of respondents’ answers, %
χ2df p
No Rather
no
Rather
yes Yes
The use of mathematics in solving practi-
cal problems (B13)
LV 40.7 24.5 17.4 17.4 12.05 3 .007
LT 30.4 25.4 21.3 23.0
Suggestions made in lessons (A2) LV 40.2 36.6 14.3 8.9 28.36 3 < .001
LT 57.1 26.6 8.5 7.8
There is a signicant dierence between the students’ interest in the two countries. The sharpest dierence is
between the negative answers given by the students. Approximately 40% of Latvia’s students and approx. 30% of
Lithuanian students do not like mathematics at all. In percentage, Lithuanian students have given more armative
answers. There are also signicant dierences regarding the enthusiasm and active participation in lessons. In this
case, the number of negative answers is similar in both countries but in Latvia there are relatively more students
who have answered by rather yes and yes.
Discussion
A student is motivated to learn if the learning content is connected with the student’s interests, his/her ex-
perience and if he/she sees that learning prepares him/her for the real life. The present research proves that the
interest of the 15-year-old students in science and mathematics on the whole is mediocre although the level of
respondents’ interest is rather dierent. The relatively low interest about science that students of this age group
have in Latvia and Lithuania has been observed also before (Cedere, Jurgena, Helmane, Tiltiņa-Kapele, & Praulīte,
2015; Lamanauskas, Gedrovics, & Raipulis, 2004).
Evaluating the obtained data on how students assess their interest about learning biology, chemistry, phys-
ics and mathematics allows concluding that these school subjects, except biology, do not provoke interest (M =
2.32 – 2.77). Students of both countries like learning biology the most (Table 1).
The factor analysis helped to group the quantities characterizing students’ interest and single out four fea-
tures or dimensions of the interest: 1) interest in the context, 2) interest in mathematics, 3) inquiry interest and 4)
enthusiasm. The rst and third dimensions correspond to the main focusses in the strategy of teaching/learning the
sciences; the mathematical aspect appears as a separate dimension (2nd dimension) which comprises also the solu-
tion of complicated tasks in chemistry and physics; the fourth dimension, in its turn, combines students’ willingness
to nd out more, to do more and to explore things with enthusiasm. The evaluation of students’ interests according
to the dimensions provides valuable information needed for the adjustment of the teaching/learning process.
Interest in the context as a vitally important dimension of interest in science has been applied before (Elster,
2007; Haeussler & Homann, 2000). The respondents’ contextual interest is relatively high in our research (Table
2), besides, there are no signicant dierences among both countries ( Table 3). Thus, it is possible to consider that
students are able to see the connection of the teaching/learning content with the real life; furthermore, a poten-
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tial cognitive activity is expected. However, having a closer look at the 4th dimension it is clear that this cognitive
interest refers only to the compulsory school classes.
The second signicant feature of the science interest – inquiry interest relates to an analogous dimension of
the interest that has been used in exploring the interest in physics (Haeussler & Homann, 2000) although the range
of interest included in it is a bit dierent. This dimension of the interest, too, excels with a relatively high mean
value. This serves as an evidence that students have the willingness to research dierent natural phenomena and
they want to engage in the exploration of things that are important in the practical life. If students like exploring,
then students are aware of and they are able to apply this type of cognition characteristic to sciences. The inquiry
interest is equally high in both countries.
Students’ interest in mathematics in the context of the performed survey describes their ability to use math-
ematics in solving dierent practical problems, including also calculation tasks in chemistry and physics. This
dimension of the interest at the same time characterizes also the formation of connected knowledge and the
integration of the school subjects, which is topical in the science acquisition process (Osborne, 2014). The math-
ematical dimension has not gained great respondents’ responsiveness. Respondents assess their interest about
the use of mathematics in solving practical problems rather negatively, M = 2.23 (Table 2). More than a third of
respondents have a negative attitude (the answer no) to the solution of real problems if they have to make math-
ematical equations (Table 4). This allows concluding that many 15-year- old students do not yet fully understand
what sciences are and how they function because sciences cannot do without mathematics. Lithuanian students’
interest in mathematics, though, is signicantly higher than that of the Latvian students (Table 3).
The fourth dimension of the interest is enthusiasm, which in the respondents’ assessment takes the lowest
place, indicates the lack of enthusiasm and self-initiative. The mean values of answers show that students are
unwilling to devote their free time to science or mathematics, M =1.84; they are not interested in the exploration
of nature if that is not a compulsory school requirement, M =1.87 (Table 2). Approximately 80% of students have
a poorly expressed self-initiative (answers no and rather no) (Table 4). The enthusiasm dimension also includes the
willingness to participate in dierent interest groups and projects that are advisable measures for the formation
of the individual science interest (Uitto, Juuti, Lavonen, & Meisalo, 2006). A low indicator of enthusiasm is charac-
teristic of the respondents in both countries although the mean value of the enthusiasm dimension in Latvia is
statistically signicantly higher than in Lithuania (Table 3). Enthusiasm is also used in other researches to describe
the cognitive interest (Purēns, 2015).
Students’ rather high interest in the practical issues and their readiness to engage in their solution can be
considered a certain achievement of the education system in Latvia and Lithuania because students have a positive
attitude to science and the majority of them have a true understanding of the role of science and mathematics in
the real life. However, the present research does not allow stating that students’ interest is stable. The negative at-
titude expressed by any respondents about constructing mathematical equations if the solution of a real problem
demands this (Table 4), is indicative of their unwillingness to make an eort. Such a connection has been stated
before (Cedere, Jurgena, Helmane, Tiltiņa-Kapele, & Praulīte, 2015): the interest is higher if the task is formulated
simply, it is lower if the formulation of the task requires probing into it. Evasion from overcoming the diculties
as well as the lack of perseverance is a characteristic feature of the modern youth that has also been observed in
other subjects (Purēns, 2015).
The comparison of the data from Table 1 and Table 2 (factors 1 and 3) reveals another signicant connec-
tion – students have interest about science phenomena in the real life, they are interested in acting and exploring
themselves, but they quite do not like learning biology, chemistry and physics at school. Thus, students’ willingness
to explore is greater than the teacher’s ability/possibilities to satisfy this willingness. It is possible that one of the
reasons is the incongruity between the teaching/learning content and the student.
The student has changed. The 21st century student who is born and lives in the digitalized world is purposeful,
but he lacks the patience, the ability to delve in the issue and to keep the attention for a longer period of time that
is characteristic of the 20th century student. The breadth and accessibility of the information space has increased
the range of cognition and at the same time has changed the way of perception and thinking. Today’s generation
is oriented towards fast living in today, towards immediate experience. The world is perceived fragmentarily (the so
called “clip” thinking), the attention has a short concentration span (Davidova, Sokolova, & Zariņa, 2014). The lack of
understanding the connections leads to the situation that today’s students do not ask questions about the causes
and consequences; they learn that things should be simply accepted without trying to understand their essence
(Rowlands, Nicholas, Williams, Huntington, Fieldhouse, Gunter, Withey, Jamali, Dobrowolski, & Tenopir, 2008). The
INTEREST OF LATVIAN AND LITHUANIAN STUDENTS IN SCIENCE AND MATHEMATICS
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40
Journal of Baltic Science Education, Vol. 17, No. 1, 2018
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ISSN 2538–7138 /Online/
transformed thinking of the youth is connected with the specics of learning. It would be useful to remember the
theory of J. Dewey that emphasizes – one should never forget that human development is promoted only by what
he himself has created and developed. A student really gains the necessary experience only when he is engaged
in things that he is able to understand and improve. In order to learn something, to widen one’s own intellectual
outlook students should be able to put the new experience in the context, to be able to add the new impressions
to the existing ones (Dewey, 2011).
Transformations are needed in the teaching/learning process so that it corresponds to the modern needs
(Hodson, 2014). For the today’s students to have a greater interest in learning the science and mathematics, it is
necessary to change the approach of teaching, to use the digital technologies more, to apply the corresponding
strategies and to strengthen the mutual cooperation with students (Fullan & Langworthy, 2014). The teaching
strategies in science must be focused on understanding the connections and the student’s personal experience.
The formation of each student’s personal interest should be promoted, teaching every student to base his/her sci-
ence experience not on mutually unrelated, fragmentary knowledge but on analytical, value-judgment thinking.
Conclusions
The gained ndings reect the attitude of today’s youth to science and mathematics. Students who partici-
pated in the research on the whole have a mediocre interest about the science subjects and mathematics; besides,
there are slight dierences between the interests of the Latvian and Lithuanian students.
Students’ cognitive interest in science and mathematics is described in the frame of the present research using
four dimensions – interest in the context, interest in the mathematics, inquir y interest ad enthusiasm. Students have
a relatively high interest about science in the context with the real life and processes in the surrounding environ-
ment. Students’ inquiry interest is equally high, and it is expressed as making the experiments, analysis, evaluation,
nding out the causes, the solution of real life problems. The interest in mathematics that includes also the solution
of complicated tasks in chemistry and physics, is relatively low. Approximately a half of the respondents dislike
mathematics and they are unwilling to do anything that requires eort. The majority of students lack enthusiasm
and perseverance in learning, they have no desire to engage in science or mathematics outside the school.
The most important aspect of the teacher’s competence is to nd a way how to ensure that students learned
with interest and were able to see the usefulness of science and mathematics in their future life. The teaching/
learning process is productive if the student accepts learning as personally meaningful and needed for satisfying
one’s cognitive interest, for widening one’s knowledge, that is useful in interaction with others. As the four found
manifesting dimensions of the cognitive interest explain only a half of the total variance, it is possible to conclude
that there is a number of other factors that inuence the students’ interest of learning. The obtained results encourage
exploring the distribution of students’ answers more closely, thus nding out the reasons for the radically dierent
opinions. This would help teachers nd a more suitable approach for the concreate teaching/learning situation.
Acknowledgements
The authors are greatly thankful to Dr. paed. Ineta Helmane for the participation in the research. The authors
also thank all the teachers who were responsive and participated in the organization of the survey.
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Appendix
Factor analysis excluded items
(load values from 0.40 to 0.60)
Items M SD
Rotated factor load values
Factor 1 Factor 2 Factor 3 Factor 4
B4 3.13 1.00 .56
B7 2.20 1.12 .55
B1 2.40 1.24 .51
B6 2.66 1.15 .51
B12 2.56 1.13 .50
B15 3.03 1.06 .40
A12 2.54 1.09 .48
B5 2.75 1.13 .42
A13 2.83 .87 .59
A9 2.31 1.04 .54
A10 2.79 .98 .47
Received: October 16, 2017 Accepted: January 15, 2018
Dagnija Cēdere
(Corresponding author)
Dr.chem., Associate Professor, University of Latvia, Jelgavas street
1, LV-1004, Riga, Latvia.
E-mail: dagnija.cedere@lu.lv
Inese Jurgena Dr.paed., Professor, University of Latvia, Imantas linija 7/1, LV-
1083, Riga, Latvia.
E-mail: inese.jurgena@lu.lv
Vilija Targamadze Dr.phil., Prof. habil., Vilnius University, Universiteto street 9/1, LT-
01513, Vilnius, Lithuania.
E-mail: vilija.targamadze@gmail.com
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