A CRoss-nAtIonAL stUDy oF CzeCh AnD tURkIsh

Transkript

A Cross-National Study
of Czech and Turkish
University Students’
Attitudes towards
ICT Used in Science
Subjects
Milan Kubiatko,
Muhammet Usak,
Kursad Yilmaz,
Mehmet Fatih Tasar
Introduction
The history of electronic educational materials does not go
far back but for several decades now there is an increasing attempt
to create more such resources (Arnold, Padilla & Tunhikorn, 2009).
The educational value of the information and communications
technologies (ICT) was confirmed by a variety of experiments
(Fančovičová & Prokop, 2008). When used appropriately, ICT can
support students’ collaboration and knowledge building. Further,
in the context of science education, it offers possibilities for interaction with the nature and tools for real-time data logging (Juuti,
Lavonen, Aksela & Meisalo, 2009). The interactive nature of ICT
materials is believed to provide the opportunity for students to
analyze the process, assimilate and work independently (Kaino,
2008). Many teachers have realized the potential of ICT to increase
quality of teaching and learning in recent years. The ICT has pervaded all sectors of education prompting the need to prepare
teachers to take advantage of these tools. Although ICT allows
students to work more productively than in the past, the teacher’s
role in classroom, where the ICT are presented, is more demanding
than ever (Keengwe, Onchwari & Wachira 2008).
General Description of ICT Attitudes
Pre-service primary science teachers’ (PPSTs) attitudes toward
ICT are very critical and important in science education since teachers play a key role within the learning environment. If the PPSTs
have positive attitudes toward ICT then they can use ICT in their
classrooms effectively. ICT offers a challenge to the teaching and
Abstract. This paper focuses on differences of attitudes related to information
and communication technologies among
Czech and Turkish university students.
Student attitudes were evaluated summatively and with respect to gender,
year, country, and type of residential area
(town/village). Student attitudes were
measured by a modified version of the Information and Communication Technologies Attitudes Questionnaire (Kubiatko &
Haláková, 2009). The sample consisted of a
total of 770 unversity students (316 Czech
and 454 Turkish). The data analysis included factor analysis, MANCOVA, ANOVA,
and t-test. The factor analysis yielded five
dimensions: 1) Influence of ICT on teaching
process, 2) Influence of ICT on human body
and environment, 3) Using of ICT in teaching, 4) School and ICT, 5) ICT as didactic
equipment. As a result, students from the
Czech Republic, male students, sophomores, and students living in town showed
more positive attitudes in comparison to
other respective groups.
Key words: attitudes, information and
communication technologies, questionnaire, science teaching, university students.
Milan Kubiatko
Masaryk University, Czech Republic
Muhammet Usak
Zirve University, Turkey
Kursad Yilmaz
Dumlupinar University, Turkey
Mehmet Fatih Tasar
Gazi University, Turkey
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Journal of Baltic Science Education, Vol. 9, No. 2, 2010
A Cross-National Study of Czech and Turkish University Students’
Attitudes towards ICT Used in Science Subjects
(P. 119-134)
ISSN 1648–3898
learning of science and to the models of PPSTs might encounter. The teacher generally has a key role
to effective application of the use of ICT in science education and the teachers have big potential to
transmit attitudes and beliefs to students by using ICT.
Zhao, Tan and Mishra (2001) showed evidence to suggest that the attitudes of teachers toward ICT
are directly related to computer use in the classroom. Success of student learning in using ICT depends
largely on teachers’ attitudes towards ICT (Teo, 2006). If teachers show positive attitudes towards ICT
then they can easily provide useful insights about acceptance and usage of ICT in teaching for students.
Many researchers emphasized the dimensions of attitudes towards ICT. Some examples are perceived
usefulness of ICT and confidence about using ICT (Rovai & Childress, 2002; Cure & Ozdener, 2007), training (Tsitouridou & Vryzas, 2003), gender (Sadık, 2006), anxiety and liking/disliking (Yıldırım, 2000).
There is indication that many teachers believe that the level of computer experience has a positive impact on attitudes towards ICT (Kumar & Kumar, 2003). Yuen and Ma (2002) found that affective
attitudes, general usefulness, behavioral control, and pedagogical employment are important factors
in determining the use of ICT. Furthermore, in a study with 184 pre-service teachers, it was reported
that a significant relationship existed between attitudes towards ICT and its use in educational system
(Jackson, Ervin, Gardner & Schmitt, 2001). Sorgo, Verckovnik & Kocijancic (2010) observed high correlation between frequency of using a computer application for school work, perceived importance, and
teachers’ proficiency in use of application among Slovenian Biology teachers. The teacher’s attained
competence and confidence level in using ICT are important factors in students’ learning. Thus, an understanding of how ICT supports and enhances learning tasks is vital issue to be determined (Baggott
La Velle, McFarlane & Brawn 2003).
Integration of ICT into science and technology curricula and classroom practices can be achieved
by science teachers showing positive attitudes toward ICT. These positive attitudes toward ICT can be
more easily gained in pre-service teacher education by courses such as Computer, Computer Supported
Learning, Information and Communication Technologies, Teaching Methods, and Design of Instructional
Materials for Teaching, etc. It is important to provide prospective teachers and in-service teachers with
courses and trainings, because lack of time is one of the main reasons stated by teachers for not employing ICT in teaching. Planning, practicing, and trying to integrate ICT into lessons are all time consuming.
But with proper training teachers can do it with more confidence and in less time. On the other hand,
a lack of ICT pedagogical training at teacher training colleges constitutes a barrier for using ICT in the
classrooms; and, although individual ICT skills might be high for personal use, the transfer of these skills
to the classroom environment may become problematic (Cuckle & Clarke, 2002). Integration of ICT into
the teaching process can also be impeded by other barriers like lack of equipment, lack of access to the
right types of technology in appropriate location, cost of technology, and poor administrative support.
All these aspects can create negative attitudes towards ICT.
ICT has a transformative potential role for science teaching. The use of ICT changes the direction
of scientific skills and thinking. ICT in science education helps to develop analytical skills (McFarlane &
Friedler, 1998; Rogers & Wild, 1996). The interactive use of ICT provides to support and develop students’
scientific reasoning and analytic skills. Some studies show, the positive influence of using ICT during
teaching process on better understanding of targeted topics and concepts. For example, Stern, Barnea
& Shauli (2008) describe students who were provided with molecular software simulation demonstrated
a significantly better understanding of the particulate model of matter than students who were not
provided with this simulation. In another study it was found that utilizing computer-assisted materials
have a potential to increase students’ achievement, foster conceptual change, and improve students’
attitudes towards biology, if it is designed according to students’ learning needs (Kara & Yesilyurt, 2008).
Also, Yang & Heh (2007) used an Internet Virtual Physics Laboratory (IVPL) and found out a positive and
significant effect on students’ physics achievement.
Pre-service teachers can arrange their environment and adjust their instructional strategies by using
ICT in science education (Zhang & Espinosa, 1997). For example Fisher, (2000) stated that PPSTs’ positive
attitudes toward ICT will provide teachers to face the challenges in the information age. The successful
use of ICT can stimulate change in pedagogical practice. Evidence from research carried out by Underwood (1988) suggests that teachers move to a more managerial and facilitating role when using ICT,
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and away from being the information provider on centre stage. ICT promises to provide a more effective
method of developing both substantive and syntactic scientific understanding. Digitally presented data
sets offer an alternative way to achieve learning objectives, as can simulations that generate data sets
or model specific processes or phenomena (Baggott La Velle, Watson, Nichol, 2001).
Influence of Different Variables toward ICT Attitudes
Many explorations are focused on finding gender differences in attitudes and using ICTs. Dorup
(2004) found that males had more access to computers at home, and held more favorable attitudes
toward the use of computers in their medical studies as compared to females. A small proportion of
students reported that they would prefer not to use computers in their studies. Males were also significantly more inclined to replace traditional teaching activities with ICT resources. A more recent study
of Palaigeorgiou et al. (2005) also confirmed that both men and women had similar engagement with
computers and held concerns for the future effects of continuous computer use, but women were more
anxious about hardware usage, and judged less positively the consequences of computers in personal
and social life. Research on gender differences in ICT has shown that in most countries girls and women
are often behind in ICT usage and ICT knowledge and skills. In most countries, the participation of
females in ICT professional careers and pathways is low and unfortunately continues to depreciate. Finally, a lot of research studies have shown that females and males differ in their preferences for specific
computer activities.
In the literature there is a controversy among studies on attitudes towards ICT with respect to
students’ age. Although it is reported that younger pupils have more positive attitudes toward computers than the older (Comber, Colley, Hargreaves & Dorn 1997; Laguna & Babcock 1997), among others, a
more recent study reported the opposite (Bozionelos 2001). On the other hand Spernjak & Sorgo (2009)
did not find differences based on age among lower secondary school students aged between 10 and
14 when performed three laboratory exercises (Activity of yeast, Gas exchange and breathing, heart
rate) as classic, computer-supported and virtual laboratory exercises. Pupils chose computer-supported
laboratory as the most popular method of laboratory work. Classically performed laboratory work followed, while computer simulation was the least popular approach toward laboratory exercises.On the
other hand, there is no cross-national study. In this study a comparison of attitudes between prospective
teachers in the Czech Republic and Turkey is reported.
Research toward ICT Attitudes in Turkey and Czech Republic
A lot of research studies have been conducted about ICT in Turkey. These studies were mainly in
the following categories: in-service teachers’ level of employing ICT (Usluel, Mumcu & Demiraslan, 2007;
Cure & Ozdener, 2008); use of ICT in teacher education (Altun, 2007; Goktas, Yildirim & Yildirim, 2008);
pre-service teachers’ level of using ICT (Altun, Alev & Yigit, 2009;) and pre-service teachers’ attitudes
toward ICT (Ozgen & Obay, 2008).
Between 2000 and 2007 most of the studies related to ICT in Turkey were about computer assisted teaching, alternative learning and teaching approaches, web-based learning, problems in using
educational Technologies, internet-based learning and distance education (Bingimlas, 2009; Çepni, Taş
& Köse, 2006; Bahar, Aydın & Karakırık, 2009; Cepni, 2009; Camnalbur & Erdogan, 2008; Erdogan, 2009;
Simsek, 2008). Altun, Alev & Yigit (2009) found that pre-service science teachers had also positive views
about ICT.
On the other hand, the research activities on the issue in the Czech Republic have not been as
intense as in Turkey. Czech researchers in this field of study published in local journals, available only
for the native, in this case Czech, readers.
Purpose of this Study
The purpose of this study was to investigate university students’ attitudes towards ICT. For that
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purpose samples were chosen from two different countries, namely Turkey and the Czech Republic. There
are major differences between these two countries: a big difference in populations (Turkey’s population
is 6 times greater than the population of Czech Republic); geographic location and area, means of access to technologies, income per capita, and culture. Educational initiatives for implementation of ICT in
education are also somewhat different. Therefore, it may be hypothesized that all these differences can
lead to different student attitudes towards ICT. This article explores the following research question:
1. Are there any differences in attitudes toward ICT with respect on gender, residence and
grade of students from both countries?
2. Is there any difference in attitudes toward ICT between students from Czech Republic and
Turkey with the respect on gender, residence and grade of students?
Methodology of Research
Sample
The study was conducted at the end of spring semester 2009. A total of 454 Turkish and 316 Czech
students attending two different universities participated in the study. The participating students were
majoring in teaching middle school / high school science (biology, geography, chemistry). The ages of
the participants were between 17 and 30 ( x = 20.44; SD = 1.45). The sample size of the Czech Republic
sample was created by 100 males and 216 females, 62 students from village, 90 students from town and
164 students from city, 128 freshmen, 105 sophomores and 83 third year students. The sample size of
Turkey was created by 296 males and 158 females, 60 students from village, 125 students from town and
269 students from city. There were 72 freshmen, 234 sophomores and the rest (147) created third year
students. In Turkey 276 students were owners of computers and 178 were not owners of computers. All
Czech respondents were in the time of research owners of computers.
Construction of the ICT Attitudes Questionnaire (ICTAQ)
Students’ attitudes toward ICT in science subjects were measured by 5 scale Likert type items. We
used a modified version of the ICT Attitude Questionnaire (Kubiatko & Haláková, 2009). This questionnaire was originally created to probe student attitudes towards ICT specifically in biology. Due to the
nature of the current study the word “biology” was replaced with “science subject” or “science subjects”
in the entire questionnaire.
The questionnaire items are related to common ICT activities and ICT usage. There were items
related to influence of ICT on the process of teaching (“ICT make lessons more interesting”); items
focusing on the influence of ICT on health and human body (“using ICT related equipment may cause
spine injuries”). Other group of items focused on using ICT in teaching (“I reach more information from
internet than from textbooks”). A couple of items were related to ICT as didactic equipment (“I think that
I achieve worse evaluation by the written examining with the ICT assistance”). We were interested in, if
students are satisfied with ICT and their employment in lessons (“I am not satisfied with employment
of ICT in science lessons at our school”).
The original form of the questionnaire was developed in English and later translated into Slovak and
Turkish by the authors with expert assistance in translation. The order of items was presented randomly;
items were not grouped together with other items having a similar character. The questionnaire consists
of 33 items that were rated by the participants from 1 (strongly disagree) to 5 (strongly agree). There were
items worded both positively (e.g., “I do my homework quicker, when I use ICT”) and negatively (e.g., “I
have got a fear, when I used a computer”) (Oppenheim, 1999). Negative items were reversed in scoring.
The total score of individual participants provides a composite index of attitudes towards ICT usage in
science subjects. A low score reflects a relatively negative attitude and a high score reflects a relatively
positive attitude towards ICT. The validity of the questionnaire was established through review by two
experts in the field of using ICT/computers in education. Reviewers were asked whether the items were
relevant to the aim of the study. Revisions were based on their comments and suggestions.
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The first part of the questionnaire contained demographic questions: gender, age, year of study,
owning of computer and type of residential area (i.e., village, town, or city). The main difference between
town and city is that cities are designated by a population greater than 100.000. All students from Czech
Republic are owners of computer, but in the Turkey is not that. For that reason we analyzed attitudes to
ICT with respect to owning of computer overall, we did not compare Czech Republic and Turkey. Age
was as covariate.
Procedure
Questionnaires were administered in two different universities. One university was from Turkey
and one from the Czech Republic. Students in this study participated by knowing that participation was
anonymous and that it would not affect their course grades. They were informed that the aim was just
a research attempt to examine student attitudes towards using ICT in science subjects. The questionnaire was randomly administrated. No time limit was given during completion of the questionnaire,
but the longest time of filling was about 15 minutes. The researchers or the instructors administered
the questionnaires.
Statistical Procedure
The data were analyzed statistically by conducting a factor analysis with Varimax rotation and five
factors with Eigen values greater than 1.00 were derived. The five factors (dimensions) were labeled as:
1. Influence of ICT on teaching process (7 items), 2. Influence of ICT on human body and environment
(4 items), 3. Using of ICT during teaching process (7 items), 4 School and ICT (3 items), 5. ICT as didactic
equipment (6 items). These five factors explained 39.23 % of total variance. Most of this variance was
explained by the factor/dimension 1 and 2 (14.80 % and 9.05 %).
Items (6) with factor score more than 0.30 loaded in more than one factor and factors with factor
score less than 0.30 were excluded from the next analyses (Anastasi, 1990). Next reliability of the questionnaire was measured. The Cronbach’s alpha for the whole instrument was 0.72, which indicates high
reliability of the questionnaire (Nunnaly, 1978). The values of alpha coefficient for the scale ranged from
0.58 to 0.89 indicate an acceptable reliability (Nunnaly, 1978).
Multivariate analysis of covariance (MANCOVA) with age as covariate, dimensions as dependent
variables and demographic variables (gender, residence, grade and owning of computers) as independent
variables were also conducted. For obtaining statistically significant differences in results between variables and between countries t-test and ANOVA were performed. Results showed statistically significant
differences on the levels: p<0.05; p<0.01 and p<0.001.
Results of Research
A factor analysis with Varimax rotation was performedon the data. After a careful examination
of the table of factors, items with factor score greater than 0.30 loaded in more than one factor were
excluded from further analysis. Questions with factor scores less than 0.30 were also eliminated (Anastasi, 1990).
It was also examined whether statistically significant differences existed in the results between
variables of gender, type of residential area lived, year of study, and owning a computer. In performing
a MANCOVA age was taken as a covariate. First, we analyzed the whole data coming from both countries and afterwards data for each country were analyzed separately. The influence of age on the results
was not showed (Table 2). In the all variables was found out statistically significant difference in results
(table 2). Males achieved an average score of 3.56 (SD=0.36), whereas the average score for females was
3.55 (SD=0.39). On the basis of the results males showed more positive attitudes towards computers in
comparison to females. Sophomore students achieved the highest average score ( x = 3.57; SD = 0.36)
and freshmen students achieved the lowest average score ( x = 3.53; SD = 0.32) and junior students
achieved an average score 3.56 (SD=0.37). Students living in towns had a more positive attitude than
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students living in villages or cities (their average score was 3.57 and SD = 0.39). Students living in cities
achieved an average score 3.55 (SD=0.35). And students living in villages have got the lowest average
score ( x = 3.47; SD = 0.40). Students, who are computer owners achieved higher score ( x = 3.55; SD
= 0.38) in comparison to students who did not own computers ( x = 3.54; SD = 0.35).
Table 1.
Values of factor score in ICTAQ.
Influence
of ICT on
teaching
process
Influence of
ICT on human
body and
environment
Using of
ICT during
teaching
process
School and
ICT
ICT as a
didactic
equipment
1. ICT are important in teaching science
subjects.
0.72
-0.02
0.07
0.03
0.03
2. ICT make lessons more interesting.
0.68
0.06
0.10
0.03
0.12
3. Using ICT cause a higher interest about
science subjects.
0.81
0.03
-0.12
-0.15
0.02
4. I understand scientific concepts better,
when ICT are used.
0.76
-0.04
0.05
0.03
0.14
5. I have got ideas, when the ICT are used.
0.76
0.04
-0.07
-0.10
-0.11
13. We obtain new information by the using
the internet, because some information in
the textbooks have become outdated.
0.41
-0.21
0.25
-0.13
0.02
20. I do my homework quicker, when I use
ICT.
0.47
0.04
0.21
-0.14
0.16
7. ICT cause exhaustingly to me.
0.29
0.38
0.08
-0.16
0.28
23. Using computers is harmful for eyes.
-0.12
0.64
0.11
0.03
0.16
25. Using ICT is harmful for spines.
-0.04
0.72
0.13
0.03
0.07
28. ICT does not save energy.
0.24
0.52
-0.05
0.06
0.05
14. I had an opportunity to cooperate with
other schools by using ICT.
0.29
-0.23
0.48
-0.02
-0.17
21. I use ICT for paper presentation.
0.13
-0.19
0.64
0.02
-0.15
22. The ownership of PC is useless, because PC’s make learning impossible.
0.02
0.10
0.61
-0.05
0.18
24. It is impossible to meaningfully use
ICT, because a majority of information is in
languages other than Czech/Turkish.
-0.16
0.18
0.57
0.24
0.28
29. Computer is not a suitable tool for
teaching, because it needs a lot of space.
0.05
0.15
0.52
-0.06
0.24
32. I have got a fear, when I used a
computer.
-0.07
0.01
0.53
-0.06
0.08
33. I obtain more information from internet
than textbooks.
0.12
-0.00
0.35
-0.35
0.15
Influence of ICT on teaching process
Influence of ICT on human body and
environment
Using of ICT during teaching process
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School and ICT
17. I am not satisfied with using ICT in
science lessons at our school.
0.03
0.08
0.24
0.43
0.20
18. The ICT equipments in our school are
very poor.
0.04
-0.13
0.084
0.71
0.17
27. Teachers should receive more training
on using of ICT for teaching.
-0.29
0.01
-0.21
0.43
0.20
ICT as a didactic equipment
8. I am not able to concentrate on teaching,
when the computer is turned on.
-0.06
0.18
0.23
-0.04
0.45
9. The work with educational disc make
better a cognitive process.
0.19
-0.13
0.12
-0.25
0.47
10. I think that using the internet is not
important for teaching.
-0.03
-0.30
0.19
0.26
0.37
12. I think that I achieve worse evaluation by the written examining with the ICT
assistance.
0.08
0.25
0.22
0.05
0.34
15. I am not able to concentrate on
teaching, when a camera is used during
teaching.
-0.01
0.12
-0.05
0.08
0.62
16. My communication with the teacher
becomes worse, when ICT are used during
teaching.
0.14
0.25
0.14
0.06
0.48
Eigenvalues
4.88
2.99
2.16
1.63
1.29
Table 2. Results of multivariate analysis of covariance (MANCOVA).
Wilk’s λ
F
p
Age
0.98
1.91
0.90
Gender
0.95
7.40
< 0.001
Grade
0.94
4.19
< 0.001
Residence
0.96
2.89
< 0.01
Owning of computer
0.93
11.46
< 0.001
The data were further analyzed to see if there existed a statistically significant difference between
factors/dimension. Age was used as covariate by all variables. Gender was found to create a statistically
significant difference in the dimension “Influence of ICT on teaching process” (F = 14.57; p < 0.001), in
this dimension was influence of age statistically significant (F = 5.73; p < 0.05). In this dimension males
achieved higher scores than females. A statistically significant difference was found in the forth dimension labeled “School an ICT” (F = 12.94; p < 0.001), where females achieved a higher mean score than
males. When compared founded results among grade, age influenced results in dimension 4 (F = 4.87;
p < 0.05). Statistically significant differences were found in dimensions 1 and 4, where the sophomores
achieved the highest average score and in dimension 2, and the freshmen achieved the highest average
score. On the variable “type of residential area” results were influenced by age only in the first dimension
(F = 4.76; p < 0.05). A statistically significant difference between results was found in dimensions 3, 4,
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and 5. In dimension 3 and 4 the highest average scores achieved by students from village and in the
last dimension (ICT as didactic equipment) it was the students from town. It was seen that age did not
influence results on the variable “owning a computer”. A statistically significant difference in results was
found, just like in previous variable, in all dimensions except dimension 2. Students, who do not own
a computer, achieved higher scores in the first dimension and in other dimensions computer owners
achieved higher average scores.
Table 3. Results of multivariate analysis of covariance (MANCOVA) in dimensions. Numbers are
the F values.
Age
Gender
Age
Grade
Age
Residence
Age
Computer
Dimension 1
5.73*
14.57***
0.40
11.52***
4.76*
0.56
3.16
24.48***
Dimension 2
0.26
3.53
0.17
3.65*
0.32
1.76
0.29
1.94
Dimension 3
0.15
3.79
1.52
1.11
0.14
4.97**
0.59
12.84***
Dimension 4
0.62
12.94***
4.87*
3.10*
0.61
3.62*
1.46
6.88**
Dimension 5
0.56
1.20
0.15
1.69
0.40
3.28*
0.25
5.47*
* p<0.05; ** p<0.01; *** p<0.001
A Comparison of Turkey and Czech Republic
When the results from Turkey and the Czech republic were compared, it was found that there were
statistically significant differences in results in two variables, sophomores from the Czech Republic
achieved a higher mean score than their counterparts in Turkey (t = 2.93; p < 0.01), On the other hand
Turkish students from town achieved a higher mean score than their Czech counterparts (t = 2.07; p
< 0.05). When other variables were considered it was seen that there was not a statistically significant
difference between groups (see Figure 1).
Figure 1. 126
Differences in attitudes to ICT in variables between Turkey and Czech Republic.
NS = non-significant; * p<0.05; ** p<0.01.
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In the next phase of the analysis a comparison between the 5 dimensions was performed. There
were statistically significant differences with respect to all dimensions except dimension 2 (Negative
influence of ICT on teaching process, see Figure 2). In the first dimension it is seen that Turkish students
attained a higher mean score (t = 12.41; p < 0.001) than Czech students. In other dimensions Czech
students showed more positive attitudes: Using ICT during teaching (t = 7.28, p < 0.001), School and
ICT (t = 9.45; p < 0.001), ICT as didactic equipment (t = 8.49; p < 0.001).
Figure 2. Differences between attitudes in five dimensions between Turkey and Czech Republic.
NS = non-significat, *** p<0.001.
In the next evaluation we compare individual variables (gender, grade and residence) and we have
tried to find out statistically significant differences between Turkey and Czech Republic.
Figure 3. Differences in attitudes toward ICT in five dimensions among females from Turkey and
Czech Republic.
** p<0.01; *** p<0.001.
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Gender
When we have compared female we found statistically significant differences in results between
all dimensions. In first two it was in the account of Turkish students (dimension 1: t=8.13; p<0.001;
dimension 2: t=2.86; p<0.01). I other three dimensions girls from Czech Republic achieved statistically
significant higher score in comparison with girls from Turkey. All differences are p<0.001 (dimension 3:
t=6.02; dimension 4: t=6.56; dimension 5: t=6.00) (Figure 3).
In the comparison of male’s results was situation a little bit different. In the first dimension we
found out statistically significant difference in results (t=8.48; p<0.001), boys from Turkey achieved
higher score in comparison with boys from Czech Republic. In other dimension boys from Czech Republic achieved statistically significant higher score In comparison with boys from Turkey (dimension 2:
t=5.09; p<0.001; dimension 3: t=3.78; p<0.001; dimension 4: t=5.69; p<0.001 and dimension 5: t=6.20;
p<0.001) (Figure 4).
Gender’s results from Czech Republic were influenced by age (Wilk’s lambda=0.93; F=4.73;
p<0.001) and results from Turkey were not influenced by age as covariate (Wilk’s lambda=0.98; F=2.02;
p=0.052).
Figure 4. Differences in attitudes toward ICT in five dimensions among males from Turkey and Czech
Republic.
*** p<0.001.
Grade
In all three grades was not statistically significant difference in dimension “Influence of ICT on human body and environment (dimension 2)” (Table 4). In other dimensions and grades was found out
statistically significant difference in results. First grade students from Czech Republic achieved higher
score in dimensions 3, 4 and 5 and students from Turkey in others. Second grade students from Czech
Republic achieved higher score in comparison with students from Turkey except first dimension (Influence of ICT on teaching process). And third grade students from Czech Republic achieved higher score
in all dimensions in comparison with students of same grade from Turkey. Grade’s results from Czech
Republic was influenced by age (Wilk’s lambda=0.95; F=3.32; p<0.01) a results from Turkey was not
influenced by age (Wilk’s lambda=0.95; F=1.44; p=0.21).
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Table 4. A Cross-National Study of Czech and Turkish University Students’
(P. 119-134)
Comparison of results between Turkey and Czech Republic with respect on grade.
1st
grade
TR
1st
grade
CZ
t
2nd
grade
TR
2nd
grade
CZ
t
3rd
grade
TR
3rd
grade
CZ
t
Dimension 1
4.23
3.56
7.02***
4.27
3.87
6.35***
4.20
3.59
6.26***
Dimension 2
3.14
3.05
0.84
2.90
2.95
0.54
3.05
3.07
0.15
Dimension 3
3.79
4.16
4.52***
3.89
4.27
5.57***
3.88
4.10
2.71**
Dimension 4
2.25
2.65
3.59***
2.28
3.02
8.98***
2.24
2.62
3.97***
3.24
3.68
5.40***
3.28
3.66
5.40***
3.32
3.58
3.36***
Dimension 5
** p<0.01; *** p<0.001
Residence
There was not found out statistically significant difference in results in dimension 2 among all
three types of residence (city, town and village). Czech students from city achieved higher score in
dimensions 3, 4 and 5. In other there were students from Turkey. Czech students from town and village
achieved higher scores in all dimensions except dimension 1. Residence’s results from Czech Republic
was influenced by age (Wilk’s lambda=0.94; F=3.76; p<0.01) a results from Turkey was not influenced
by age (Wilk’s lambda=0.98; F=1.81; p=0.11).
Table 5. Comparison of results between Turkey and Czech Republic with respect on residence.
City
TR
City
CZ
t
Town TR
Town
CZ
t
Village
TR
Village
CZ
t
Dimension 1
4.25
3.64
9.68***
4.27
3.63
7.84***
4.12
3.80
2.72**
Dimension 2
3.05
3.02
0.36
2.93
3.05
1.22
2.85
2.98
0.90
Dimension 3
3.83
4.14
5.17***
3.96
4.12
2.12*
3.88
4.38
8.03***
Dimension 4
2.26
2.73
6.60***
2.24
2.70
4.56***
2.33
2.94
4.78***
Dimension 5
3.28
3.57
4.98***
3.34
3.74
5.31***
3.22
3.74
4.56***
* p<0.05; ** p<0.01; *** p<0.001
Discussion
In this study the aim was to determine prospective science teachers’ attitudes towards ICT. The data
were collected from two countries, namely the Czech Republic and Turkey. The data were analyzed as
a whole and separately for each country. The selected variables were gender, type of residential area
lived, and year of study. Age was chosen as the covariate.
The factor analyses yielded five factors with Eigen values greater than 1.00. The five factors (dimension) were constructed as follows: 1. Influence of ICT on teaching process (7 items), 2. Influence of ICT
on human body and environment (4 items), 3. Using ICT during teaching (7 items), 4. School and ICT (3
items), 5. ICT as didactic equipment (6 items).
Examining university students’ attitudes towards ICT is an important and necessary for determining
perceptions and the current status. In this way it can be revealed if the students are taking the full advantages of using ICT in education. It can also be determined if ICT are being used properly in teaching.
The finding of this study reveals that the participant university students had positive attitudes towards ICT used in science teaching. Similar findings were also reported before (Simsek, 2008) revealing
that a majority of students accepted the use of ICT for learning and they maintained positive attitudes
toward using ICT. A similar finding, this time specifically about utilizing the internet, was reported by
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Akpinar & Bayramoglu (2008). Kubiatko & Haláková (2009) also asserted that secondary grammar school
students had positive attitudes towards ICT for teaching and learning biology.
When Turkey and the Czech Republic are compared, it is seen that Czech university students have
more positive attitudes towards ICT. This situation can be explained by the fact that all Czech students
in the sample owned personal computers. When each factor (dimension) is considered it is seen that
Turkish students’ scores were higher in the first dimension only and Czech students have had higher
scores in the remaining four dimensions. The reason could be that their instructors have more intensely
and/or skillfully employed ICT in their teaching of science, hence set a good example for their students.
It was revealed previously that Czech teachers in general use ICT for only presentation purposes or to
offer information in word processors (Paraskeva, Bouta & Papagianni, 2008); and using ICT in the form
of educational discs, virtual laboratories, etc. were seen rarely. However, it is known that whenever ICT
are employed, they are used in the greater variety by Turkish teachers.
Research studies about ICT are focused mainly on describing differences between variables.
Gender is the variable used most frequently. The majority of ICT articles are concerned with gender
and attitudes towards ICT. Besides, there are also publications focusing on differences caused by race/
ethnicity towards ICT attitudes and a few others discussing socio-economic or class differences (e.g.,
Heemskerk, Brink, Volman & Dam, 2005).
In this research study it is revealed that males have more positive attitudes towards ICT as compared
to females. This finding supports the common view that “males are technically more competent than
females,” despite all efforts worldwide to train females at least equally competently with males in science
and engineering. The similar assertions were also made elsewhere (e.g., Cooper, 2006). Cooper indicated
that the public in general believes that males are more interested in using computers, and hence they are
more competent in using computers. The negative attitudes of females, in turn, negatively impact their
performance in using computers. Knowing that females have negative attitudes towards computers and
are reluctant to use them only reinforces the stereotypical view that computers are for males and not for
females. Females may have been socialized differently in today’s computer generation to have them feel
more comfortable with using computers and, hence, removing barriers to opportunities for receiving
better training, at least partially. This could be due to the increased use of computers for teaching and
learning at schools that might have worked against the cultivation of gender differences as reported in
previous research (North & Noyes, 2002). Computer attitudes and computer skills are related to gender
in favor males, that is, males have better attitudes towards computers, attain improved computer skills
and experiences as compared to females (Varank, 2007). There are many hypothetical reasons why,
males consistently achieve more positive attitudes towards ICT. It could be that when the computer is
used for purposes other than studying, male students spend more time working with computers than
female students, male students do more word processing, they use e-mail more, and they play games
more often (Imhof, Vollmeyer & Beierlein, 2007).
There is no consensus on gender issues within the ICT related literature. For example, several researchers have found that males are generally using computers less than women or females have more
negative attitudes towards computer and ICT (Akkoyunlu & Orhan, 2003; Miura, 1987; Murpy, Coover &
Owen, 1989; Uzunboylu, 2004; Venkatesh & Davis, 2000). In addition, researchers have determined that
gender has strong effect regarding using computer and ICT in attitudes study (Butler, 2000; Dupange
& Krendel, 1992).
Kubiatko & Haláková (2009) found out similar results in comparison to the current study. Males
have more positive attitudes toward ICT than females. When university students in Turkey and the Czech
Republic are compared, this study revealed that the Czech students attained more positive attitudes
toward ICT. The views of male and female participants from the Czech Republic were more positive as
compared to male and female participants from Turkey. But, a more detailed analysis shows that females
from Turkey had more positive views in two of the five dimensions, namely, Influence of ICT on teaching
and Influence of ICT on human body and environment. Additionally, males from Turkey have had more
positive views in the first dimension only.
In the analysis another variable was students’ year of study. In this study participants from both
countries were in their first, second, and third years. Sophomore students had the highest positive
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views and the freshmen expressed the least favorable views towards ICT. But, it is not known whether
age plays a role in this dimension, since age and year of study does not necessarily match. All that can
be said is that there is statistically significant differences among students in different years of study. In
the literature there are just few empirical studies focusing on age and attitudes towards ICT. In such a
study Comber, Colley, Hargreaves & Dorn (1997) reported that the younger students had more positive
attitudes towards computers than the older ones. In other studies it findings were contradictory: while in
some studies it is reported that there existed a significant correlation between age and attitudes towards
ICT (e.g., Handler, 1993; Massoud, 1991), in other studies the findings showed just the opposite (e.g.,
Blankenship, 1998; Chio, 1992). Sophomore students from the Czech Republic have held more positive
views as compared to students from Turkey. The freshmen from both countries expressed almost similar
views and the juniors from Turkey expressed more positive views. These differences between students
in different years of their studies could be explained by the structure of the subject in each year.
The last variable in this study was the type of residential area lived. The three types were as follows: village, town, and city. There is no other study, to the best of our knowledge that reports on this
variable and its relation to attitudes towards ICT. As a result of this study it is seen that students coming
from towns have attained more positive attitudes as compared to students coming from villages and
cities. Also, students coming from villages have the least favorable views towards ICT. Turkish students
coming from towns had more positive views and attitudes as compared to Czech students coming from
towns. However, when other two types of residential areas are considered it is seen that Czech students
attained more positive views and attitudes. Altough it could be speculated about this finding, it is suggested that it should be investigated in other studies and other countries in depth to understand the
reasons behind it.
Conclusion
Attitudes results toward ICT using in science subject among high school students were based on
statistical evaluation. Students, whose were respondents of our investigation showed an interest about
using ICT in the science subjects, it was obvious from their answers. It is important awake to, that ICT can
enhance students’ learning in science from an early age. An effective use of ICT could have the additional
benefit of improving attitudes and computers skills, which in turn could improve the effectiveness of
ICT, thus creating a positive feedback spiral.
References
Akpinar, Y., & Bayramoglu, Y. (2008). Promoting teachers’ positive attitude toward web use: a study in web site
development. The Turkish Online Journal of Educational Technology, 7, 46-55.
Altun, T. (2007). Information and communications technology (ICT) in initial teacher education: what can Turkey
learn from range of international perspectives? Journal of Turkish Science Education, 4, 45-60.
Altun, T., Alev, N. & Yigit, N. (2009). An investigation of pre-service science teachers’ views about their technical
and pedagogical skills in the use of ICT. 9th International Educational Technology Conference. May 6–8, 2009. Hacettepe
University, Ankara, Turkey. 515-521.
Anastasi, A. (1990). Psychological testing (7th ed.). New York: Macmillan.
Arnold, S. R., Padilla, M. J., & Tunhikorn, B. (2009). The development of pre-service science teachers’ professional
knowledge in utilizing ICT to support professional lives. Eurasia Journal of Mathematics, Science and Technology
Education, 5, 91-101.
Bahar, M., Aydın, F.& Karakırık, E. (2009). A diagnostic study of computer application of structural communication
grid. The Turkish Online Journal of Educational Technology, 8, 5-19.
Baggott la Velle, L., McFarlane, A. & Brawn, R. (2003). Knowledge transformation through ICT in science education: a case study in teacher-driven curriculum development—Case-Study. British Journal of Educational Technology,
34, 183-199.
Baggott La Velle, L., Watson, K. E. & Nichol, J. D. (2001). OtherScope – The virtual microscope – can the real
learning experiences in practical science be simulated? International Journal of Healthcare Technology and Management, 2, 539-556
131
(P. 119-134)
ISSN 1648–3898
Blankenship, S. E. (1998). Factors related to computer use by teachers in classroom instruction. Unpublished
Doctoral Dissertation, Virginia Polytechnic Institute and State University. http://scholar.lib.vt.edu/theses/available/
etd-32398-14166/unrestricted/etd.pdf. [last access: 20/03/2009].
Bingimlas, K. A. (2009). Barriers to the Successful Integration of ICT in Teaching and Learning Environments: A
Review of the Literature. Eurasia Journal of Mathematics, Science & Technology Education, 5, 235-245.
Bozionelos, N. (2001). Computer anxiety: Relationship with computer experience and prevalence. Computers in
Human Behavior, 17, 213-224.
Camnalbur, M. & Erdogan, Y.(2008). A meta analysis on the effectiveness of computer-assisted instruction: Turkey
sample. Kuram Ve Uygulamada Egitim Bilimleri, 8, 497-505.
Cepni, S., Tas, E., & Kose, S. (2006). The effects of computer-assisted material on students’ cognitive levels, misconceptions and attitudes towards science. Computers & Education, 46, 192–205.
Cepni, S. (2009). Effects of computer supported instructional material (CSIM) in removing students misconceptions about concepts: “Light, light source and seeing”. Energy Education Science And Technology: Part B-Social and
Educational Studies, 1, 51-83.
Chio, Y. K. (1992). Attitudes toward and knowledge of microcomputers used for instruction among commercial
high school teachers in Korea. Unpublished EDD dissertation. University of Georgia. AAT 9316322.
Comber, C., Colley, A., Hargreaves, D. J., & Dorn, L. (1997). The effects of age, gender computer experience upon
computer attitudes. Educational Research, 39, 123-133.
Cooper, J. (2006). The digital divide: the special case of gender. Journal of Computer Assisted Learning, 22, 320334.
Cuckle, P. & Clarke, S. (2002). Mentoring student-teachers in schools: views, practices and access to ICT. Journal
of Computer Assisted Learning, 18, 330-340.
Cure, F, Ozdener, N (2008). Teachers’ Information and Communication Technologies (ICT) using achievements
and attitudes towards ICT. Hacettepe Universitesi Egitim Fakultesi Dergisi-Hacettepe University Journal of Education, 34, 41-53.
Dorup, J. (2004). Experience and attitudes towards information technology among first year medical students in
Denmark: Longitudinal questionnaire survey. Journal of Medical Internet Research, 2004, 6, e10.
Dupagne, M., & Krendel, K. A. (1992). Teachers’ attitudes towards computers: a review of literature. Journal of
Research on Computing in Education, 24, 420–429.
Erdogan Y (2009) Paper-based and computer-based concept mappings: The effects on computer achievement,
computer anxiety and computer attitude. British Journal Of Educational Technology, 40, 821-836.
Fančovičová, J., & Prokop, P. (2008). Students’ attitudes toward computer use in Slovakia. Eurasia Journal of Mathematics, Science and Technology Education, 4, 255–262.
Fisher, M. (2000). Computer skills of initial teacher education students. Journal of Information Technology for
Teacher Education, 9, 109-123.
Goktas, Y, Yildirim, Z. & Yildirim, S (2008). The keys for ICT integration in K-12 education: Teachers’ perceptions and
usage. Hacettepe Universitesi Egitim Fakultesi Dergisi-Hacettepe University Journal of Education, 34, 127-139.
Handler, M.G. (1993). Preparing new teachers to use computer technology: perceptions and suggestions for
teacher educators. Computer Education, 20, 147-156.
Heemskerk, I., Brink, A., Volman, M. & Dam, G. (2005). Inclusiveness and ICT in education: a focus on gender,
ethnicity and social class. Journal of Computer Assisted Learning, 21, 1-16.
Imhof, M., Vollmeyer, R., & Beierlein, C. (2007). Computer use and the gender gap: The issue of access, use, motivation, and performance. Computers in Human Behavior, 23, 2823-2837.
Jackson, L. A., Ervin, K. S., Gardner, P. D., & Schmitt, N. (2001). Gender and the Internet: Women communicating
and men searching. Sex Roles, 44, 363-379.
Jimoyiannis, A., & Komis, V. (2007). Examining teachers’ beliefs about ICT in education. Implications of a teacher
preparation programme. Teacher Development, 11, 149-173.
Juuti, K., Lavonen, J., Aksela, M., & Meisalo, V. (2009). Adoption of ICT in science education: a case study of communication channels in a teachers’ professional development project. Eurasia Journal of Mathematics, Science and
Technology Education, 5, 103–118.
Kaino, L. M. (2008). Technology in learning: narrowing the gender gap? Eurasia Journal of Mathematics, Science
and Technology Education, 4, 263–268.
Kara, Y. & Yesilyurt, S. (2008). Comparing the impacts of tutorial and edutainment software programs on students’
achievements, misconceptions and attitudes toward biology. Journal of Science Education and Technology, 17, 32-41
Keengwe, J., Onchwari, G. & Wachira, P. (2008). Computer Technology Integration and Student Learning: Barriers
and Promise. Journal of Science Education and Technology, 17, 560-565.
Korte, W. B. & Hüsing, T. (2007). Benchmarking access and use of ict in European schools 2006: results from head
teacher and a classroom teacher surveys in 27 European countries. eLearning Papers, 2 (1). http://www.elearningeuropa.
info/files/media/media11563.pdf. [last access: 20/03/2009].
Kubiatko, M. & Haláková, Z. (2009). Slovak high school students’ attitudes to ICT using in biology lesson. Computers in Human Behavior, 25, 743-748.
132
ISSN 1648–3898
(P. 119-134)
Kumar, P., & Kumar, A. (2003). Effect of a web-based project on pre-service and inservice teachers’ attitude toward
computers and their technology skills. Journal of Computing in Teacher Education, 19, 87-91.
Laguna, K., & Babcock, R. L. (1997). Computer anxiety in young and older adults: Implications for human–computer
interactions in older populations. Computers in Human Behavior, 13, 317-326.
Massoud, S. L. (1991). Computer attitudes and computer knowledge of adult students. Journal of Educational
Computing Research, 7, 269-291.
McFarlane, A., & Friedler, Y. (1998). Where you want IT when you want IT - the role of portable computers in science education. In B. Fraser & K. Tobin, International handbook of science education. (pp. 399-420). Amsterdam: Kluwer
Pres.
Miura, T. (1987). The relationship of computer self-efficacy expectations to computer interest and course enrolment in college. Sex Roles, 16, 303-311. Murpy, C., Coover, D., & Owen, S. (1989). Development and validation of the computer self efficacy scale. Education and Psychological Measurement, 49, 893-899.
Myers, J. M., & Halpin, R. (2002). Teachers’ attitudes and use of multimedia technology in the classroom: Constructivist-based professional development training for school districts. Journal of Computing in Teacher Education,
18, 133-140.
North, A. S., & Noyes, J. M. (2002). Gender influences on children computer attitudes and cognitions. Computers
in Human Behavior, 18, 135-150
Nunnaly, J. (1978). Psychometric theory. McGraw-Hill: New York.
Oppenheim, A. N. (1999). Questionnaire design, interviewing and attitude measurement. London: Continuum
International Publishing Group, New Edition.
Ozgen, K. & Obay, M. (2008). The attitudes of secondary mathematics preservice teachers towards educational
technology. 8th International Educational Technology Conference. May 6th - 9th 2008.Anadolu University, Eskişehir, Turkey.
pp. 583-588.
Palaigeorgiou, G. E., Siozos, P. D., Konstantakis, N. I., & Tsoukalas, I. A. A. (2005). Computer attitude scale for computer
science freshmen and its educational implications. Journal of Computer Assisted Learning, 21, 330-342.
Paraskeva, F., Bouta, H., & Papagianni, A. (2008). Individual characteristcs and computer self-efficacy in secondary
education teachers to integrate technology in educational practice. Computers & Education, 50, 1084-1091.
Rogers, L. T., & Wild, P. (1996). Datalogging: effects on practical science. Journal of Computer Assisted Learning,
12, 130-145.
Rovai, A. P., & Childress, M. D. (2002). Explaining and predicting resistance to computer anxiety reduction among
teacher education students. Journal of Research on Technology in Education, 35, 226-235.
Sadik, A. (2006). Factors influencing teachers’ attitudes toward personal use and school use of computers: New
evidence from a developing nation. Evaluation Review, 30, 86-113.
Schumacher, P., & Morahan-Martin, J. (2001). Gender, Internet and computer attitudes and experiences. Computers in Human Behavior, 17, 95-110.
Simsek, S. C. S. (2008). Students’ attitudes towards integration of ICTs in a reading course: A case in Turkey. Computers and Education, 51, 200-211.
Spernjak, A., & Sorgo, A. (2009). Comparison of Attitudinal Differences with Three Different Styles of Biological
Laboratory Exercises among Elementary School Students. Didactica Slovenica-Pedagoska Obzorja, (3-4), 68-86.
Sorgo, A., Verčkovnik, T., & Kocijančič, S. (2010). Information and communication technologies (ICT) in biology
teaching in Slovenian secondary schools. Eurasia Journal of Mathematics, Science and Technology Education, 6, 37-46.
Stern, L., Barnea, N. & Shauli, S. (2008). The effect of a computerized simulation on middle school students’ understanding of the kinetic molecular theory. Journal of Science Education and Technology, 17, 305-315.
Teo, T. (2006). Attitudes toward computers: A study of post-secondary students in Singapore. Interactive Learning
Environments, 14, 17-24.
Teo, T. (2008). Pre-service teachers’ attitude toward computer use: A Singapore survey. Australasian Journal of
Educational Technology, 24, 413-424.
Tondeur, J., Van Braak, J. & Valcke, M. (2007). Curricula and the use of ICT in education: Two worlds apart? British
Journal of Technology Education, 38, 962-976.
Tsitouridou, M., & Vryzas, K. (2003). Early childhood teachers’ attitudes towards computer and information technology: The case of Greece. Information Technology in Childhood Education Annual, 1, 187-207.
Underwood, J. D. M. (1988). An investigation of teacher intents and classroom outcomes in the use of informationhandling packages. Computers & Education, 12, 91-100.
Usluel, Y.K., Mumcu, F.K. &Demiraslan, Y. (2007) ICT in the learning-teaching process: Teachers’ views on the
integration and obstacles Hacettepe Universitesi Egitim Fakultesi Dergisi-Hacettepe University Journal of Education, 32,
164-178 Varank, I. (2007). Effectiveness of quantitative skills, qualitative skills, and gender in determining computer skills
and attitudes: a causal analysis. Clearing House: A Journal of Educational Strategies, 81, 71-80.
Venkatesh, V., & Davis, D. F. (2000). A theoretical extension of the technology acceptance model: four longitudinal
field studies. Management Science, 46, 186–204.
133
(P. 119-134)
ISSN 1648–3898
Yang, K. Y. & Heh, J. S. (2007). The impact of internet virtual physics laboratory onstruction on the achievement in physics, science process skills and computer attitudes of 10th-grade student. Journal of Science Education
and Technology, 16, 451-461.
Yildirim, S. (2000). Effects of an educational computing course on pre-service and inservice teachers: A discussion and analysis of attitudes and use. Journal of Research on Computing in Education, 32, 479-495.
Yuen, H. K. & Ma, W. K. (2002). Gender differences in teacher computer acceptance. Journal of Technology and
Teacher Education, 10, 365-382.
Zhang, Y., & Espinoza, S. (1997). Affiliations of computer self-efficacy and attitudes with need for learning
computer skills. Journal of Educational Computing Research, 17, 371-383.
Zhao, Y., Tan, H. S., & Mishra, P. (2001). Teaching and learning: Whose computer is it? Journal of Adolescent &
Adult Literacy, 44, 348-354.
Received 08 December 2009; accepted 30 April 2010
Milan Kubiatko
Muhammet Usak
134
Assistant Professor at Institute for Research in School Education at
Faculty of Education, Masaryk University in Brno, Žerotínovo nám.
617/9, 601 77, Brno, Czech Republic.
E-mail: [email protected]
Website: http://www.kubiatko.eu
Assistant Professor at the Department of Elementary Education,
Faculty of Education, Zirve University, Gaziantep, Turkey.
E-mail: [email protected] & [email protected]
Website: http://www.zirve.edu.tr
Kursat Yilmaz
Assistant Professor at the Department of Educational Science, Faculty
of Education, Dumlupinar University, Kutahya, Turkey.
Website: http://www.dpu.edu.tr/dpuweb/
Mehmet Fatih
Tasar
Associate Professor at the Department of Science Education, Faculty
of Education, Gazi University, Ankara, Turkey.
Website: http://www.gazi.edu.tr/
Journal of Technology and Information Education
3/2010, Volume 2, Issue 3
ISSN 1803-537X
RESEARCH
http://jtie.upol.cz
ARTICLES
CZECH UNIVERSITY STUDENTS’ ATTITUDES TOWARDS ICT USED IN
SCIENCE EDUCATION
Milan KUBIATKO
Abstract: This paper focuses on differences of attitudes related to information and communication
technologies among Czech university students. Students’ attitudes were evaluated summatively and
with respect to gender, grade, and residence. The sample consisted of a total of 316 university
students. The data analysis included factor analysis, ANCOVA, ANOVA, and t-test. The factor analysis
yielded five dimensions: 1) Influence of ICT on teaching process, 2) Influence of ICT on human body
and environment, 3) Using of ICT in teaching, 4) School and ICT, 5) ICT as didactic equipment. As a
result, male students, sophomores, and students living in town showed more positive attitudes in
comparison to other respective groups.
Key words: attitudes, information and communication technologies, questionnaire, science teaching,
university students.
POSTOJE ČESKÝCH VYSOKOŠKOLSKÝCH STUDENTŮ K POUŽÍVANÍ ICT
V PŘÍRODOVĚDNÝCH PŘEDMĚTECH
Resumé: Příspěvek je zaměřen na postoje studentů českých vysokých škol k informačním
a komunikačním technologiím. Postoje byly vyhodnocovány jako celek a také s ohledem na pohlaví,
ročník studia a bydliště respondentů. Výzkumný vzorek tvořilo 316 studentů vysokých škol. Faktorová
analýza, ANCOVA, ANOVA a t-test byly použity jako statistické metody. Použitím faktorové analýzy
bylo zjištěno 5 dimenzí: 1) Vliv ICT na vyučovací proces, 2) Vliv ICT na lidský organismus
a prostředí, 3) Použití ICT ve vyučování, 4) Škola a ICT, 4) ICT jako didaktická pomůcka. Studenti
(muži), studenti druhého ročníku a studenti žijící ve městě prokázali pozitivnější postoj k ICT
v porovnání s ostatními skupinami.
Klíčová slova: postoje, informační a komunikační technologie, dotazník, přírodovědné předměty,
vysokoškolští studenti.
prepare teachers to take advantage of these tools.
Although ICT allows students to work more
productively than in the past, the teacher’s role in
classroom, where the ICT are presented, is more
demanding than ever (Keengwe, Onchwari &
Wachira 2008).
1 Introduction
The history of electronic educational materials
does not go far back but for several decades now
there is an increasing attempt to create more such
resources (Arnold, Padilla & Tunhikorn, 2009).
The educational value of the information and
communications technologies (ICT) was
confirmed by a variety of experiments
(Fančovičová & Prokop, 2008). When used
appropriately, ICT can support students’
collaboration and knowledge building. Further, in
the context of science education, it offers
possibilities for interaction with the nature and
tools for real-time data logging (Juuti, Lavonen,
Aksela & Meisalo, 2009). The interactive nature
of ICT materials is believed to provide the
opportunity for students to analyze the process,
assimilate and work independently (Kaino,
2008). Many teachers have realized the potential
of ICT to increase quality of teaching and
learning in recent years. The ICT has pervaded
all sectors of education prompting the need to
2 Theoretical background
Zhao, Tan and Mishra (2001) showed
evidence to suggest that the attitudes of teachers
toward ICT are directly related to computer use
in the classroom. Success of student learning in
using ICT depends largely on teachers’ attitudes
towards ICT (Teo, 2006). If teachers show
positive attitudes towards ICT then they can
easily provide useful insights about acceptance
and usage of ICT in teaching for students. Many
researchers emphasized the dimensions of
attitudes towards ICT. Some examples are
perceived usefulness of ICT and confidence
about using ICT, training (Tsitouridou & Vryzas,
2003), gender, anxiety and liking/disliking
20
(Yıldırım, 2000). Integration of ICT into science
and technology curricula and classroom practices
can be achieved by science teachers showing
positive attitudes toward ICT. These positive
attitudes toward ICT can be more easily gained in
pre-service teacher education by courses such as
Computer, Computer Supported Learning,
Information and Communication Technologies,
Teaching Methods, and Design of Instructional
Materials for Teaching, etc. It is important to
provide prospective teachers and in-service
teachers with courses and trainings, because lack
of time is one of the main reasons stated by
teachers for not employing ICT in teaching.
Planning, practicing, and trying to integrate ICT
into lessons are all time consuming. But with
proper training teachers can do it with more
confidence and in less time. On the other hand, a
lack of ICT pedagogical training at teacher
training colleges constitutes a barrier for using
ICT in the classrooms; and, although individual
ICT skills might be high for personal use, the
transfer of these skills to the classroom
environment may become problematic (Cuckle &
Clarke, 2002). Integration of ICT into the
teaching process can also be impeded by other
barriers like lack of equipment, lack of access to
the right types of technology in appropriate
location, cost of technology, and poor
administrative support. All these aspects can
create negative attitudes towards ICT. Many
explorations are focused on finding gender
differences in attitudes and using ICTs. Dorup
(2004) found that males had more access to
computers at home, and held more favorable
attitudes toward the use of computers in their
medical studies as compared to females. A small
proportion of students reported that they would
prefer not to use computers in their studies.
Males were also significantly more inclined to
replace traditional teaching activities with ICT
resources. A more recent study of Palaigeorgiou
et al. (2005) also confirmed that both men and
women had similar engagement with computers
and held concerns for the future effects of
continuous computer use, but women were more
anxious about hardware usage, and judged less
positively the consequences of computers in
personal and social life. Research on gender
differences in ICT has shown that in most
countries girls and women are often behind in
ICT usage and ICT knowledge and skills. In most
countries, the participation of females in ICT
professional careers and pathways is low and
unfortunately continues to depreciate. Finally, a
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lot of research studies have shown that females
and males differ in their preferences for specific
computer activities. In the literature there is a
controversy among studies on attitudes towards
ICT with respect to students’ age. Although it is
reported that younger pupils have more positive
attitudes toward computers than the older
(Laguna & Babcock 1997), among others, a more
recent study reported the opposite (Bozionelos
2001). On the other hand Spernjak & Sorgo
(2009) did not find differences based on age
among lower secondary school students aged
between 10 and 14 when performed three
laboratory exercises (Activity of yeast, Gas
exchange and breathing, heart rate) as classic,
computer-supported and virtual laboratory
exercises. Pupils chose computer-supported
laboratory as the most popular method of
laboratory
work.
Classically
performed
laboratory work followed, while computer
simulation was the least popular approach toward
laboratory exercises.
The main aim of this study was to investigate
university students’ attitudes towards ICT and
this article explores the following research
question: Is there any difference in attitudes
toward ICT between students with the respect on
gender, residence and grade of students?
3 Methodology
A total 316 Czech students attending one
university participated in the study. The
participating students were majoring in teaching
middle school / high school science (biology,
geography, chemistry). The ages of the
participants were between 17 and 30 (x = 20.44;
SD = 1.45). The sample size was created by 100
males and 216 females, 62 students from village,
90 students from town and 164 students from
city, 128 freshmen, 105 sophomores and 83 third
year students. All Czech respondents were in the
time of research owners of computers. Students’
attitudes toward ICT in science subjects were
measured by 5 scale Likert type items. We used a
modified version of the ICT Attitude
Questionnaire (Kubiatko & Haláková, 2009).
This questionnaire was originally created to
probe student attitudes towards ICT specifically
in biology. Due to the nature of the current study
the word “biology” was replaced with “science
subject” or “science subjects” in the entire
questionnaire. The questionnaire items are related
to common ICT activities and ICT usage. There
were items related to influence of ICT on the
process of teaching (“ICT make lessons more
21
interesting”); items focusing on the influence of
ICT on health and human body (“using ICT
related equipment may cause spine injuries”).
Other group of items focused on using ICT in
teaching (“I reach more information from internet
than from textbooks”). A couple of items were
related to ICT as didactic equipment (“I think
that I achieve worse evaluation by the written
examining with the ICT assistance”). We were
interested in, if students are satisfied with ICT
and their employment in lessons (“I am not
satisfied with employment of ICT in science
lessons at our school”). The questionnaire
consists of 33 items that were rated by the
participants from 1 (strongly disagree) to 5
(strongly agree). There were items worded both
positively (e.g., “I do my homework quicker,
when I use ICT”) and negatively (e.g., “I have
got a fear, when I used a computer”)
(Oppenheim, 1999). Negative items were
reversed in scoring. The total score of individual
participants provides a composite index of
attitudes towards ICT usage in science subjects.
A low score reflects a relatively negative attitude
and a high score reflects a relatively positive
attitude towards ICT. The validity of the
questionnaire was established through review by
two experts in the field of using ICT/computers
in education. Reviewers were asked whether the
items were relevant to the aim of the study.
Revisions were based on their comments and
suggestions. The first part of the questionnaire
contained demographic questions: gender, age,
year of study, owning of computer and type of
residential area (i.e., village, town, or city). The
main difference between town and city is that
cities are designated by a population greater than
100.000. All students from Czech Republic are
owners of computer, for that reason we did not
analyze attitudes to ICT with respect to owning
of computer. Age was as covariate.
Questionnaires were administered in one
university. Students in this study participated by
knowing that participation was anonymous and
that it would not affect their course grades. They
were informed that the aim was just a research
attempt to examine student attitudes towards
using ICT in science subjects. The questionnaire
was randomly administrated. No time limit was
given during completion of the questionnaire, but
the longest time of filling was about 15 minutes.
The data were analyzed statistically by
conducting a factor analysis with Varimax
rotation and five factors with Eigen values
greater than 1.00 were derived. The five factors
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(dimensions) were labeled as: 1. Influence of ICT
on teaching process (7 items), 2. Influence of ICT
on human body and environment (4 items), 3.
Using of ICT during teaching process (7 items), 4
School and ICT (3 items), 5. ICT as didactic
equipment (6 items). These five factors explained
39.23 % of total variance. Most of this variance
was explained by the factor/dimension 1 and 2
(18.66 % and 7.00 %). Items (6) with factor score
more than 0.30 loaded in more than one factor
and factors with factor score less than 0.30 were
excluded from the next analyses (Anastasi,
1990). Next reliability of the questionnaire was
measured. The Cronbach’s alpha for the whole
instrument was 0.72, which indicates high
reliability of the questionnaire (Nunnaly, 1978).
The values of alpha coefficient for the scale
ranged from 0.58 to 0.89 indicate an acceptable
reliability (Nunnaly, 1978).
Analysis of covariance (ANCOVA) with age
as covariate, mean score as dependent variable
and demographic variables (gender, residence,
grade and owning of computers) as independent
variables were also conducted. For obtaining
statistically significant differences in results
between variables t-test and ANOVA were
performed.
Results
showed
statistically
significant differences on the levels: p<0.05;
p<0.01 and p<0.001.
4. Results
A factor analysis with Varimax rotation was
performedon the data. After a careful
examination of the table of factors, items with
factor score greater than 0.30 loaded in more than
one factor were excluded from further analysis.
Questions with factor scores less than 0.30 were
also eliminated (Anastasi, 1990). The total score
was 3.57 (SD = 0.42), what indicates a relatively
positive attitudes toward using ICT in science
subjects. It was also examined whether
statistically significant differences existed in the
results between variables of gender, type of
residential area lived and year of study. In
performing an ANCOVA age was taken as a
covariate. The influence of age on the results was
not showed. In the all variables was also not
found out statistically significant difference in
results. Males achieved an average score of 3.63
(SD = 0.05), whereas the average score for
females was 3.55 (SD = 0.04). Students living in
towns had a more positive attitude than students
living in villages or cities (their average score
was 3.67 and SD = 0.08). Students living in cities
achieved an average score 3.61 (SD = 0.04). And
22
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students living in villages have got the lowest of ICT on human body and environment” (figure
average score (x = 3.50; SD = 0.05). Sophomore 1), next statistically significant differences by the
students achieved the highest average score (x = influence of grade in the dimensions “Influence
3.69; SD = 0.05) and freshmen students achieved of ICT on teaching process” and “School and
the lowest average score (x = 3.51; SD = 0.04) ICT” (figure 2) and the statistically significant
and third years students achieved an average difference was found out by the influence of
residens in the dimension “Using of ICT during
score 3.57 (SD = 0.08).
By the analyzing of dimension, we found out teaching process” (figure 3).
statistically significant difference by the
influence of gender in the dimension “Influence
Figure 1 Differences between attitudes in five dimensions with respect on gender (NS = nonsignificant; *** p < 0.001)
5,00
NS
NS
NS
***
4,50
male
NS
4,00
mean score + SD
female
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
Influence of ICT on
teaching process
Influence of ICT on
human body and
environment
Using of ICT during
teaching process
School and ICT
ICT as a didactic
equipment
Figure 2 Differences between attitudes in five dimensions with respect on grade (NS = non-significant;
** p < 0.01; *** p < 0.001)
5,00
4,50
NS
NS
**
NS
4,00
mean score + SD
1st grade
2nd grade
***
3rd grade
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
Influence of ICT on
teaching process
Influence of ICT on
human body and
environment
Using of ICT during
teaching process
School and ICT
ICT as a didactic
equipment
mean score + SD
Figure 3 Differences between attitudes in five dimensions with respect on residence (NS = nonsignificant; ** p < 0.01)
5,00
4,50
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
**
NS
NS
NS
NS
city
town
village
Influence of
ICT on
teaching
process
Influence of
Using of ICT
ICT on human
during
body and
teaching
environment
process
School and
ICT
23
ICT as a
didactic
equipment
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worked against the cultivation of gender
differences Computer attitudes and computer
skills are related to gender in favor males, that is,
males have better attitudes towards computers,
attain improved computer skills and experiences
as compared to females (Varank, 2007). In the
analysis another variable was students’ year of
study. Sophomore students had the highest
positive views and the freshmen expressed the
least favorable views towards ICT. But, it is not
known whether age plays a role in this
dimension, since age and year of study does not
necessarily match. All that can be said is that
there is statistically significant differences among
students in different years of study. In the
literature there are just few empirical studies
focusing on age and attitudes towards ICT. In
other studies it findings were contradictory: while
in some studies it is reported that there existed a
significant correlation between age and attitudes
towards ICT (e.g., Handler, 1993). The last
variable in this study was the type of residential
area lived. The three types were as follows:
village, town, and city. There is no other study, to
the best of our knowledge that reports on this
variable and its relation to attitudes towards ICT.
As a result of this study it is seen that students
coming from towns have attained more positive
attitudes as compared to students coming from
villages and cities. Also, students coming from
villages have the least favorable views towards
ICT.
5 Discussion
In this study the aim was to determine
prospective science teachers’ attitudes towards
ICT. The selected variables were gender,
residence and year of study. Age was chosen as
the covariate. The factor analyses yielded five
factors with Eigen values greater than 1.00. The
five factors (dimension) were constructed as
follows: 1. Influence of ICT on teaching process
(7 items), 2. Influence of ICT on human body and
environment (4 items), 3. Using ICT during
teaching (7 items), 4. School and ICT (3 items),
5. ICT as didactic equipment (6 items).
Examining university students’ attitudes towards
ICT is an important and necessary for
determining perceptions and the current status. In
this way it can be revealed if the students are
taking the full advantages of using ICT in
education. It can also be determined if ICT are
being used properly in teaching.The finding of
this study reveals that the participant university
students had positive attitudes towards ICT used
in science teaching. Similar findings were also
reported before (Simsek, 2008) revealing that a
majority of students accepted the use of ICT for
learning and they maintained positive attitudes
toward using ICT. Kubiatko & Haláková (2009)
also asserted that secondary grammar school
students had positive attitudes towards ICT for
teaching and learning biology.In this research
study it is revealed that males have more positive
attitudes towards ICT as compared to females.
This finding supports the common view that
“males are technically more competent than
females,” despite all efforts worldwide to train
females at least equally competently with males
in science and engineering. The similar assertions
were also made elsewhere (e.g., Cooper, 2006).
Cooper indicated that the public in general
believes that males are more interested in using
computers, and hence they are more competent in
using computers. The negative attitudes of
females, in turn, negatively impact their
performance in using computers. Knowing that
females have negative attitudes towards
computers and are reluctant to use them only
reinforces the stereotypical view that computers
are for males and not for females. Females may
have been socialized differently in today’s
computer generation to have them feel more
comfortable with using computers and, hence,
removing barriers to opportunities for receiving
better training, at least partially. This could be
due to the increased use of computers for
teaching and learning at schools that might have
6 Conclusion
Attitudes results toward ICT using in science
subject among high school students were based
on statistical evaluation. Students, whose were
respondents of our investigation showed an
interest about using ICT in the science subjects, it
was obvious from their answers. It is important
awake to, that ICT can enhance students’
learning in science from an early age. An
effective use of ICT could have the additional
benefit of improving attitudes and computers
skills, which in turn could improve the
effectiveness of ICT, thus creating a positive
feedback spiral.
7 References
[1] ARNOLD, S. R., PADILLA, M. J.,
TUNHIKORN, B.: The development of preservice science teachers’ professional knowledge
in utilizing ICT to support professional lives.
Eurasia Journal of Mathematics, Science and
Technology Education, 2009, vol. 5, no.2, pp. 91101.
24
[2] BOZIONELOS, N.: Computer anxiety:
Relationship with computer experience and
prevalence. Computers in Human Behavior, 2001,
vol. 17, no. 2, pp. 213-224.
[3] COOPER, J.: The digital divide: the special
case of gender. Journal of Computer Assisted
Learning, 2006, vol. 22, no. 5, pp. 320-334.
[4] CUCKLE, P., CLARKE, S.: Mentoring
student-teachers in schools: views, practices and
access to ICT. Journal of Computer Assisted
Learning, 2002, vol. 18, no. 3, pp. 330-340.
[5] DORUP, J.: Experience and attitudes towards
information technology among first year medical
students in Denmark: Longitudinal questionnaire
survey. Journal of Medical Internet Research,
2004, vol. 6, no. 1, e10.
[6] FANČOVIČOVÁ, J., PROKOP, P.: Students’
attitudes toward computer use in Slovakia.
Eurasia Journal of Mathematics, Science and
Technology Education,2008, vol. 4, no. 3, pp.
255-262.
[7] HANDLER, M.G.: Preparing new teachers to
use computer technology: perceptions and
suggestions for teacher educators. Computer
Education, 1993, vol. 20, no.2, pp. 147-156.
[8] JUUTI, K., LAVONEN, J., AKSELA, M.,
MEISALO, V.: Adoption of ICT in science
education: a case study of communication
channels in a teachers’ professional development
project. Eurasia Journal of Mathematics, Science
and Technology Education, 2009, vol. 5, no. 2, pp.
103-118.
[9] KAINO, L. M.: Technology in learning:
narrowing the gender gap? Eurasia Journal of
Mathematics,
Science
and
Technology
Education, 2008, vol. 4, no. 3, pp. 263-268.
[10] KEENGWE, J., ONCHWARI, G.,
WACHIRA,
P.:
Computer
Technology
Integration and Student Learning: Barriers and
Promise. Journal of Science Education and
Technology, 2008, vol. 7, no. 6, pp. 560-565.
[11] KUBIATKO, M., HALÁKOVÁ, Z.: Slovak
high school students’ attitudes to ICT using in
biology lesson. Computers in Human Behavior,
2009, vol. 25, no. 3, pp. 743-748.
[12] LAGUNA, K., BABCOCK, R. L.:
Computer anxiety in young and older adults:
Implications for human–computer interactions in
older populations. Computers in Human
Behavior, 1997, vol. 13, no. 3, pp. 317-326.
[13] PALAIGEORGIOU, G. E., SIOZOS, P. D.,
KONSTANTAKIS, N. I., TSOUKALAS, I. A.
25
ISSN 1803-537X
http://jtie.upol.cz
A.: Computer attitude scale for computer science
freshmen and its educational implications.
Journal of Computer Assisted Learning, 2005,
vol. 21, no. 5, pp. 330-342.
[14] SIMSEK, S. C. S.: Students’ attitudes
towards integration of ICTs in a reading course:
A case in Turkey. Computers and Education,
2008, vol. 51, no.1, pp. 200-211.
[15] SPERNJAK, A., SORGO, A.: Comparison
of Attitudinal Differences with Three Different
Styles of Biological Laboratory Exercises among
Elementary
School
Students.
Didactica
Slovenica-Pedagoska Obzorja, 2009, vol. 24, no.
3-4, pp. 68-86.
[16] TEO, T.: Attitudes toward computers: A
study of post-secondary students in Singapore.
Interactive Learning Environments,2006, vol. 14,
no. 1, pp. 17-24.
[17] TSITOURIDOU, M., VRYZAS, K.: Early
childhood teachers' attitudes towards computer
and information technology: The case of Greece.
Information Technology in Childhood Education
Annual, 2003, vol. 1, pp. 187-207.
[18] VARANK, I.: Effectiveness of quantitative
skills, qualitative skills, and gender in
determining computer skills and attitudes: a
causal analysis. Clearing House: A Journal of
Educational Strategies, 2007, vol. 81, no. 2, pp.
71-80.
[19] YILDIRIM, S.: Effects of an educational
computing course on pre-service and inservice
teachers: A discussion and analysis of attitudes
and use. Journal of Research on Computing in
Education, 2000, vol. 32, no. 4, pp. 479-495.
[20] ZHAO, Y., TAN, H. S., MISHRA, P.:
Teaching and learning: Whose computer is it?
Journal of Adolescent & Adult Literacy, 2004,
vol. 44, no. 4, pp. 348-354.
Contact information
PaedDr. Milan Kubiatko, PhD.
Pedagogická fakulta MU
Institut výzkumu školního vzdělávání
Poříčí 31, 603 00 Brno, ČR
Tel: +420 549 49 4885
www: http://www.ped.muni.cz/weduresearch/
joomla
ERIDOB CONFERENCE 2010
Academic Committee
Dr. Anat Yarden (Secretary)
Weizmann Institute of Science, Rehovot, Israel
Dr. Dirk Jan Boerwinkel
University of Utrecht, The Netherlands
Dr. Graça S. Carvalho
University of Minho, Braga, Portugal
Dr. Margareta Ekborg
Umeå University, Sweden
Dr. Dirk Krüger
Freie Universität Berlin, Germany
Dr. Michael Reiss
University of London, UK
Dr. Patricia Schneeberger
IUFM d’Aquitaine, Bordeaux, France
Dr. Vasso Zogza
University of Patras, Greece
Local Organising Committee
Dr. Graça S. Carvalho
Dr. Zélia Anastácio
Dr. Cledir Santos
Dr. Rosa Branca Tracana
Dr. Sara Fernandes
António Carlos Jesus
Cláudia Ferreira
Emília Gonçalves
Carla Silva
Leonel Pereira
Sponsors
Instituto de Educação
CIFPEC
portoenorteTEM
UNIVERSIDADE DO MINHO - BRAGA - PORTUGAL
i
ERIDOB CONFERENCE 2010
75
Elementary school pupils knowledge and attitudes toward butterflies and
mosquitoes
Kubiatko, M.1 & Vaculová, I 2. 1
Educational Research Centre, Faculty of Education, Masaryk University, Porici 31,
60300 Brno
2
Department of Physics, Faculty of Education, Masaryk University, Porici 7, 603 00
Brno
CZECH REPUBLIC
The purpose of this study is to compare attitudes and knowledge about the mosquito and the
butterfly among elementary school pupils from Slovakia and the Czech Republic. In this study a
mosquito is considered to be an unpopular / unsympathetic animal and a butterfly is considered
to be a popular or sympathetic animal among people. The number of similar studies is
constantly increasing.
Mosquitoes and butterflies are common animals occurring in the area of human habitations.
Mosquitoes are generally considered to be harmful animals, which suck blood and leave itchy
red bumps. Most people do not see any importance in this kind of animal, as they always kill
them without thinking about the
mosquitos’ significance. On the other hand, there is another group of animals called butterflies.
People are evaluating these animals as more positive in comparison with mosquitoes. This is
probably caused by the more colored wings of butterflies. Due to this attribute butterflies are
caught by collectors. This activity has caused some species to be endangered and some have
disappeared from Slovakia and the Czech Republic.
We were interested in knowledge and attitudes of butterflies and mosquitoes among elementary
school pupils. We focused on finding differences between gender and residence of respondents.
In total, we received filled questionnaires from 614 elementary school pupils from all grades of
lower secondary basic education (according to ISCED). The age of pupils was between 10 of 15
(x = 12.62; SD = 1.39). More respondents were from towns (n = 423) and the proportion
between girls and boys was similar. Boys created 51.47 % (n = 316) and girls created rest of
sample (n = 298).
We used a Butterfly-Mosquito Attitude Questionnaire (BMAQ), which contained 78 Likert type
items, 39 for butterfly and 39 for mosquito. On the statistical evaluation, factor analysis was
used which divided items in to three dimensions for each animal. Paired t-test was used next, for
finding differences between children’s attitudes and knowledge toward butterfly and mosquito.
By use of paired t-test we found pupils had better knowledge and attitudes toward butterflies in
comparison with mosquitoes.
128
UNIVERSIDADE DO MINHO - BRAGA - PORTUGAL
92
STUDIE
Pedagogická orientace, 2010, roč. 20, č. 2, s. 92–108
Mylné představy žáků II. stupně základních škol:
Možnost jejich zkoumání na příkladě tématu Ptáci
a
b
c
Milan Kubiatko , Ivana Vaculová , Eva Pecušová
a
Institut výzkumu školního vzdělávaní PdF MU, b Katedra fyziky PdF MU Brno, c Základná škola
s materskou školou Bolešov
Abstrakt: Mylné představy žáků různého věku o zvířatech byly prezentovány v mnoha
výzkumných studiích. Předkládaná studie je zaměřena na zjišt’ování mylných představ
žáků 2. stupně základních škol. Věk žáků byl v rozmezí 10 až 16 let. Výzkumný nástroj
se skládal z 30 uzavřených a také otevřených otázek, jedna byla grafická. Do analýz
bylo zahrnuto 719 vyplněných dotazníků ze 7 slovenských základních škol. Položky
testové části dotazníku byly rozděleny do 5 kategorií dle jejich charakteru, konkrétně:
1. Identifikace ptáků; 2. Rozmnožování ptáků; 3. Potrava ptáků; 4. Ptačí smysly; 5.
Migrace ptáků. Studie je zaměřena na zjištění rozdílu ve výsledcích mezi žáky různého
věku. Celkově bylo zjištěno značné množství mylných představ u všech věkových skupin
a ve všech kategoriích.
Klíčová slova: dotazník, mylné představy, ptáci, žáci
Úvod
Člověk je součástí přírodního prostředí planety Země. Stal se z něho konzument produktů živočišné a rostlinné říše. I když mu přírodní prostředí poskytuje zdroje pro jeho existenci, sám má problémy koexistovat vedle ostatních
součástí životního prostředí a způsobuje vyhubení některých rostlinných či živočišných druhů, bez toho, aby si uvědomoval, že jejich vyhubení může mít
za příčinu vymizení živé části planety. Proto je důležité klást na žáky nároky
na vzdělávání i v oblasti přírodovědných předmětů, nebot’ současné děti jako
budoucí generace budou nemalou mírou ovlivňovat život okolo nás. Musíme
si ale uvědomit, že vnímání dítěte je odlišné od vnímání dospělého, a proto
se nezřídka stává, že mylné představy přetrvávají až do dospělosti. Tady vyvstává důležitá úloha školy, která by se měla podílet na odstranění chybných
interpretací a poskytnout žákům komplexnější informace o pojmech a vztazích.
Nejdříve je však potřebné tyto mylné představy odhalit, aby mohlo dojít k jejich
odstranění a k lepšímu pochopení učiva.
Mylné představy žáků II. stupně základních škol . . .
93
Teoretická východiska
Vymezení základních pojmů
Mylné představy jsou jedním z pojmů, které určují odlišnost žákovských představ od vědeckých. Další názvy uvádějí Čáp a Mareš (2001): naivní teorie dítěte, dětské naivní koncepce, dětské miskoncepce, dětské prekoncepce. Existují také výzkumné práce, které rozlišují mezi výše uvedenými pojmy. Treagust
a Duit (2008) nepovažují za vhodné používat termín miskoncepce, tento termín byl používan na začátku výzkumu v této oblasti (konec sedmdesátých a začátek osmdesátých let minulého století) pro označení nesprávných představ
žáků. Tento termín je běžně používán výzkumníky v oblasti přírodních věd zaměřených na identifikaci mylných představ a částečně na identifikaci možných
příčin, které vedli ke vzniku mylných představ. Výzkumníci, kteří se orientují
na problémy při učení žáků se používání pojmu miskoncepce vyhýbají. Mylné
představy vznikají nepochopením, resp. špatným pochopením učiva, mohou
vznikat v průběhu výkladu učitele tím, že žák přiřazuje znakům či slovům mylnou představu, případně jim neumí přiřadit žádnou představu (Abbel, Roth,
1995; Čáp, Mareš, 2001). Samotný průběh vyučování může žákovi komplikovat pochopení probíraného učiva. Důvodem je to, že učitel při vysvětlování
nezohledňuje věk žáků a další charakteristiky, které brání správnému pochopení učiva (Čáp, Mareš, 2001). To může vést k tomu, že u některých žáků se
rozvine paralelní pochopení pojmů, jednak pro školu a jednak pro svět, ve kterém dítě žije (Chi, Slotta, Leeuw, 1994). Podobně může nastat situace, ve které
dítě, resp. žák nepřijme vysvětlení pojmů nebo učiva učitelem, ale dále věří
původním nesprávným prekonceptům a používá je. Nejdříve tedy nastává problém, jak se těchto nesprávných představ zbavit (Sandoval, Morrison, 2003).
Gropengießer (1999) rozpracovává teorii porozumění založenou na zkušenosti,
která zdůrazňuje určitou náročnost spojenou se změnou žákovských představ.
Tato teorie navrhuje vytvoření kontextů pro vyučování, na základě kterých můžeme představám porozumět, tak aby bylo pro žáky vyučování smysluplné.
Gropengießer (1999) zde dostává do hry propojení komponentů Modelu didaktické rekonstrukce (Objasnění odborných představ, Výzkum představ žáků
a Strukturování učebního prostředí), který má potenciál, zaměřit se na zkvalitnění vyučování. Vyzdvihuje se zde zejména porovnání vědeckých představ
s představami žáků, které může ověřit smysluplné kontexty pro vyučování a tím
následně napomoct k vyřešení problémů mezi výzkumem a vytvářením argumentů zdůvodňujících vyučování (Kattmann a kol., 1997).
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Milan Kubiatko, Ivana Vaculová, Eva Pecušová
Možnosti diagnostikování mylných představ
Pro diagnostikování mylných představ se používá více způsobů. Patří mezi ně
například: dětská kresba, která se dá využít při diagnostice chyb u mladších
žáků. U mladších žáků můžeme také použít metody dramatické výchovy. Učitelé
mají možnost pozorovat u dětí projevy emocí, dětské výroky a celkové chování
dítěte. K diagnostickým účelům se může použít také metoda hraní rolí, která
je využitelná i u starších žáků (Čáp, Mareš, 2001). Další metodou je rozhovor
s jednotlivcem, případně s celou skupinou. Podoba rozhovoru může být různá,
od volného povídání se žáky až po standardizované dotazování. Jelemenská
(2009) uvádí tuto metodu jako vhodnou pro identifikaci porozumění představ
žáků. Speciálním případem je fenomenografický přístup, kterým se zjišt’uje,
jak žák získává životní zkušenosti, jak vytváří obsah pojmů a jak chápe svět,
který ho obklopuje (Orsmond, Merry, Reiling, 2005). Gropengießer (1999)
uvádí kognitivně-lingvistickou analýzu, kterou je možné použít jako nástroj
ke zvýraznění představ každodenního života. Mezi diagnostické metody se dají
zařadit i projektivní techniky, které vycházejí z předpokladu, že při neukončeném zadání má žák tendenci doplňovat smysl, který mu je osobně blízký. Do
svých odpovědí tak promítá vlastní představy, postoje a názory o daném jevu
(Novák, 1989). Další diagnostickou metodou je grafické strukturování učiva.
Výzkumníky byly ověřeny 2 přístupy – vytváření sítí a map (Brown, 2003). Diagnostickou metodu plní i didaktické testy. Především se to týká testových úloh,
které nejsou lehce vyhodnotitelné a jsou „široké“ (jedna až jedna a půl strany).
Nejúčinnější jsou tzv. dvojúrovňové didaktické testy. Žák při nich vybírá odpověd’ ve dvou krocích. Nejdříve volí z nabízených možností a potom si vybírá
z několika argumentů, kterými se dá jeho předcházející odpověd’ zdůvodnit
(Yen, Yao, Chiu, 2004). Další z metod je dotazník, který obsahuje postojové
i vědomostní položky. Výběr metody záleží na samotném výzkumníkovi, zda
se přiklání spíše ke kvantitativnímu nebo ke kvalitativnímu zpracování. Také
závisí na tom, jestli cílem výzkumníka je pouze identifikace mylných představ,
nebo i jejich eliminace.
Výzkumy zaměřené na zjišt’ování mylných představ
V oblasti biologie existuje značné množství výzkumů zaměřených na zjišt’ování mylných představ. Část z nich je zaměřena na zkoumání mylných představ
u témat, která jsou pro žáky abstraktní, jako jsou fotosyntéza, dýchání rostlin,
stavba buňky. Druhá skupina výzkumných prací se zabývá přítomností mylných
95
představ v oblastech, jako jsou stavba lidského těla, botanika či zoologie. V zoologii se výzkumy týkají například identifikace živočichů, vnitřní stavby jejich
těla, chování živočichů, případně se autoři zaměřují na více aspektů. Důvod
výběru abstraktních témat je zřejmý ze skutečnosti, že u těchto témat je větší
šance zjistit značně velké množství mylných představ, at’ už u žáků základní
školy, nebo u studentů střední školy. Například Osuská, Pupala (1996) uskutečnili výzkum, v rámci kterého byly získány od žáků třetích ročníků gymnázií
rozhovory o fotosyntéze. Rozhovorů se zúčastnilo 22 žáků zhruba jeden měsíc po odučení příslušného tématu a šlo o zjišt’ování toho, jak žáci fotosyntézu
chápou, interpretují. V souhrnné kvantifikaci typů odpovědí nejvíce překvapuje
jednoznačný primát mylně strukturovaných výpovědí, v porovnání s ostatními
(od 31,8 % do 63,6 %). O mnoho nižší zastoupení mají vědecky akceptovatelné výpovědi. Simpson a Marek (1988) zkoumali u žáků základních škol chápání čtyř témat: difuze, udržení stálosti vnitřní rovnováhy těla, dýchání rostlin
a klasifikace živočichů a rostlin. Ve všech tématech byly zjištěny mylné představy žáků. Cílem výzkumu bylo zjistit, zda se výskyt chybných interpretací lišil
u žáků z velkého města v porovnání se žáky z malého města.
Zkoumání mylných představ žáků o ptácích nepatří mezi velmi rozšířené oblasti zkoumání. Mylné představy o této skupině živočichů bývají jen součástí výzkumů zaměřujících se na zkoumání mylných představ o zvířatech jako celku,
případně, jak se zkoumá jen určitá vlastnost živočichů, jako je například pohyb, případně jejich životní prostředí. Výzkumů zaměřujících se na třídu Ptáci
je málo, uvedené jsou níže. Z témat, která jsou zaměřena na výzkum mylných
představ ze zoologie, zkoumali například Randler, Höllwarth a Schall (2007)
vědomosti návštěvníků městského parku o živočišných druzích. Výsledky byly
porovnávány s výsledky kontrolní skupiny. Kontrolní skupinu tvořili lidé, kteří
nenavštěvovali městský park. Respondenti měli pojmenovat znázorněné živočichy, kteří jsou běžně přítomní v daném městském parku. Návštěvníci parku
dosahovali lepší skóre v porovnání s těmi, kteří park nenavštěvovali.
Další výzkumná práce se zabývá vědomostmi, postoji a chováním žáků základních škol, studentů středních škol a studentů vysokých škol k delfínům. Zkoumal se vliv stupně vzdělání na vědomosti a vliv vědomostí a postojů na vztah
k delfínům. Výsledky poukázaly na velmi slabé vědomosti studentů o delfínech a také na negativní postoje k nim. Pouze vysokoškolsky vzdělaní studenti
vykazovali pozitivní postoje k delfínům (Barney, Mintzes, Yen, 2005). Další výzkumy se týkaly toho, zda jsou žáci a studenti schopni rozlišit obratlovce od
bezobratlých a co si žáci základních škol představují pod pojmem zvíře. Mnoho
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dětí přiřadilo hlavu, končetiny a vnější kostru k obratlovcům. Přítomnost vnější
kostry je nejčastěji přisuzovaným znakem obratlovců u 7 až 9letých dětí. Dalším častým znakem, který žáci přisuzují obratlovcům, je přítomnost krunýře.
Tyto děti klasifikují úhoře a hady jako bezobratlovce. Důvod, který uvádějí, je,
že jejich tělo je schopné se zkroutit. Děti měly též problém klasifikovat želvu.
Část dětí ji označila jako bezobratlovce (Braund, 1991; Ryman, 1974a, 1974b;
Trowbridge, Mintzes, 1985). Pro děti není problém identifikovat člověka či
slona jako obratlovce. Větší problémy jim činí identifikace ptáka. Mnozí ho pokládají za bezobratlovce proto, že má lehké tělo a dokáže létat (Braund, 1996).
Problémy dětí s klasifikací živočichů se zabývalo i mnoho dalších autorů. Například Kattmann (2001) zjistil, že žáci základných škol nejčastěji klasifikovali
živočichy podle prostředí. Dalším klasifikačním kritériem byl způsob pohybu.
Nejčastěji uváděli létání a plazení. Morfologické a anatomické kritérium hrálo
minimální úlohu. Kromě této existují i další práce, které se věnují klasifikaci
živočichů (Prokop, Rodák, 2009; Tunnicliffe, Reiss, 1999). Prokop, Kubiatko
a Fančovičová (2007, 2008) zkoumali mylné představy o ptácích u žáků základních škol. Hlavním záměrem výzkumu bylo zjistit, jak umí žáci určovat
ptáky a jak se jejich představy o avifauně mění s přibývajícím věkem. Autoři
zjistili, že žáci všech stupňů základních škol mají problémy s určováním ptáků.
Metodika
V našem příspěvku prezentujeme jednu z možností zkoumání mylných představ žáků o ptácích. Hlavním cílem výzkumu bylo zjistit mylné představy o ptácích u žáků II. stupně základních škol. V shodě se Škodou a Doulíkem (2007)
jsme se zaměřili na zkoumání kognitivní dimenze mylných představ u žáků,
proto byly použity otázky testového charakteru. Kromě analýzy mylných představ bylo cílem nabídnout potencionálním čtenářům možnost kvantitativního
vyhodnocování získaných dat. Hlavní výzkumná otázka zněla: Bude počet mylných představ vyšší u žáků, kteří ještě dané učivo neabsolvovali v porovnání
se žáky, kteří už dané učivo absolvovali? Výzkumný vzorek tvořilo 719 žáků
II. stupně ze sedmi slovenských základních škol. Věkové rozmezí žáků bylo od
10 do 16 let (x = 12,72; S D = 1,39). Chlapci byli zastoupení v počtu 338,
děvčat bylo 381 ze 7 ZŠ. Výzkumný vzorek tvořili respondenti z vesnického
prostředí (n = 448) i z městského prostředí (n = 271). Největší část tvořili
žáci šestého ročníku (n = 195), dále žáci sedmého ročníku (n = 172), devátého (n = 134), osmého (n = 130) a nejméně bylo žáků pátého ročníku
(n = 88). Přičemž učivo o třídě Ptáci ještě nebylo probráno žáky pátého a šes-
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tého ročníku. Obsah učiva v jednotlivých ročnících základních škol je uveden
na stránkách Státního pedagogického ústavu (www.statpedu.sk).
Jako výzkumný nástroj byl použit dotazník, který byl rozdělen do několika
částí. Úvodní část obsahovala informace o samotném dotazníku, po ní následovaly demografické údaje. V demografických údajích jsme se zajímali o pohlaví respondenta, ročník, bydliště (vesnice nebo město) a či respondent chová
nebo nechová domácí zvíře, kromě hospodářských. Jelikož výzkumná otázka
byla zaměřena na ročník, ostatní demografické údaje jsme nebrali v úvahu.
Druhá část byla postojová a třetí testová. V příspěvku prezentujeme vyhodnocování testové části dotazníku. Ta se skládala z 30 otázek, 12 bylo otevřených
a 18 uzavřených. U uzavřených bylo žákům nabídnuto 3 až 5 možností, ze
kterých byla vždy jen jedna správná. Otevřené otázky byly konstruovány tak,
aby odpověd’ žáka nepřesáhla jednu větu a aby žáci stihli dotazník vyplnit za
jednu vyučovací hodinu. Otázky v testové části dotazníku byly vytvořeny s přihlédnutím na obsah učiva ZŠ. Výzkumný nástroj bude případným zájemcům
poskytnut na požádání. Inspirací nám byly i práce jiných autorů, kteří se zabývali podobnou tematikou (Kubiatko, Prokop, 2007; Prokop, Kubiatko, Fančovičová, 2007). Dotazník autorů Prokop, Kubiatko, Fančovičová (2007) byl
také zaměřen na zkoumání mylných představ žáků o ptácích, z něho však byly
použity pouze některé otázky, které se jevily jako problematické vzhledem ke
správnému řešení. Inspirací byly pro nás kategorie, do kterých byly zařazeny
jednotlivé otázky. Před samotnou administrací byl dotazník zhodnocen dvěma
vysokoškolskými učiteli, zabývajícími se systematickou zoologií. Dotazník byl
žákům zadáván prostřednictvím jejich učitele. Ten jim dotazníky rozdal a upozornil je, že se nejedná o testování, ale že odpovědi budou použity na zkoumání
jejich představ o ptácích. Respondenti nebyli časově ohraničení, ale vyplnění
nepřesáhlo 30 minut.
Podle charakteru jednotlivých položek byly otázky v testové části dotazníku
rozděleny do 5 kategorií: identifikace ptáků (10), rozmnožování ptáků (7), potrava ptáků (5), ptačí smysly (4), migrace ptáků (4). Čísla v závorce udávají
počet otázek v jednotlivých kategoriích. Počet otázek v kategoriích vznikl na
základě subjektivního rozhodnutí autora s přihlédnutím na výše vzpomínané
studie, ve kterých bylo zastoupení jednotlivých otázek v kategoriích přibližně
stejné. Vyhodnocování získaných dat může být různorodé. Jedna z možností je
kódovat odpovědi na správné a nesprávné, přičemž správné se přiřadí číslo 1
a nesprávné 0. Pro účely zkoumání mylných představ je vhodnější brát v úvahu
i vyhodnocovat každou otázku zvlášt’, právě kvůli zjištění různých mylných
98
představ žáků o zkoumaném fenoménu. Úlohou výzkumu bylo zjistit i představy žáků, které mohou vycházet z jejich každodenní zkušenosti. Odpovědi
byly kódovány tak, aby bylo možné bez problémů odlišit správné interpretace
od vědecky nesprávných. V úvahu by přicházela rovněž možnost sofistikovanějšího vyhodnocování odpovědí žáků, přičemž by bylo možné opírat se o model
didaktické rekonstrukce (Kattmann a kol., 1997). Ten nabízí možnost adekvátněji rozlišit mezi vědecky přiměřenými odpovědmi a antropomorfními představami žáků (srov. Jelemenská, 2009, s. 173–175). V našem výzkumu toto nebylo uplatněno, víceméně nabízí se možnost vydat se tímto směrem v našich
dalších navazujících výzkumech. Počet mylných představ byl značný i u žáků,
kteří už dané učivo absolvovali. Na vyhodnocování dat se kromě percentuální
úspěšnosti použily i některé metody deskriptivní statistiky (aritmetický průměr,
směrodatná odchylka). Z metod induktivní statistiky byl použit Pearsonův korelační koeficient a analýza rozptylu. Tyto dvě metody byly použity při vyhodnocování celkové úspěšnosti respondentů a Pearsonův chí-kvadrát test (2) byl
použit při vyhodnocování jednotlivých odpovědí žáků. Na výpočet reliability
výzkumného nástroje bylo použito Cronbachovo alfa. Tato metoda se používá
až po získání dat a po jejich překódování do číselné podoby. Jak otevřeným
tak i uzavřeným položkám bylo přiřazeno číslo 1, když byla odpověd’ správná,
a číslo 0, pokud byla odpověd’ nesprávná. Až po tomto překódování byla zjištěna reliabilita výzkumného nástroje. Reliabilita nebyla vyhodnocována zvlášt’
pro otevřené položky a zvlášt’ pro uzavřené.
Výsledky
Celková analýza vědomostní části testu
Celkový počet položek v testové části dotazníku byl 30. Pomocí Cronbachova
alfa byla zjištěna reliabilita testové části dotazníku (α = 0,55), což indikuje
střední spolehlivost dotazníku. Podle charakteru jednotlivých položek byly
otázky v testové části dotazníku rozděleny do 5 kategorií: identifikace ptáků
(10); rozmnožování ptáků (7); potrava ptáků (5); ptačí smysly (4); migrace
ptáků (4). V závorce za názvem kategorie je uveden počet položek do něj patřících. V tabulce 1 je uvedena průměrná korelace mezi jednotlivými kategoriemi
a v tabulce 2 jsou uvedeny některé statistické charakteristiky jednotlivých kategorií. Korelačním koeficientem jsme se snažili dokázat nezávislost kategorií,
tedy že otázky jsou správně zařazeny do určité kategorie a nepatří současně do
jiné.
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Tab. 1: Průměrná korelace mezi jednotlivými kategoriemi
Rozmnožování
ptáků
Identifikace
ptáků
Rozmnožování
ptáků
Potrava
ptáků
0,27***
Potrava ptáků
Ptačí smysly
Migrace ptáků
0,09*
0,15***
0,30***
0,11**
0,09*
0,22***
0,04
Ptačí smysly
0,14***
0,12**
* p < 0,05; ** p < 0,01; *** p < 0,001
Z tabulky 1 je zřejmé, že korelace mezi jednotlivými kategoriemi byla malá
(0,1–0,3), případně až triviální (hodnoty pod 0,1). Znamená to, že jednotlivé
kategorie se navzájem ovlivňují velmi slabě (Cohen, 1988).
Tab. 2: Vybrané statistické charakteristiky sledovaných kategorií
Identifikace ptáků
Počet otázek
Průměrné skóre
Relativní
úspěšnost (%)
Směrodatná
odchylka
10
5,87
58,70
1,62
Rozmnožování ptáků
7
4,28
61,14
1,36
Potrava ptáků
5
1,09
21,80
0,94
Ptačí smysly
4
1,34
33,50
0,70
Migrace ptáků
4
2,23
55,75
0,99
Z tabulky 2 je zřejmé, že žáci měli největší problém s otázkami týkajícími se
potravy ptáků, kde úspěšnost nebyla ani čtvrtinová, a také ptačích smyslů, kde
úspěšně na otázku odpověděla přibližně třetina respondentů. Nejméně problémů činily žákům otázky z kategorie rozmnožování ptáků, kde byla úspěšnost více než 60 %. Ve zbývajících dvou kategoriích dosahovala úspěšnost žáků
hodnotu o něco vyšší než 50 %.
V grafu na obr. 1 je uveden průměrný počet bodů dosažených v jednotlivých
ročnících pro každou z uvedených kategorií. V kategoriích identifikace ptáků,
migrace ptáků a ptačí smysly dosahovali nejvyššího skóre žáci osmého ročníku.
V kategorii potrava ptáků to byli žáci šestého ročníku a žáci pátého ročníku
dosahovali nejvyšší skóre v otázkách týkajících se rozmnožování ptáků.
Průměrné skóre jednotlivých ročníků jsme podrobili dalšímu statistickému
zpracování, a to konkrétně analýze rozptylu (ANOVA). Statisticky významný
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Obr. 1: Průměrné skóre žáků jednotlivých ročníků za jednotlivé dimenze
rozdíl ve výsledcích mezi ročníky jsme zjistili v kategorii identifikace ptáků
(F(4,714) = 8,98; p < 0,001). Žáci šestého ročníku v této dimenzi dosahovali výrazně nižší skóre v porovnání se žáky z ostatních ročníků. U kategorie potrava
ptáků byl také zjištěn statisticky významný rozdíl ve výsledcích mezi ročníky
(F(4,714) = 7,87; p < 0,001), přičemž žáci devátého ročníku dosahovali nejnižší
skóre v porovnání s ostatními ročníky. Žáci pátého ročníku dosahovali výrazně
vyšší skóre, v porovnání s jejich staršími spolužáky, v otázkách, které se týkaly
rozmnožování ptáků (F(4,714) = 3,47; p < 0,01).
V kategorii ptačí smysly byl zjištěn rozdíl ve výsledcích mezi ročníky (F(4,714) =
2,91; p < 0,05), přičemž největší rozdíl v dosaženém skóre byl mezi žáky
šestého a osmého ročníku. Ve zbylé kategorii migrace ptáků nebyl zjištěn statisticky významný rozdíl ve výsledcích mezi jednotlivými ročníky (F(4,714) =
2,11).
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Celkové skóre z testu bylo 18,28 bodů (n = 719; SD = 4,30). Minimální hodnota byla 6 a nejvyšší 30.
Na výsledky mezi ročníky, ze kterých jsou respondenti, je možné se dívat
ze dvou pohledů. První je ten, že do analýzy se zahrnou jednotlivé ročníky
(F(4,714) = 4,22; p < 0,01), kde nejvíce bodů dosahovali žáci 8. ročníku
(x̄ = 15,39) a nejnižší počet dosahovali žáci 6. ročníku (x̄ = 14,04 – graf 2).
Druhý pohled je ten, že se do úvahy vezmou pouze žáci, kteří už absolvovali
učivo o třídě Ptáci a ti, kteří ho ještě neabsolvovali. I v tomto případě byl zjištěn statisticky významný rozdíl ve výsledcích (F(1,717) = 13,04; p < 0,001) ve
prospěch žáků, kteří už dané učivo absolvovali (x̄ = 15,16). Žáci, kteří ještě
na hodinách přírodopisu učivo o ptácích neabsolvovali, měli průměrné skóre
14,23 bodů.
Obr. 2: Průměrné skóre žáků jednotlivých ročníků
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Analýza vybraných odpovědí
Analýza odpovědí žáků na jednotlivé otázky má spíše význam pro didaktiku
biologie než pro pedagogiku, proto uvádíme jen vybrané otázky, ve kterých
bylo určení správné odpovědi pro žáky často problémem. Kromě úspěšnosti
odpovědí na danou otázku jsou uvedeny i časté nesprávné odpovědi.
Identifikace ptáků
V kategorii identifikace ptáků při otázce „Co se děje s peřím ptáka v průběhu
jeho života?“ dosahovali nejnižšího skóre žáci pátého ročníku, ve srovnání
s ostatními respondenty (χ 2 = 23,81; p < 0,001). Správné odpovědi nejčastěji uváděli žáci 8. ročníku (χ 2 = 23,81; p < 0,001). Žáci osmého ročníku
jako jediní dosáhli úspěšnosti více než 50 %. U žáků pátých ročníků procento
správných odpovědí kleslo pod 20 %. Téměř třetina respondentů uváděla, že
ptákům peří postupně dorůstá, a čtvrtina žáků zvolila odpověd’ „peří naroste
v prvním roku života“, s tím, že se s ním už dále nic neděje. Více než 40 %
respondentů odpovědělo na tuto otázku správně, a to, že ptákům se peří mění
každý rok. Jednou z častých mylných představ týkajících se identifikace ptáků
je pokryv těla tučňáka. Jelikož je zařazen do třídy Ptáci, má pokryté tělo peřím. Nejvíce správných odpovědí (χ 2 = 21,83; p < 0,001) uvedli nejmladší
žáci (5. ročník), a to přibližně 32 %. Nejvíce chybných odpovědí (χ 2 = 21,83;
p < 0,001) uváděli nejstarší žáci (9. ročník), kde procento správných odpovědí klesalo až k 10 %. Ze všech žáků správně na tuto otázku odpovědělo
přibližně 20 % respondentů. Téměř polovina žáků uvedla „holou kůži“, tedy
tučňák podle nich nemá žádný tělní pokryv, a téměř 30 % označilo za pokryv
těla srst. Další možnosti byly „vlna“ a „šupiny“, ale tyto nabízené odpovědi
dohromady označilo jen o něco více než 3 % respondentů.
Rozmnožování ptáků
Z kategorie rozmnožování ptáků měli žáci největší problémy s vysvětlením
pojmu krmivý pták. Od žáků jsme očekávali odpověd’, že mlád’ata jsou závislá na rodičích, kteří je musí krmit. Od toho je odvozen pojem „krmivý
pták“. Nejúspěšnější byli žáci sedmého ročníku (χ 2 = 18,78; p < 0,001), jejich
úspěšnost byla více než 35 %, nejhorších výsledků dosahovali žáci 6. ročníku
(χ 2 = 18,78; p < 0,001), relativní početnost správných odpovědí u nich poklesla pod 20 %. Správnou odpověd’ označilo téměř 28 % respondentů. Nesprávných odpovědí bylo uváděno celé spektrum. Jednou z nejčastějších byla
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„musí ho krmit člověk“, tu označilo přibližně 21 % dotázaných. Z dalších byly
uváděny například: „uživí se sám, hodně sežere, je chráněný, . . . “.
Potrava ptáků
Jednou z otázek týkajících se potravy ptáků bylo dokázat vliv pohádek, at’ už
z knih, nebo z televizního vysílání na utváření mylné představy. Ptali jsme se
žáků, proč datel klove do stromu. Správná odpověd’ je „hledání a vybírání potravy“. Na tuto otázku správně odpovědělo přibližně jen 43 % tázaných. Zbytek se přiklonil k nesprávné odpovědi, která byla téměř vždy uváděna jako
„lékař stromů“. V porovnání ročníků byli nejúspěšnější žáci sedmých ročníků
(χ 2 = 13,31; p < 0,01), nejvíce nesprávných odpovědí uváděli žáci pátých
ročníků (χ 2 = 13,31; p < 0,01). V žádném ročníku nedosáhli žáci více než
50 % úspěšnosti. Jak uvádíme výše, otázky týkající se hledání potravy a potravního složení byly pro žáky nejproblematičtější. V žádné z nich neodpovědělo
na otázku správně více než 50 % respondentů. Ve většině případů se úspěšnost
pohybovala kolem 20 %.
Ptačí smysly
Další otázkou, která se týkala ptačích smyslů a která vykazovala jednu z nejnižších úspěšností, jsme se ptali na to, kdy podle žáků vidí sova lépe. Sova vidí
stejně přes den i v noci. Samozřejmě je to živočich, který je aktivní převážně
v noci, a to pravděpodobně vedlo k častému určení nesprávné odpovědi, tedy,
že sova vidí lépe v noci. Téměř 96 % uvedlo právě tuto nesprávnou odpověd’
a jen přibližně 3 % oslovených uvedlo správnou odpověd’. Nejčastější správnou
odpověd’ uváděli žáci 8. ročníku (χ 2 = 16,41; p < 0,01). Správně jich odpovědělo jen přibližně 7 %. U žáků 5. ročníku se vyskytlo nejvíce nesprávných
odpovědí (χ 2 = 16,41; p < 0,01), žádný z žáků pátého ročníku neodpověděl
správně.
Migrace ptáků
Poslední kategorie se týkala migrace ptáků. V jedné z otázek jsme se ptali na
důvod, proč někteří ptáci odlétají a jiní zůstávají. Jen necelých 13 % uvedlo
správný důvod, a to nedostatek potravy. Nejčastější nesprávnou odpovědí bylo,
že by zamrzli (23 %). Více než 18 % odpovědělo, že nejsou přizpůsobeni na
zimu a téměř 16 % žáků uvedlo, že jsou teplomilní, případně, že jsou stěhovaví, což je samozřejmě pravda, ale to je jen důsledek nepřítomnosti potravy.
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Nejvíce správných odpovědí z jednotlivých ročníků bylo zaznamenáno u žáků
z 9. ročníků (χ 2 = 23,82; p < 0,001), a to téměř 70 %. Nesprávné odpovědi
nejčastěji uváděli žáci pátého ročníku (χ 2 = 23,82; p < 0,001), přibližně 40 %.
Diskuse
Předkládaná výzkumná studie si dala za cíl zjistit mylné představy žáků
II. stupně základních škol. Následně bylo zkoumáno, zda se mylné představy
liší v závislosti na ročníku, který navštěvují respondenti. Nejvyššího skóre dosahovali žáci osmého ročníku a nejnižšího žáci šestého ročníku. O příčinách,
proč nastal daný stav, se můžeme pouze domnívat. Při distribuci dotazníků
jsme nezkoumali složení samotných tříd, zda jsou v nich zastoupeni jen žáci
s výborným prospěchem, nebo jen žáci, jejichž prospěch dosahuje průměrně
vyšších čísel. Mohl proto nastat jev, že právě v osmém ročníku se vyskytovalo
nejvíce žáků s výborným prospěchem a v šestém byli ne právě úspěšní žáci.
To může být i impulzem pro další výzkum v této problematice, prozkoumat
vztah mezi mylnými představami a prospěchem žáků. Námi vytvořené otázky
byly rozděleny do pěti kategorií: identifikace ptáků, rozmnožování ptáků, potrava ptáků, ptačí smysly a migrace ptáků. Mylné představy se vyskytly ve všech
kategoriích a ve všech sledovaných ročnících.
Při porovnávání vlastních zjištění s jinými autory se objevila podobnost. Prokop, Kubiatko a Fančovičová (2007, 2008) zkoumali mylné představy o ptácích
u žáků základních škol. Žáci měli problémy zejména s identifikací ptáků, kteří
nežijí na Slovensku, jako je např. tučňák. Vyskytoval se ve všech případech problém s určením pokryvu těla. Podobné zjištění uvádějí i Trowbridge a Mintzes
(1985). Při percentuálním vyhodnocení otázky o tom, co se děje s peřím ptáka
v průběhu jeho života, tvořily nesprávné odpovědi až 57,86 %. V literatuře
existuje několik výzkumů, které se zaměřují na představy žáků o identifikaci živočichů. Například Trowbridge a Mintzes (1985) uvádějí, že žáci všech stupňů
mají problémy s jejich identifikací. Z druhé kategorie rozmnožování ptáků se
jako nejvíce problémová ukázala otázka o tom, co znamená, že pták je krmivý. Správnou odpověd’ „krmiví ptáci jsou ti, které rodiče krmí na hnízdě,
nebot’ nejsou schopni najít si sami potravu“ neuvedla ani 1/3 respondentů.
Třetí kategorii tvořila potrava ptáků. Jednoznačně tato kategorie, ve srovnání
s ostatními, činila žákům největší problémy. Ani na jednu z pěti otázek sem zařazených neodpověděla správně ani 1/2 respondentů. V odpovědích na otázku
„Proč datel klove do stromu?“ byli nejméně úspěšní žáci 5. ročníku a celková
úspěšnost všech respondentů byla 42,98 %, kdy zvolili správnou odpověd’ „hle-
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dání resp. vybírání potravy“. Podobný výsledek zaznamenali i autoři Prokop,
Kubiatko, Fančovičová (2007). Ptačí smysly tvořily čtvrtou kategorii. Ze všech
otázek použitých v dotazníku byla nejnižší úspěšnost zaznamenána u odpovědí na otázku, která se týkala zrakového smyslu sovy. Správnou odpověd’,
která zněla „sova vidí stejně přes den i v noci“, uvedlo jen 3,34 % respondentů. Nejhorších výsledků dosáhli žáci 5. ročníku. Alarmující je zjištění, že
ani jeden z těchto žáků neuvedl správnou odpověd’. V kategorii migrace ptáků
činila žákům největší problémy otázka o tom, proč někteří ptáci u nás přes
zimu zůstávají a jiní odlétají. Až 87,34 % tvořily nesprávné odpovědi, přičemž
nejvíce jich uvedli žáci 9. ročníku. Na základě zjištěných výsledků si můžeme
položit otázku, proč se u žáků každé věkové skupiny vyskytuje značný počet
chybných interpretací o ptácích. Vědecká i popularizační literatura přitom dost
často uvádí, že ptáci patří mezi nejoblíbenější živočichy u dětí i dospělých.
O příčinách tohoto stavu se můžeme jen domnívat, důvodem může být malý
zájem o zoologii, případně i celou biologii ze strany žáků. Příčinami mylných
představ mohou být také faktory vyskytující se mimo školní prostředí. Nejvíce
se do myslí žáků dostávají informace poskytované z médií, jako je televize a internet.
Ptáci jsou neoddělitelnou součástí učiva přírodopisu na základní škole. Proto
každá informace o tom, jak je žáci vnímají a co o nich vědí, může pomoci
učitelům pozměnit, případně upravit jejich učitelské strategie tak, aby v co
největší míře eliminovali mylné představy žáků o této skupině živočichů. Eliminace miskoncepcí může probíhat i přímým pozorováním ptáků, tak jak uvádí
Dillon a kol. (2006). Druhým způsobem by mohlo být aplikování prvků problémového vyučování (Savery, 2006), což může být výhodné, nebot’ zvyšuje úroveň myšlení studentů. Učitelé mohou zapojit žáky do okruhu výzkumu a řešení
otázek výzkumu umožňuje žákům shromažd’ovat informace, zaujmout stanovisko, interpretovat zjištění apod. Z výsledků vyplynula nedostatečná informovanost žáků o exotických druzích ptáků, jako je tučňák, což může indikovat, že
žáci se na hodinách učí jen o domácích druzích. Dále by se učitelé měli snažit
zaměřit i na netypické druhy ptáků (tučňák, pštros, emu, . . . ). Z výzkumu vyplynulo, že žáci nemají dostatečně osvojeny vědomosti o smyslech ptáků, což
se projevilo u odpovědí, týkajících se zraku sovy a čichu samiček vrabců. Důležitým aspektem, jak je uvedeno výše, je i přímé pozorování ptáků a následné
vysvětlení pozorovaného, nebot’ bez adekvátního vysvětlení zůstanou v žácích
zakořeněny představy například o tom, že datel klove do stromů proto, aby je
vyléčil.
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Závěr
V předkládané studii jsme si dali za cíl zjistit nejčastější mylné představy o ptácích u žáků II. stupě základních škol. Zaměřili jsme se zejména na srovnání
jednotlivých ročníků, jejich úspěšnosti a detailněji jsme vyhodnotili vybrané
otázky. Také jsme představili některé statistické metody, které mohou být využity při zkoumání mylných představ. Věříme, že předkládaná studie přinese
nové informace, které mohou sloužit ke zkoumání mylných představ.
Literatura
ABBEL, S. K., ROTH, M. Reflections on a fifth-grade life science lesson: making sense of children’s
understanding of scientific models. International Journal of Science Education, 1995, roč. 17,
č. 1, s. 59–74.
BARNEY, E. C., MINTZES, J. J., YEN, C. F. Assessing knowledge, attitudes and behavior toward charismatic megafauna: The case of dolphins. The Journal of Environmental Education, 2005,
roč. 36, č. 2, s. 41–55.
BRAUND, M. Children’s ideas in classifying animals. Journal of Biological Education, 1991, roč. 25,
č. 2, s. 103–110.
BRAUND, M. Snakes can’t have backbones – can they? Primary Science Review, 1996, roč. 44, č. 1,
s. 20–22.
BROWN, D. S. High school biology: A group approach to concept mapping. The American Biology
Teacher, 2003, roč. 65, č. 3, s. 192–197.
CHI, M. T. H., SLOTTA, J. D., LEEUW, N. From things to processes: A theory of conceptual change for
learning science concepts. Learning and Instruction, 1994, roč. 4, č. 1, s. 27–43.
COHEN, J. Statistical power analysis for the behavioral sciences. 2. vyd. New York: Academic Press,
1988.
ČÁP, J., MAREŠ, J. Psychologie pro učitele. Praha: Portál, 2001.
DILLON, J., RICKINSON, M., TEAMEY, K., MORRIS, M., CHOI, M. Y., SANDERS, D., BENEFIELD, B. The
value of outdoor learning: Evidence from research in the UK and elsewhere. School Science
Review, 2006, roč. 87, č. 320, s. 107–111.
GROPENGIESSER, H. Was die Sprache über unsere Vorstellungen sagt. Kognitionslinguistische Analyse als Methode zur Erfassung von Vorstellungen: Das Beispiel Sehen. Zeitschrift für Didaktik
der naturwissenschaften, 1999, roč. 5, č. 1, s. 57–77.
JELEMENSKÁ, P. Model didaktické rekonstrukce z metodologického pohledu. In JANÍKOVÁ, M., VL Č KOVÁ , K. et al. Výzkum výuky: Tematické oblasti, výzkumné přístupy a metody. Brno: Paido, 2009,
s. 145–170.
JELEMENSKÁ, P. Prepojenost’ výberu učebných obsahov, zist’ovania výkonov žiakov a predstáv učitel’ov. Význam empirických výsledkov výskumu didaktiky biológie na príklade vyučovania evolúcie. Pedagogika, 2009, roč. 59, č. 2, s. 164–181.
KATTMANN, U. Acquatics, flyers, creepers and terrestrials – students’ conceptions of animal classification. Journal of Biological Education, 2001, roč. 35, č. 3, s. 141–147.
107
KATTMANN, U., DUIT, R., GROPENGIESSER, H., KOMOREK, M. Das Modell der Didaktischen Rekonstruktion – Ein theoretischer Rahmen für naturwissebschaftsdidaktische Forschung und Entwicklung. Zeitschrift für Didaktik der Naturwissenschaften, 1997, roč. 3, č. 3, s. 3–18.
KUBIATKO, M., PROKOP, P. Pupils’ misconceptions about mammals. Journal of Baltic Science Education,
2007, roč. 6, č. 1, s. 5–14.
NOVÁK, Z. Test volných slovních asociací jako test školních znalostí. Pedagogika, 1989, roč. 39, č. 4,
s. 431–445.
ORSMOND, P., MERRY, S., REILING, K. Biology Students’ Utilization of Tutors’ Formative Feedback:
A Qualitative Interview Study. Assessment and Evaluation in Higher Education, 2005, roč. 30,
č. 4, s. 369–386.
OSUSKÁ, L’., PUPALA, B. „To je ako zázrak prírody“: fotosyntéza v žiakovom poňatí. Pedagogika,
1996, roč. 46, č. 3, s. 214–223.
PROKOP, P., KUBIATKO, M., FAN ČOVI ČOVÁ, J. Slovakian pupils’ knowledge of and attitudes toward
birds. Anthrozoös, 2008, roč. 21, č. 3, s. 221–235.
PROKOP, P., KUBIATKO, M., FAN ČOVI ČOVÁ, J. Why do cocks crow? Children’s concepts about birds.
Research in Science Education, 2007, roč. 37, č. 4, s. 393–405.
PROKOP, P., RODÁK, R. Ability of Slovakian pupils to identify birds. Eurasia Journal of Mathematics,
Science & Technology Education, 2009, roč. 5, č. 2, s. 127–133.
RANDLER, C., HÖLLWARTH, A., SCHAAL, S. Urban park visitors and their knowledge of animal species.
Anthrozoös, 2007, roč. 20, č. 1, s. 65–74.
RYMAN, D. Children’s understanding of the classification of living organisms. Journal of Biological
Education, 1974a, roč. 8, č. 3, s. 140–144.
RYMAN, D. The relative effectiveness of teaching methods on pupils’ understanding of the classification of living organisms at two levels of intelligence. Journal of Biological Education, 1974b,
roč. 8, č. 4, s. 219–223.
SANDOVAL, W. A., MORRISON, K. High school students’ ideas about theories and theory change after
a biological inquiry unit. Journal of Research on Science Teaching, 2003, roč. 40, č. 4, s. 369
až 392.
SAVERY, J. R. Overview of problem-based learning: Definitions and Distinctions. The Interdisciplinary Journal of Problem-based Learning, 2006, roč. 1, č. 1, s. 9–20.
SIMPSON, W. D., MAREK, E. A. Understandings and misconceptions of biology concepts held by students attending small high schools and students attending large high schools. Journal of Research on Science Teaching, 1988, roč. 25, č. 5, s. 361–374.
ŠKODA, J., DOULÍK, P. Children’s concepts research of selected common phenomena from physics
and chemistry at elementary schools. Science Education in Changing Society, 2007, roč. 1, č. 1,
s. 106–112.
TREAGUST, D. F., DUIT, R. Compatibility between cultural studies and conceptual change in science
education: there is more to acknowledge than to fight straw men! Cultural Studies of Science
Education, 2008, roč. 3, č. 2, s. 387–395.
TROWBRIDGE, J. E., MINTZES, J. J. Students’ alternative conceptions of animals and animal classification. School Science and Mathematics, 1985, roč. 85, č. 4, s. 305–316.
108
TUNNICLIFFE, S. D., REISS, M. J. Building a model of the environment how do children see animals.
Journal of Biological Education, 1999, roč. 33, č. 3, s. 142–148.
YEN, C. F., YAO, T. W., CHIU, Y. C. Alternative Conceptions in Animal Classification Focusing on Amphibians and Reptiles: A Cross-Age Study. International Journal of Science and Mathematics
Education, 2004, roč. 2, č. 2, s. 159–174.
Autoři
PaedDr. Milan Kubiatko, PhD., Institut výzkumu školního vzdělávání
Pedagogické fakulty Masarykovy univerzity, Poříčí 31, 603 00 Brno, e-mail:
[email protected]
Mgr. Ivana Vaculová, Ph.D., Katedra fyziky Pedagogické fakulty Masarykovy
univerzity, Poříčí 7, 603 00 Brno e-mail: [email protected]
Mgr. Eva Pecušová, Základná škola s materskou školou Bolešov, Štúrova 276,
018 53 Bolešov, Slovenská republika e-mail: [email protected]
Basic Pupils´ Wrong Ideas about Birds
Abstract: Wrong ideas of pupils about animals have been the focus on many research
papers. This study concentrates on investigating of basic school pupils’ wrong ideas.
The age of the pupils was from 10 to 16. The research tool included 30 open-ended
and multiple choice questions, one question was pictorial. The total number of 719
questionnaires from 7 Slovakian basic schools was included in the analyses. The items
were divided into five categories, namely: 1. Identification of birds; 2. Reproduction
of birds; 3. Food of birds; 4. Birds senses; 5. Migration of birds. The study is focused
on finding differences in results of pupils in different age groups. The large amount of
wrong ideas was found in all age groups and categories.
Key words: questionnaire, wrong ideas, birds, pupils
Postoje českých
vysokoškolských študentov
k používaniu IKT vo vyučovaní
prírodovedných predmetov
Czech university students´attitudes towards ICT
used in science education
Milan Kubiatko – ČR
Abstrakt: Príspevok je zameraný na zistenie rozdielov
v postojoch k informačným a komunikačným technológiám u českých vysokoškolských študentov. Postoje boli
vyhodnocované celkovo a následne s ohľadom na gender, ročník a bydlisko respondentov. Výskumnú vzorku
tvorilo 316 študentov. Vyhodnotenie dát bolo realizované
prostredníctvom faktorovej analýzy, analýzy kovariancie,
analýzy rozptylu a t-testu. Použitím faktorovej analýzy boli
položky rozdelené do piatich dimenzií: 1) Vplyv IKT na
vyučovací proces, 2) Vplyv IKT na človeka a prostredie,
3) Využívanie IKT vo vyučovaní, 4) Škola a IKT, 5) IKT
ako didaktická pomôcka. Výsledkom výskumu bolo, že
muži, druháci a študenti žijúci v meste majú pozitívnejšie
postoje.
Kľúčové slová: dotazník, informačné a komunikačné
technológie, postoje, prírodovedné predmety, vysokoškolskí študenti
1 Úvod
História využívania informačných a komunikačných
technológií (IKT) vo vyučovaní nie je dlhá, napriek tomu
ich vplyv je neustále narastajúci. Význam IKT pre vyučovací proces bol potvrdený viacerými výskumnými štúdiami (napr. Fančovičová & Prokop, 2008). používanie IKT
vo vyučovaní poskytuje študentom príležitosť analyzovať
procesy v prírode, navzájom ich porovnávať a tiež pracovať nezávisle (Kaino, 2008). IKT však nemožno brať ako
úplnú náhradu za učiteľa, práve naopak, úloha učiteľa
je pri používaní IKT vo vyučovaní veľmi zodpovedná a
náročná. Učiteľ musí usmerňovať vyučovací proces, tak
aby IKT plnili svoju úlohu, ktorá im je prisudzovaná.
2 Teoretické východiská
Zhao, Tan & Mishra (2001) vo svojej práci poukázali
nárast pozitívnych postojov k IKT u učiteľov, keď sa počítače používali v triedach počas vyučovacieho procesu.
Pozitívny vplyv IKT na vyučovanie vo veľkej miere záleží
aj na postojoch učiteľov k IKT (Teo, 2006). Veľa autorov
vyzdvihuje určité oblasti, ktoré vplývajú na postoje k IKT.
Napríklad je to vnímanie užitočnosti IKT, dôvera v IKT
(Tsitouridou & Vryzas, 2003), vplyv genderu, či strach z
používania IKT (Yıldırım, 2000). Na integrácia IKT do kurikula prírodovedných predmetov výrazne vplýva pozitívny
postoj učiteľov k technológiám. Na dosiahnutie pozitívnych postojov učiteľov k IKT môže výraznou mierou vplývať úspešná integrácia IKT pri vzdelávaní učiteľov. Okrem
8
Slovenský učiteľ
povinných predmetov súvisiacich práve s používaním IKT
vo vyučovaní prírodovedných predmetov k pozitívnym
postojom môže napomôcť absolvovanie rôznych kurzov
zameraných na využívanie IKT. Takisto absolvovanie kurzov môže ovplyvniť postoje k IKT aj u učiteľov v praxi.
Absolvovanie kurzov má aj výhodu z časového hľadiska.
Učiteľom trvá určitú dobu dokým si naplánujú, pripravia
a vyskúšajú hodinu a práve poznatky, ktoré získajú na
kurzoch im môžu vyššie spomenuté činnosti uľahčiť a tým
skrátiť čas na prípravu (Cuckle & Clarke, 2002). Úspešná
integrácia IKT do vyučovacieho procesu musí prekonať aj
iné prekážky, akými sú napríklad nedostatočné vybavenie
technológiami, nemožnosť prístupu k technológiám, ale
aj nedostatočná administratívna podpora zo strany školy.
Všetky vyššie spomenuté fakty, ale aj mnohé iné môžu
vyvolať negatívne postoje k IKT
Výskumné štúdie orientované na postoje respondentov k IKT sú vo veľkej miere orientované, okrem celkovej úrovne postojov, na zistenie rozdielov medzi mužmi
a ženami v ich postojoch k technológiám. Dorup (2004)
uvádza pozitívnejšie postoje u mužov k používaniu počítačov v porovnaní so ženami, muži sa takisto vyslovili
za nahradenie tradičného spôsobu vyučovania, počítačmi riadené vyučovanie. Jeho respondentmi boli študenti
medicíny. Len veľmi malé percento študentov sa vyslovilo
za nepoužívanie počítačov vo výučbe.
Palaigeorgiou a kol. (2005) zistili približne rovnakú
úroveň postojov k IKT u mužov aj žien a tiež aj rovnaký
záujem o využívanie technológií vo výučbe. Autori zistili rozdiel v prospech žien, ktoré mali preukázali väčší
strach z používania hardvéru. Pri pohľade na výskumné
štúdie ako výsledok vo väčšine výskumov vychádza, že
dievčatá a ženy zaostávajú za požadovanými vedomosťami o IKT a schopnosťami, ktoré by mali dosahovať pri
práci s počítačmi. Vo väčšine krajín je participácia žien v
povolaniach, ktoré priamo súvisia s IKT a bohužiaľ trend
poklesu žien v týchto odvetviach je neustávajúci. Celkovo je možné povedať, že výskumné štúdie zamerané na
skúmanie postojov s ohľadom na gender poukazujú na
rozličné vnímanie IKT.
Ďalšou skúmanou premennou býva vek respondentov,
ale v porovnaní s genderom je počet štúdií zameraných
na vek menší. V starších štúdiách sa uvádza, že mladší
respondenti majú pozitívnejší vzťah k IKT v porovnaní
so staršími (Laguna & Babcock, 1997), v ďalšej štúdii
uvádza Bozionelos (2001) opak, teda starší študenti majú
pozitívnejšie postoje k IKT v porovnaní s mladšími. Spernjak & Sorgo (2009) však nenašli rozdiel medzi postojmi
študentov, ktorých vek sa pohyboval v rozmedzí 10 až
14 rokov.
Hlavným cieľom predkladaného príspevku bolo zistiť
postoje vysokoškolských študentov k IKT používaných v
prírodovedných predmetoch a takisto sa príspevok snaží
zodpovedať výskumnú otázku: Existuje rozdiel v používaní IKT medzi študentmi s ohľadom na gender, bydlisko
a ročník štúdia respondentov?
3 Metodika
Výskumnú vzorku tvorilo 316 vysokoškolských štu-
dentov navštevujúcich jednu univerzitu. Takmer všetci
študenti študovali učiteľskú dvojkombináciu predmetov,
z ktorých aspoň jeden bol prírodovedného zamerania
(biológia, chémia alebo geografia). Vek respondentov sa
pohyboval v rozmedzí 17 až 13 rokov (x = 20,44; SD =
1,45). Počet mužských zástupcov bol 100, zvyšok tvorili
ženy (n = 216). S ohľadom na bydlisko bolo 62 respondentov z dediny, 90 študentov bolo z mesta a zvyšok tvorili
študenti z veľkomesta (n = 164). Vo výskumnej vzorke boli
zastúpení študenti z troch ročníkov. Najväčšie zastúpenie
mali prváci (n = 128), počet druhákov bol 105 a tretiaci
tvorili najmenšiu časť výskumnej vzorky (n = 83). Súčasťou demografických položiek bola aj otázka, či sú študenti
vlastníkmi počítača, v čase priebehu výskumu boli všetci
študenti jeho vlastníkmi, tak táto položka nebola zahrnutá
do analýz.
Postoje študentov boli merané pomocou 5-stupňovej
škály Likertovho typu. Na zistenie postojov bol použitý
modifikovaný dotazník od autorov Kubiatko & Haláková
(2009), ktorý bol zameraný na skúmanie študentských
postojov k IKT v biológii. Položky boli upravené tak, že
pojem “biológia” bol nahradený pojmom “prírodovedné
predmety” v príslušnom tvare. Dotazník pozostával z 33
položiek, ktoré boli bodované od 1 (úplne nesúhlasím)
po 5 (úplne súhlasím). Položky boli ladené pozitívne aj
negatívne. Negatívne položky boli bodované v opačnom
poradí. Zistené skóre udávalo celkový postoj jednotlivca
k IKT. Nízke skóre reflektovalo negatívny postoj k IKT
a vysoké pozitívny postoj. Validita výskumného nástroja
bola zaistená prostredníctvom dvoch expertov zaoberajúcich sa problematikou IKT vo vzdelávaní. Títo experti
boli oslovení na zhodnotenie položiek, či sú relevantné k
cieľu výskumu. Na základe ich pripomienok boli položky
upravené. Prvá časť výskumného nástroja pozostávala
z demografických položiek: gender, vek respondentov,
ročník štúdia, vlastníctvo počítača a bydlisko (dedina,
mesto alebo veľkomesto). Hlavný rozdiel medzi mestom
a veľkomestom bol v tom, že za veľkomesto bolo považované sídlo s počtom obyvateľov väčším ako 100 tisíc.
Študenti participujúci na výskume boli ubezpečení, že
sa jedná o anonymný dotazník a neovplyvní ich prospech
v štúdiu. Dotazník bol administrovaný medzi študentov
náhodne, na vyplnenie nebol daný žiaden časový limit,
pričom samotné vyplnenie netrvalo dlhšie ako 15 minút.
Získané dáta boli analyzované pomocou faktorovej
analýzy s Varimax rotáciou, následne bolo vygenerovaných 5 faktorov resp. dimenzií: 1) Vplyv IKT na vyučovací
proces (7 položiek), 2) Vplyv IKT na človeka a prostredie
(4 položky), 3) Využívanie IKT vo vyučovaní (7 položiek),
4) Škola a IKT (3 položky), 5) IKT ako didaktická pomôcka (6 položiek). Týchto 5 faktorov súhrnne vysvetľovalo
39,23 % rozptylu, pričom najviac rozptylu bolo vysvetleného prvými dvoma faktormi (18,66 % a 7,00 %). Šesť
položiek s hodnotou faktorového skóre menšou ako 0,30
prípadne položky, ktoré sýtili viac ako dva faktory boli vylúčené z ďalších analýz (Anastasi, 1990). Následne bola
určená reliabilita dotazníka pomocou Cronbachovho alfa.
Reliabilita dotazníka bola vysoká (α = 0,72) a hodnoty
koeficientu pre jednotlivé dimenzie sa pohybovali v roz-
medzí 0,58 až 0,89, čo je považované za dostatočnú
hodnotu, aby sme mohli dotazník, prípadne jeho časť
označiť za reliabilnú (Nunnaly, 1978).
Na analýzu dát bola použitá analýza kovariancie (ANCOVA), kde vek slúžil ako kovariát, priemerné skóre, či
už za celý dotazník alebo za jednotlivé dimenzie ako závislá premenná a demografické položky (gender, bydlisko
a ročník štúdia) ako nezávislé premenné. Ďalej na zistenie
rozdielov medzi jednotlivými kategorickými premennými
bol použitý t-test a analýza rozptylu.
4 Výsledky
Celkové skóre zistené u študentov českých vysokých
škôl bolo 3,57 (SD = 0,42), čo indikuje relatívne pozitívne
postoje k využívaniu IKT vo vyučovaní prírodovedných
predmetov. Ďalej bolo zisťované, či existujú štatisticky
významné rozdiely vo výsledkoch s ohľadom na gender,
bydlisko a ročník štúdia. Ako štatistické metóda bola
použitá analýza kovariancie s vekom ako kovariátom.
Vplyv veku na výsledku preukázaný nebol. Štatisticky
významný rozdiel vo výsledkoch s ohľadom na jednotlivé kategorické premenné preukázaný nebol. Muži však
dosahovali vyššie skóre (x = 3,63; SD = 0,05) v porovnaní
so ženami (x = 3,55; SD = 0,04). Študenti s bydliskom
v meste dosahovali pozitívnejšie postoje (x = 3,67; SD
= 0,08) v porovnaní so študentmi žijúcimi vo veľkomeste
(x = 3,61; SD = 0,04) alebo vo vidieckom prostredí (x =
3,50; SD = 0,05). Poslucháči v druhom ročníku štúdia
dosiahli najvyššie skóre (x = 3,69; SD = 0,05). Najnižšie
skóre s ohľadom na ročník štúdia dosiahli prváci (x = 3,51;
SD = 0,04) a tretiaci dosiahli priemerné skóre 3,57 (SD
= 0,08).
Pri analýze jednotlivých dimenzií bol zistení štatisticky
významný rozdiel vo výsledkoch s ohľadom na gender
v dimenzii „Vplyv IKT na človeka a prostredie“. Muži dosahovali vyššie skóre v porovnaní so ženami. Muži dosahovali vyššie skóre v porovnané so ženami ešte v poslednej dimenzii nazvanej „IKT ako didaktické pomôcka“.
V dimenzii „Vplyv IKT na vyučovací proces“ dosiahli obe
skupiny u sledovanej kategorickej premennej identické
skóre. V ostatných dvoch dimenziách dosahovali vyššie
skóre ženy (graf 1).
Graf 1 Rozdiely v postojoch v sledovaných dimenziách
s ohľadom na gender (NS – nesignifikantný rozdiel; ***
p < 0,001).
9
Druháci dosahovali signifikantne významný rozdiel
v porovnaní s ostatnými skupinami u dvoch sledovaných
dimenzií „Vplyv IKT na vyučovací proces“ a „Škola a IKT“.
Vyššie, ale nesignifikantné skóre dosiahli ešte v dimenzii
„Využívanie IKT vo vyučovaní“ (graf 2).
s ohľadom na ročník štúdia (NS – nesignifikantný rozdiel;
** p < 0,01; *** p < 0,001).
Pri vyhodnocovaní kategorickej premennej bydlisko
respondentov bol zistený štatisticky významný rozdiel iba
v dimenzii „Využívanie IKT vo vyučovaní”, kde dosiahli
najvyššie skóre študenti z dediny. Títo boli úspešnejší
v dimenziách „Vplyv IKT na vyučovací proces“ a „Škola
a IKT“ (graf 3).
s ohľadom na bydlisko (NS – nesignifikantný rozdiel; **
p < 0,01).
5 Diskusia
V predkladanej štúdii bolo cieľom zistiť postoje budúcich učiteľov prírodovedných predmetov k informačným
a komunikačným technológiám. Okrem celkového skóre
bol zisťovaný rozdiel s ohľadom na vybrané kategorické
premenné ako gender, bydlisko, ročník štúdia. Vek respondentov slúžil ako kovariát. Použitím faktorovej analýzy boli položky dotazníka rozdistribuované do piatich
dimenzií: 1) Vplyv IKT na vyučovací proces, 2) Vplyv IKT
na človeka a prostredie, 3) Využívanie IKT vo vyučovaní,
4) Škola a IKT, 5) IKT ako didaktická pomôcka.
Skúmanie postojov vysokoškolských študentov k IKT
je dôležité a zároveň aj nutné z dôvodu zistenia aktuálneho stavu vnímania IKT. Týmto spôsobom môže byť
takisto odhalená aj úroveň používania IKT vo vyučovaní. Vo výskumnom šetrení bol zistený pozitívny postoj
10
Slovenský učiteľ
českých vysokoškolských študentov k IKT používaných
v prírodovedných predmetoch. Podobné zistenie uvádza
aj Simsek (2008), ktorý vo svojom výskume zistil aj akceptáciu takmer všetkých študentov s používaním IKT pri
vyučovaní a učení. Kubiatko & Haláková (2009) podobne
uvádzajú pozitívny postoj študentov gymnázií k IKT používaných vo vyučovaní biológie.
Pri vyhodnocovaní jednotlivých kategorických premenných bolo zistené, že muži mali pozitívnejší postoj k IKT
v porovnaní so ženami. Toto zistenie podporuje všeobecný pohľad, ktorý hovorí: „muži sú technicky viac zdatnejší
v porovnaní so ženami“, napriek celosvetovému úsiliu
o vyrovnanie kompetentnosti v práci s IKT žien a mužov. Podobné tvrdenia uvádza vo svojej práci napríklad
Cooper (2006), ktorý poukazuje na pretrvávajúci názor
verejnosti o väčšej zainteresovanosti mužov v používaní
počítačov. Negatívnejší postoj žien k IKT môže viesť aj
k menšej sebadôvere pri práci s technológiami. Poznanie, že ženy majú negatívny postoj k IKT a sú aj menej
ochotné ich používať pri pracovnej činnosti len podporuje
prevládajúci stereotyp, že počítače sú pre mužov a nie
pre ženy. Ako jedno z riešení na zvrátenie súčasného
trendu sa navrhuje odlišný proces socializácie žien, tak
aby sa necítili nepríjemne pri práci s počítačom, napríklad
absolvovaním rôznych kurzov, ktoré im umožnia prekonať bariéry pri práci s IKT. Prekonávať prekážky im môže
napomôcť aj neustále sa zvyšujúci počet IKT zariadení
v školách, ktoré prispievajú k nutnosti naučiť sa s nimi
pracovať a tým aj znižovať rozdiely v postojoch medzi
mužmi a ženami (Varank, 2007).
Ďalšou analyzovanou premennou bol ročník štúdia.
Študenti navštevujúci druhý ročník dosiahli najpozitívnejšie postoje v porovnaní so študentmi navštevujúcimi
prvý a tretí ročník. Prváci vyjadrili najmenej pozitívne
postoje k používaniu IKT. Pri analýze ročníkov štúdia je
nutné si uvedomiť, že sa nejedná o analýzu vplyvu veku.
Vek môže byť rozličný u študentov jednotlivých ročníkov,
rovnaký vek môže mať študent navštevujúci prvý ročník
a ten istý vek môže mať aj študent v poslednom ročníku
štúdia. Preto v našej práci bol vek ako kovariát a teda
výsledky boli očistené od jeho vplyvu. Výsledky výskumov
sú kontroverzné, niektoré tvrdia, že vzťah medzi postojom
k IKT a vekom neexistuje (Comber, Colley, Hargreaves &
Dorn, 1997) a iné zas tvrdia, že medzi vekom a postojmi
k IKT je významný vzťah (Handler, 1993).
Poslednou skúmanou premennou v štúdii bolo bydlisko respondentov. Študenti boli rozdelení do troch skupín
podľa miesta bydliska, na tých čo pochádzajú z dediny,
z mesta a z veľkomesta. Pri prehľadávaní databáz nebola nájdená žiadna práca, ktorá by sa zaoberala vplyvom
bydliska na postoje študentov k IKT. Výskumom bolo zistené, že študenti z mesta dosahovali najpozitívnejšie postoje v porovnaní s ostatnými dvoma skupina a študenti
z dediny dosahovali najmenej pozitívne skóre.
6 Záver
Určenie postojov študentov vysokých škôl k IKT používaných v prírodovedných predmetoch bolo prevedené na
základe štatistického vyhodnotenia. Respondenti nášho
výskumného šetrenia preukázali záujem o používanie
IKT vo výučbe prírodovedných predmetov, čo bolo zistené z ich odpovedí. Efektívne používanie IKT pri príprave
budúcich učiteľov môže vplývať pozitívnym spôsobom na
ich postoje k technológiám, čo môže mať za následok
ich vhodné používanie vo vyučovacom procese, čím sa
vytvorí špirála spätnej väzby.
CZECH UNIVERSITY STUDENTS’ ATTITUDES TOWARDS ICT USED IN SCIENCE EDUCATION
Abstract: This paper focuses on differences of attitudes
related to information and communication technologies
among Czech university students. Students’ attitudes
were evaluated summatively and with respect to gender,
grade, and residence. The sample consisted of a total of
316 university students. The data analysis included factor
analysis, ANCOVA, ANOVA, and t-test. The factor analysis yielded five dimensions: 1) Influence of ICT on teaching
process, 2) Influence of ICT on human body and environment, 3) Using of ICT in teaching, 4) School and ICT, 5)
ICT as didactic equipment. As a result, male students,
sophomores, and students living in town showed more positive attitudes in comparison to other respective groups.
Key words: attitudes, information and communication
technologies, questionnaire, science teaching, university
students
Literatúra
Bozionelos, N.: Computer anxiety: Relationship with
computer experience and prevalence. Computers in Human Behavior, vol. 17, no. 2, 2001, pp. 213-224.
Comber, , C., Colley, A., Hargreaves, D. J., Dorn,
L. The effects of age, gender and computer experience
upon computer attitudes. Educational Research, vol. 39,
no. 2, 1997, pp. 123-133
Cooper, J.: The digital divide: the special case of gender. Journal of Computer Assisted Learning, vol. 22, no.
5, 2006, pp. 320-334.
Cuckle, P., Clarke, S.: Mentoring student-teachers
in schools: views, practices and access to ICT. Journal
of Computer Assisted Learning, vol. 18, no. 3, 2002, pp.
330-340.
Dorup, J.: Experience and attitudes towards information technology among first year medical students in
Denmark: Longitudinal questionnaire survey. Journal of
Medical Internet Research, vol. 6, no. 1, 2004, 10p.
Fančovičová, J., Prokop, P.: Students’ attitudes toward computer use in Slovakia. Eurasia Journal of Mathematics, Science and Technology Education, vol. 4, no. 3,
2008, pp. 255-262.
Handler, M.G.: Preparing new teachers to use computer technology: perceptions and suggestions for teacher
educators. Computer Education, vol. 20, no.2, 1993, pp.
147-156.
Kaino, L. M.: Technology in learning: narrowing the gender gap? Eurasia Journal of Mathematics, Science and
Technology Education, vol. 4, no. 3, 2008, pp. 263-268.
Kubiatko, M., Haláková, Z.: Slovak high school students’ attitudes to ICT using in biology lesson. Computers
in Human Behavior, vol. 25, no. 3, 2009, pp. 743-748.
Laguna, K., Babcock, R. L.: Computer anxiety in young and older adults: Implications for human–computer
interactions in older populations. Computers in Human
Behavior, vol. 13, no. 3, 1997, pp. 317-326.
Nunnaly, J. Psychometric theory. McGraw-Hill: New
York, 1978.
Oppenheim, A. N. Questionnaire design, interviewing
and attitude measurement. London: Continuum International Publishing Group, New Edition, 1999.
Palaigeorgiou, G. E., Siozos, P. D., Konstantakis, N. I., Tsoukalas, I. A. A.: Computer attitude
scale for computer science freshmen and its educational
implications. Journal of Computer Assisted Learning, vol.
21, no. 5, 2005, pp. 330-342.
Simsek, S. C. S.: Students’ attitudes towards integration
of ICTs in a reading course: A case in Turkey. Computers
and Education, vol. 51, no.1, 2008, pp. 200-211.
Spernjak, A., Sorgo, A.: Comparison of Attitudinal
Differences with Three Different Styles of Biological Laboratory Exercises among Elementary School Students.
Didactica Slovenica-Pedagoska Obzorja, vol. 24, no. 3-4,
2009, pp. 68-86.
Teo, T.: Attitudes toward computers: A study of postsecondary students in Singapore. Interactive Learning
Environments, vol. 14, no. 1, 2006, pp. 17-24.
Tsitouridou, M., Vryzas, K.: Early childhood teachers‘ attitudes towards computer and information technology: The case of Greece. Information Technology in
Childhood Education Annual, vol. 1, 2003, pp. 187-207.
Varank, I.: Effectiveness of quantitative skills, qualitative skills, and gender in determining computer skills and
attitudes: a causal analysis. Clearing House: A Journal of
Educational Strategies, vol. 81, no. 2, 2007, pp. 71-80.
Yildirim, S.: Effects of an educational computing course
on pre-service and inservice teachers: A discussion and
analysis of attitudes and use. Journal of Research on
Computing in Education, vol. 32, no. 4, 2000, pp. 479-495.
Zhao, Y., Tan, H. S., Mishra, P.: Teaching and learning:
Whose computer is it? Journal of Adolescent & Adult Literacy, vol. 44, no. 4, 2004, pp. 348-354.
PaedDr. Milan Kubiatko, PhD.
Pedagogická fakulta MU
Institut výzkumu školního vzdělávání
Poříčí 31, 603 00 Brno, ČR
MOTIVÁCIA ŽIAKOV UČIŤ SA
PRÍRODOPIS – BIOLÓGIU NA
ZÁKLADNEJ ŠKOLE
Student`s learning motivation to science - biology
on primary school
Milan Veselský, Romana Hausnerová – SR
11
ISSN 1571-0068, Volume 8, Number 3
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MILAN KUBIATKO and KATERINA VLCKOVA
THE RELATIONSHIP BETWEEN ICT USE AND SCIENCE
KNOWLEDGE FOR CZECH STUDENTS: A SECONDARY
ANALYSIS OF PISA 2006
Received: 29 August 2009; Accepted: 22 January 2010
ABSTRACT. The 2006 Programme for International Student Assessment focussed on
students’ scientific competencies, measured their knowledge and provided questionnaires
focussed on different aspects of life. One aspect was students’ experience with
information and communication technology (ICT). A secondary analysis of variance of
the Czech Republic data (N=5,932 students) was conducted using the science knowledge
test score and ICT familiarity items. The science knowledge items explored different
thematic areas, such as evolution, mousepox, genetics and acid rain. The main result was
that students who were connected in some way with ICT achieved better scores on the
science knowledge test in comparison with students who were not. Furthermore,
students whose ICT activity was connected with the educational process achieved a
higher score in comparison with students whose ICT activity was not connected with
the educational process.
KEY WORDS: Czech Republic, ICT, information and communication technology,
large-scale data, PISA, science knowledge, students
INTRODUCTION
Information and communication technologies (ICT) can be considered a
key component of modern societies and lives. Nevertheless, the public
and academic discussion regarding new ICT and their influence on the
educational process and results is continuing. The question is often put
whether ICT can really support and improve learning and the quality of
instruction and, additionally, in which way, under which conditions and
for what it can be useful. The current research focusses on more
specialised questions regarding different aspects and conditions of using
ICT and educational results.
This study addresses these questions by analysing high-quality data
drawn from the Programme for International Student Assessment (PISA),
which in 2006 included an ICT familiarity questionnaire. We were
particularly focussed on finding differences in students’ scientific literacy
and the use of computers outlined in previous studies (Anderson, Lin,
Treagust, Ross & Yore, 2007; Yore, Pimm & Tuan, 2007).
International Journal of Science and Mathematics Education (2010) 8: 523Y543
# National Science Council, Taiwan (2010)
524
MILAN KUBIATKO AND KATERINA VLCKOVA
The OECD Programme for International Student Assessment
PISA is an internationally standardised triennial survey of the knowledge and
skills of 15-year-olds. It is the product of collaboration between participating
countries and economies through the Organisation for Economic
Co-operation and Development (OECD); it draws on leading international
expertise to develop valid comparisons across countries and cultures. The
Czech Republic has participated in PISA since its introduction in 2000. PISA
2006 was focussed on students’ scientific competencies—not merely on
whether students can reproduce what they have learned in science but also on
how well they can extrapolate from what they have learned and apply their
knowledge in new situations. PISA 2006 defines science competency as the
extent to which a student (a) possesses scientific knowledge and uses that
knowledge to identify questions, acquire new knowledge, explain scientific
phenomena and draw evidence-based conclusions about science-related
issues; (b) understands the characteristic features of science as a form of
human knowledge and enquiry; (c) shows awareness of how science and
technology shape our material, intellectual and cultural environments and (d)
engages in science-related issues and with the ideas of science, as a reflective
citizen (OECD, 2007).
The science items assessed students’ ability to perform scientific tasks in
a variety of situations, ranging from those that affect their personal lives to
wider issues for the community or the world. These tasks measured
students’ performance in relation both to their science competencies and to
their scientific knowledge. The main aim is to measure how well students
are prepared to meet the challenges of today’s knowledge societies. PISA
2006 introduced an ICT questionnaire to document use and activities. ICT
was considered as one of a vast number of variables influencing a student’s
performance.
ICT Opportunities, Learning and Instruction
Recently, ICT has rapidly acquired an important place in society (Wang,
2008) and is used increasingly as a learning tool in all forms and at all levels
of education (Demiraslan & Usluel, 2008). Students differ in their
experiences with and attitudes toward ICT. At home, not all children have
the same access to ICT, and they may use ICT resources available at home
differently than at school. Therefore, differences in ICT knowledge and
skills develop amongst students. Because of these differences, the increasing
role of ICT as a learning tool can cause problems for students with less
experience with technology or less affinity for ICT (Volman, Van Eck,
Heemsker & Kuiper, 2004).
ICT USE AND SCIENCE KNOWLEDGE: PISA 2006 (CZECH REPUBLIC)
525
ICT can enhance knowledge sharing by lowering temporal and spatial
barriers between knowledge workers and improving access to information
about knowledge (Sohail & Daud, 2009). The introduction of ICT in
compulsory schooling and related changes in the curriculum include a
greater focus on student activity and responsibility. At the same time, the
role of the teacher is expected to change (Jedeskog & Nissen, 2004).
Computers may be located in a computer laboratory, distributed
throughout the school, or students may use their own laptop computers.
ICT may be a subject in its own right or may be used across all areas of
the curriculum. How ICT is used in the school setting is important in
providing students with the skills to participate in a knowledge society
(Ainley, Banks & Fleming, 2002).
Contemporary settings are now favouring curricula that promote
competency and performance. Curricula are starting to emphasise
capabilities and to be concerned more with how the information is used
than what the information is about. The moves to competency-based and
performance-based curricula are well supported and encouraged by
emerging instructional technologies, which tend to require:
Access to a variety of information sources
Access to a variety of information forms and types
Student-centred learning settings based on information access and
inquiry
Learning environments focussed on problem-centred and inquiry-based
activities
Authentic settings and examples
Teachers as coaches and mentors rather than content experts
(Stephenson, 2001).
The growing use of ICT as an instructional medium is changing and
will likely continue to change many of the strategies employed by both
teachers and students in the learning process. Technology has the capacity to
promote and encourage the transformation of education from a teacherdirected enterprise into one that supports more student-centred models
(Robertson, 2005). Evidence of this today is manifested in the proliferation
of capability-, competency- and outcomes-focussed curricula; moves
towards problem-based learning; increased use of the Web as an information
source and Internet users being able to choose the experts from whom they
will learn. The use of ICT in educational settings acts in itself as a catalyst for
change in this domain. ICT by its very nature comprises tools that encourage
and support independent learning and knowledge construction. Students
using ICT become immersed in the process of learning; and as more and
526
more students use computers as information sources and cognitive tools
(Smeets, 2005), the influence of the technology on how they learn will
continue to increase.
When ICT was used in the curriculum, including in science, a majority
of students took greater responsibility for their own learning as a result
(Beauchamp & Parkinson, 2005). Reynolds, Treharne & Tripp (2003)
investigated the impact of ICT on students’ achievements in science
(amongst other subjects) and provided evidence that they spent longer
time on learning tasks.
The successful use of ICT can stimulate change in pedagogical practice—
although the question of whether this enhances student learning requires
further investigation. The pedagogical approach adopted in traditional
classes has been shown to have a major influence on students’ cognitive
achievements. The teacher’s competence and confidence in using ICT is an
important factor in the success of student learning, but it is not enough on its
own. An understanding of how ICT supports and enhances the learning task
may be even more vital. Early evidence suggested, for example, that students
struggled to make sense of their learning tasks when given insufficient
information and guidance from the teacher (Baggott la Velle, McFarlane &
Brawn, 2003).
When using ICT in science, students developed novel strategies for
problem solving by building models and creating new rules (Dede &
Palombo, 2004). The scaffolding effect built into the software has been
related to students’ ability to complete tasks of greater cognitive complexity
(Speier, Vessey & Valacich, 2003). Several studies suggest that using ICT
fosters in students the ability to develop higher order thinking skills
(Kennewell & Morgan, 2006; Lim & Tay, 2003; Reece, 2005) and to engage
in complex, causal reasoning (Dondlinger, 2007). Students have also been
shown to use more exploratory language to arrive at choices through
discussion (Shachaf, 2008).
Learners commonly experience difficulty in applying the appropriate
knowledge for solving a novel problem; therefore, a transformation strategy
is needed to supplement and/or transform their existing knowledge base
(Baggott la Velle et al., 2003). There are indications that the dynamic
representation of systems—and the ability to interact with these representations, which ICT enables—can assist children in developing an understanding that allows them to recognise the relevance of that experience in
novel situations (Lin, Lee & Chen, 2004; Wood, 2009). The cognitive tools
embedded in ICT and the pedagogical content knowledge involved provides
a powerful driver for the knowledge transformation that enables students to
understand a new problem (Baggott la Velle, Watson & Nichol, 2001).
527
ICT resources for education are part of that learning environment, and
their effects are expressed in a social context with a rich, multimedia and
multimodal learning environment (Preston, 2008). Teaching with these
ICT is said to offer more time for teacher intervention with all students
and interactions with students, greater sharing of class results and more
time for students to observe, think and analyse rather than be preoccupied
with gathering and processing data (Finlayson & Rogers, 2003). Research
has also identified the important influence of the teacher who decides how
the ICT resources are chosen (Castillo, 2006), how they are used in schools
and classrooms and how students interact with the materials (Hennessy,
Ruthven & Brindley, 2005). Therefore, the teacher’s input crucially affects
the impact of ICT use on student learning (Cox & Marshall, 2007).
Various government surveys have shown that teachers’ ICT use is usually
confined to very few types (e.g. using an interactive whiteboard for wholeclass demonstrations or using word-processing for creative writing).
Furthermore, regular uses reported by teachers may mean only a few
minutes of use by individual students or extensive use by some and much
less by others. This variation in use will clearly affect any impact that an ICT
resource may have on student learning (Cox & Abbott, 2004; Munro, 2002;
Wentling, Park & Peiper, 2006).
Previous research has also shown that different types of ICT resources
have different effects on learning, for example, the use of science
simulations to correct students’ misconceptions and alternative frameworks (Cox, 2000), the use of data-handling software to improve
students’ abilities to apply binary logic (Cox & Marshall, 2007) and the
use of word processing in English to reduce mistakes in punctuation and
grammar (Charness, Kelley, Bosman & Mottram, 2001).
It is clear from these and numerous other examples that ICT’s
contributions to student learning is highly dependent upon the type of ICT
resource and the subject in which it is being used. Any impact on learning
can be assessed by investigating the specific nature of the ICT-based tasks
and the types of concepts, skills and processes that it might affect. There is,
therefore, a dilemma for researchers between the need to investigate very
selected uses of ICT through an in-depth case-study approach or to conduct a
large-scale study that may produce results that are more generalisable but
will be limited because it does not have data in sufficient detail on the
specific uses made by each learner (Cox & Marshall, 2007).
Positive influence of ICT on the teaching of science in the school as
well as on consequent science literacy could be achieved by means of a
wide variety of opportunities. Students should have access to wide bodies
of data, such as real-time air pollution measurements and epidemiological
528
statistics or direct links to high-quality astronomical telescopes, and to a
wealth of information about science in the making. Access to secondary
resources and data, however, places greater emphasis on the need to
provide a science education that seeks proficiency as its ultimate goal and
to develop higher-order cognitive skills of evaluation and interpretation of
evidence, which requires critical assessment of the validity of theories and
explanations. Such an education would seek to support and develop
students’ scientific reasoning, critical reflections and analytical skills. The
established model of using ICT to support school science subjects
assumes an iterative, investigative approach as embedded in national
curricula as it incorporates simultaneous learning about scientific theory
and process (Osborne & Hennessy, 2003).
The use of ICT, particularly the tools for data handling and graphing, can
speed up and effect working processes, notably the more arduous and routine
components. This frees students from setting up experiments, taking
complex measurements, tabulating data, drawing graphs by hand and
executing multiple or difficult calculations. It enables rapid plotting of
diverse variables within a short period of time or collection and comparison
of large numbers of results (Ruthven, Hennessy & Brindley, 2004). An
interactive computer simulation can help students avoid getting bogged
down with the mechanics of simply setting up equipment. For example,
constructing and testing a circuit where the proliferation of wires involved
can make it difficult to see what is actually happening, and minor faults in
physical connections can pose a complete impediment (Hitch, 2000).
Using ICT also allows teachers and students to observe or interact with
simulations, animations or phenomena in novel ways that may be too
dangerous, complex or expensive for the school laboratory. The use of a
data logger can facilitate otherwise impossible demonstrations, such as
measuring energy transfer as a hot liquid cools. Digital video capture
offers an alternative to data logging; repeated and slow-motion playback
allows phenomena that are difficult for a whole class to view or events
otherwise too slow (e.g. growth of a plant) or fast (e.g. sound waves or
the behaviour of two different masses dropped from the same height) to
be captured. The Internet also offers some unique opportunities to
experience phenomena, such as a view of the Earth from a moving
satellite (Finlayson & Rogers, 2003; Osborne & Hennessy, 2003).
The Czech Republic was integrated into the “Benchmarking Access
and Use of ICT in European Schools” research programme in 2006, in
which data were obtained from head teachers and classroom teachers in
27 countries (Korte & Hüsing, 2007). The surveys sought information on
ICT equipment and the Internet in schools, their use in classrooms,
529
teachers’ attitudes to ICT use, results on access, competence and
motivation for using ICT in schools and ICT readiness of teachers. The
Czech Republic results give the number of computers per 100 pupils as 9.3
and the number of computers connected to the Internet per 100 pupils as
8.2. In the Czech Republic, 63% of schools have broadband Internet access
and 48% provide computers in classrooms (Korte & Hüsing, 2007). By this
time, these percentages might be higher as the numbers of people
connected to the Internet and of computers in schools increase every year.
METHODOLOGY
The aim of this study was to explore the relationships amongst students’
science achievement and their self-reported ICT access and engagement
in schools, homes and other settings. The secondary analysis was
designed to use data from the PISA 2006 Czech Republic knowledge
test and ICT questionnaire. Research questions were established in
relation to the aim of the study:
1. Are there any differences in knowledge scores between students who
used computers and those who did not?
have been using a computer for a long time and those who did not?
3. Are there any differences in knowledge scores between students
regarding the time spent using the computer at different places?
4. Are there any differences in knowledge scores between students
regarding frequency and type of computer use?
were good at the activities related to ICT and those who were not?
ICT Science Knowledge Test and Questionnaire
The items on the science knowledge test focussed on animate and
inanimate nature and concerned different thematic areas, such as
evolution, mousepox, genetic and acid rain. The test items and student
responses were in written and graphic form. Individual items were
weighted differently in the final score; for each question, students
obtained 0 points minimum and 3 points maximum. The knowledge test
was standardised at the national and international levels, and it showed
adequately high reliability. There were subquestions in each question. We
used an overall average score for each student in the study. The value of
530
every question varied between 0 and 3 points. The score from the
knowledge test, the dependent variable, was used in the statistical
evaluation and used to calculate descriptive statistics: means and standard
deviations. The sample size of students from the Czech Republic was
5,932, with 2,786 girls and 3,146 boys. The students were 15 years old
and attending the ninth year of elementary school (i.e. lower secondary
level, at the end of compulsory education) or the first year of upper
secondary vocational school or grammar school.
The ICT questionnaire was part of the student survey and was divided
into five areas with one question for each area, as follows:
1. Have you ever used a computer? This question was dichotomous
(yes–no).
2. How long have you been using computers? This question contains a
four-point frequency scale (less than 1 year–1 year or more–3 years or
more–5 years or more).
3. How often do you use a computer at the following places? This
question was related to the amount of time the computer was used at
home, at school or elsewhere and was measured on a five-point
frequency scale (almost every day–once or twice a week–a few times a
month–once a month or less–never).
4. How often do you use computers for the following reasons? This
question rated the frequency of computer use for 11 activities on a
five-point scale (almost every day–a few times each week–between
once a week and once a month–less than once a month–never).
5. How well can you do each of these tasks on a computer? The last
question asked students to rate their ability on a four-point scale (I can
do this very well by myself–I can do this with help from someone–I
know what this means but I cannot do it–I do not know what this
means).
Statistical Procedure
The score in the science knowledge test was defined as the dependent
variable. The responses on the ICT questionnaire were used as the
independent variable. The first two analyses did not address any
subquestions; therefore, responses to each question served as an independent
variable. The other analyses included subquestions; therefore, the responses
to each subquestion served as an independent variable. It means that every
subquestion was presented as individual. For example, question 3 was “Are
there any differences in knowledge scores between students regarding the
531
time spent using the computer at different places?” with three subquestions
of at home, at school and at other places. Each subquestion was evaluated
independently. The situation in questions 4 and 5 was similar. We
analysed the influence of independent variables on the knowledge scores.
One-way analyses of variance (ANOVAs; Statistica 8) were used to test
differences in science achievement for significance for specific item
responses on the ICT questionnaire. Because every question except
question 1 contained more than two options, it was necessary to use a post
hoc pair-wise comparison to obtain better and more detailed explanation
of the results. The nonresponse rate varied between 0.1% and 3% for each
ICT item; therefore, we decided to exclude data sets containing items
without responses to avoid potential bias.
RESULTS
The results are structured in five areas and correspond to the items of the
ICT questionnaire. Discussion and conclusions follow.
Question 1: Are there any differences in knowledge scores between students who used
computers and those who did not?
Student responses regarding computer usage indicated almost all
(96.83%) had used computers. These students scored significantly higher
on the mean achievement score than students who had not used computers
(F(2, 5,928)=14.93; p=0.001; η2 =0.07). The mean achievement score for
computer users was 1.12 with a standard deviation of 0.01; for nonusers, it
was 0.89 with a standard deviation of 0.05.
Question 2: Are there any differences in knowledge scores between students who have
been using a computer for a long time and those who did not?
Student responses regarding length of time of computer usage were
recorded on a four-point ordered frequency scale. The responses to the
question showed a relationship between science achievement and length
of computer use (Figure 1). Students who had used computers the longest
achieved the highest mean scores on the knowledge test whereas students
who had used computers for the shortest time achieved the lowest scores
(F(4, 5,926)=25.14; pG0.001; η2 =0.13). The possibility of less than
1 year was selected by 3.76% of the respondents (includes nonusers from
question 1), 1 year or more by 12.26%, 3 years or more by 26.97% and
5 years or more by 53.62%. Post hoc Tukey’s honestly significant
532
Figure 1. Relation between mean knowledge test score and length of computer use
difference test revealed statistically significant (pG0.05) differences
between the response groups.
Question 3: Are there any differences in knowledge scores between students regarding the
time spent using the computer at different places?
Student responses regarding length of time of computer usage were
recorded on a five-point frequency scale. Table 1 provides F value, effect
size, mean score and percentage of respondents for each possible answer.
A statistically significant difference in knowledge score was found in using
a computer at home (F(5, 5,925)=23.05; pG0.001; η2 =0.14); students who
used a computer at home once or twice a week achieved the highest mean
score on the knowledge test whereas students who never used a computer
at home achieved the lowest mean score. A statistically significant
difference in knowledge score was also found in using a computer at
school (F(5, 5,925)=22.60; pG0.001; η2 =0.14); students who used a
computer almost every day achieved the highest mean score whereas
students who never used a computer achieved the lowest mean score on the
knowledge test. Students also differed in the knowledge score for computer
use at other places (F(5, 5,925)=14.38; pG0.001; η2 =0.11); most
successful were students who used a computer once a month or less
533
TABLE 1
ANOVA values for each reason, effect size, mean score of answer possibilities and
percentage score of each possibility
Places for
using
a computer
Fa
η2
a
%
b
%
c
%
d
%
e
%
School
23.05 0.14 1.13 70.43 1.16 11.61 1.11 4.35 1.07 1.90 1.02 6.30
Home
22.60 0.14 1.15 8.33 1.14 58.38 1.10 16.01 1.09 6.91 1.04 4.86
Other places 14.38 0.11 1.09 5.65 1.12 13.10 1.14 20.55 1.14 25.05 1.12 29.16
a almost every day, b once or twice a week, c a few times a month, d once a month or less, e never
a
The statistically significant difference of each F value is pG0.001
whereas the lowest mean score was recorded by students who used a
computer almost every day.
Question 4: Are there any differences in knowledge scores between students regarding
frequency and type of computer use?
Student responses regarding frequency and reasons for computer usage
were recorded on a five-point frequency. Table 2 lists 11 reasons for
computer use, with the F value, effect size, mean score and percentage of
respondents for each possible answer. The majority of responses were as
anticipated. Students who used ICT more often achieved better
knowledge scores. Only three cases (i.e. playing games, educational
software, creating programmes) achieved lower knowledge scores.
Question 5: Are there any differences in knowledge scores between students who were
good at the activities related to ICT and those who were not?
Student responses regarding proficiency on specific computer tasks
were recorded on a four-point competency scale for 16 tasks. Table 3
provides F value, effect size, mean score and percentage of respondents
for each possible answer. The F values are significant at pG0.001 for
proficiency on all reported tasks. Students who responded I can do this
very well by myself achieved the highest mean score on the knowledge
test in every task except the last one, where the most successful students
responded I know what this means, but I cannot do it. The lowest
knowledge score was recorded by students who responded in all tasks I
do not know what this means, except for the create database task, where
the lowest knowledge score was recorded by students who responded I
know what this means, but I cannot do it.
32.78
16.63
41.13
9.95
27.98
10.51
27.58
17.32
9.90
11.53
15.61
Fa
0.16
0.12
0.18
0.09
0.15
0.09
0.15
0.12
0.09
0.10
0.11
η2
1.15
1.10
1.13
1.13
1.11
1.12
1.12
1.10
1.11
1.09
1.13
a
35.17
29.86
13.12
32.16
6.57
24.17
10.45
5.14
34.66
7.55
48.72
%
1.14
1.13
1.16
1.13
1.15
1.14
1.15
1.13
1.13
1.12
1.14
b
33.13
21.46
31.36
21.11
16.55
18.09
17.45
12.14
21.11
12.22
21.07
%
1.12
1.16
1.14
1.13
1.15
1.14
1.15
1.15
1.15
1.11
1.13
c
17.30
17.03
32.10
16.15
28.94
16.67
25.29
22.30
14.95
16.74
11.60
%
a almost every day, b a few times each week, c between once a week and once a month, d less than once a month, e never
a
Browse the Internet for information
Play games
Write documents
Collaborate with a group or team
Use spreadsheets
Download software
Draw, paint or use graphics programmes
Use educational software
Download music
Write computer programmes
Communication (e-mail, chat)
Reasons for using a computer
1.06
1.16
1.07
1.13
1.14
1.14
1.13
1.15
1.15
1.12
1.12
d
6.25
14.48
12.58
11.97
23.95
13.10
24.83
26.06
9.07
18.34
6.19
%
1.00
1.09
1.01
1.08
1.05
1.09
1.05
1.09
1.11
1.14
1.05
e
4.30
13.13
7.03
14.36
19.76
23.36
17.77
30.02
16.20
40.86
8.43
%
534
ANOVA values for each reason, science knowledge, mean score of answer possibilities and percentage score of each possibility
TABLE 2
14.68
18.25
25.17
9.32
24.29
39.51
30.24
24.98
29.54
34.43
43.05
32.44
18.91
14.28
27.75
15.30
Fa
0.10
0.11
0.13
0.08
0.13
0.16
0.14
0.13
0.14
0.15
0.17
0.15
0.11
0.10
0.14
0.10
η2
1.13
1.14
1.14
1.14
1.14
1.14
1.13
1.13
1.14
1.14
1.15
1.15
1.13
1.13
1.13
1.13
a
87,96
53.22
64.51
25.51
78.02
85.38
91.35
80.82
77.38
82.10
63.82
61.88
76.96
46.61
87.96
29.97
%
1.07
1.11
1.10
1.13
1.10
1.06
1.01
1.10
1.08
1.06
1.10
1.10
1.11
1.12
1.06
1.12
b
4.40
24.73
19.84
34.20
11.09
6.51
2.88
10.76
11.82
8.65
21.81
19.99
12.10
32.45
4.87
36.51
%
1.12
1.11
1.08
1.11
1.07
0.99
0.99
1.05
1.07
1.01
1.05
1.07
1.10
1.12
1.03
1.13
c
2.92
15.63
9.91
20.94
5.56
2.87
1.06
3.34
4.96
3.12
7.25
9.31
5.50
14.19
2.21
27.11
%
0.94
1.01
0.98
1.12
0.96
0.93
0.88
0.91
0.97
1.01
0.98
1.03
0.96
1.03
0.89
1.00
d
a I can do this very well by myself, b I can do this with help from someone, c I know what this means but I cannot do it, d I do not know what this means
a
Chat online
Use software to find and get rid of computer viruses
Edit digital photographs or other graphic images
Create a database
Copy data to a CD
Move files from one place to another on a computer
Search the Internet for information
Download files or programmes from the Internet
Attach a file to an e-mail message
Use a word processor
Use a spreadsheet to plot a graph
Create a presentation
Download music from the Internet
Create a multimedia presentation
Write and send e-mails
Construct a web page
Tasks on a computer
ANOVA values for each task and the mean score of answer possibilities and the percentage score of each possibility
TABLE 3
0.81
2.36
1.47
15.16
1.47
1.26
0.59
1.05
1.70
2.02
2.80
4.62
1.47
2.51
0.72
2.04
%
535
536
DISCUSSION
This research investigated the relation between science knowledge and
ICT activities, experience, proficiency and type and place of use. The first
area focussed on respondents’ experience with computers. Students who
had used computers achieved a higher mean score on the knowledge test
in comparison with those who had not. This result is in keeping with
Barak (2007) and O’Neil, Wainess & Baker (2005) who found that ICT
has a positive effect on learning outcome. The positive relation between
using ICT and higher science-knowledge scores suggests that students
using ICT have access to more information from a variety of sources
related to science and human activity. Whilst textbooks might not be as
attractive to different groups of students for various reasons, the
interactive nature of the Internet holds their attention so that the content
is better absorbed. It must be noted that the very small group of nonusers
may include students with very low socioeconomic resources and less
than desirable school opportunities thereby biasing the results.
In the second question, students were asked how long they had used
computers. The highest scores on the knowledge test were recorded by
students who had used a computer for the longest time. This again
assumes that students found information with the assistance of ICT. The
Internet offers a relatively unlimited amount of information, which may
make it more acceptable to students than information in textbooks.
Educational software, too, seems to be of greater interest to students as
they can try out different illustrations, animations, experiments etc.
Volman & van Eck (2001) produced a similar finding in their study. It is
likely that length of use and proficiency are related; therefore, these
results may contain a critical proficiency effect that may explain the
nonlinear nature of the graphic display of achievement and length of use.
The third question was focussed on how often students use computers
at different places (home, school or other places). Students who used the
computer more frequently at home or school but not other places were the
most successful in the knowledge test. It can be assumed that at school
students use computers in relation to the educational process because
schools allow access only to those web pages connected with educational
goals, which may not be the case in other places and in some homes.
Because of these controls, students are not expected to be engaged in
activities that are not connected with the educational process, such as
downloading movies or music or playing online games. In our findings, it
was revealed that educational software and ICT applications have been
integrated into the science subjects and almost every school subject. This
537
is a change from some years ago when ICT was connected only with the
subject of informatics. Currently, a variety of educational CDs in students’
native language and English are available. Chambers & Davies (2001)
showed that information written in a language other than the native
language reduces work with ICT even though it helps the user to learn the
foreign language.
Educational ICT applications have a great impact on the learning
process through the combination of images, sounds, video and text. Using
ICT applications usually changes the teacher’s role in the learning
environment. ICT tools are often used as a means for students’ independent
work, which gives the teacher fewer opportunities to make supplementary
remarks and to stimulate reflection. In a face-to-face learning situation,
teachers have more opportunity to use material in a flexible manner, to add
or skip parts or to discuss information that is one-sided or biased. Vogel &
Klassen (2001) found that students are more quickly prepared in lessons in
which they use ICT. Encouraging students to take a more active part in the
learning process is one advantage of ICT. Furthermore, as Brewer (2003)
showed, using ICT in the learning process helps eliminate misconceptions.
The fourth question in the analysis focussed on how often students use
ICT for some activities. Some activities were connected with school, and
some were out-of-school activities. Students who used computers more
frequently for educational activities (e.g. spreadsheets, writing documents
etc.) achieved a higher knowledge score. One surprising result was that
students who wrote computer programmes almost every day achieved the
lowest mean science knowledge score. This activity was understood as
being connected with the educational process but, in this case, it might be
connected only with informatics. Therefore, these students may have less
interest in science subjects and the consequence might be their relatively
low score in the science-knowledge test. The worst score was recorded by
students who most frequently performed out-of-school-type activities (e.g.
playing games) that probably take up a considerable amount of time, which
could be used for the learning process. Therefore, we can agree with
Feinsinger (2001) that computer-based technologies can be powerful
pedagogical tools and can turn the passive recipient of information into
an active participant in the learning. However, we have to know how ICT
should be used because it is of little instructional value if we have not
clarified the goals for students’ learning before bringing them into
classroom.
In the final question, students indicated how well they could perform
certain activities connected with ICT, such as online chat and copying
data to a CD. In all activities, the most successful students were those
538
who thought that they could do these activities well. With one exception,
students who were good at constructing a web page achieved a worse
score. Our interpretation of this might be similar to that of the previous
case. Students interested in this activity may have less positive attitudes
toward science subjects, and the consequence of this might be their low
score in the science-knowledge test.
CONCLUSION
This secondary analysis of PISA 2006 data found a positive relationship
between the use of ICT and the science knowledge of 15-year-old
students in the Czech Republic—but this holds only when the use of ICT
is connected with the educational process independent of the place where
the ICT is used (i.e. whether at home, school or other places). Very
interesting positive relations were found regarding the amount of time
spent using a computer and science knowledge and regarding the
decreasing variance in the knowledge scores achieved by students, which
suggests the interpretation that ICT might have a supporting role in
diminishing differences in achievement amongst students.
These results support the application of ICT in lower secondary and
primary schools in the Czech Republic because of the strong and positive
relation between the amounts of time spent using a computer and the
development of a knowledge of science. The results support empirically
not only the use of computers at school but also the educational
effectiveness of their use at home when used for educational purposes.
We are in agreement with Hand, Prain & Yore (2001), who asserted that
increased use of computers focussed on specific educational reasons and
knowledge-building activities (whether at school, home or elsewhere)
could reduce the digital divide or gap. The results appear to provide
specific guidance as to which activities are promising and which are not.
The results also indicate the need for explicit instruction in the use of
some activities to improve science literacy, such as the need for critical
stance and critical thinking, databases, multiple representations and the
transformation between representations.
Suggestions for further research might include an analysis of the
relationship between the use of ICT and competencies in science,
attitudes to science and mathematical and reading competencies; this
could help further establish the perceived importance of ICT in education.
The relationship between science knowledge and ICT should focus in
further studies on different areas of scientific competency (e.g. reasoning,
539
analysing, application) and ICT. In addition, analysis in other countries
focussing on the relationship between ICT use and science knowledge can
be strongly recommended to support the generalisation of this relationship
across different educational and socioeconomic systems.
It appears that ICT has given us a powerful tool for the learning of
science subjects. Nevertheless, the results should be interpreted with
caution and a background explanation mediated through socioeconomic
capital and personal characteristics (e.g. motivation, aspiration level and
intelligence) taken into account. These aspects can be expected to play the
role of latent variables in the connection of ICT and science knowledge.
The relation between ICT use and socioeconomic status and the capital of
the family can be anticipated. In addition, PISA found differences
amongst schools in the Czech Republic in results in science, reading and
mathematics competency. Schools might differ in the access they give
students to ICT and in the amount and forms of ICT use in the
instructional process or outside the classroom related to other educational
activities. Nevertheless, the anticipated indirect role of all these variables
in the positive relation of ICT and science knowledge does not change the
importance of the main finding; that is, the use of ICT in the education
process is reasonable and meaningful, not least because it fosters the
acquisition of a knowledge of science.
John (2005) showed that, whilst ICT use influences the classroom
culture, the classroom culture also influences ICT use. Therefore, it is very
important to look at ICT applications not only from a static point of view
but also whilst it is in actual use. The learning environment as students
experience it comprises the ICT tool, the teacher and his or her teaching
and the interactions in the class. It is the teacher’s task to challenge the
students and to motivate and support them in the learning process and
knowledge construction. Baylor & Ritchie (2002) argued that the effective
use of computers in the classroom requires the teacher to use computer
management and instructional strategies that include supporting cultural and
individual learning preferences, flexibility in classroom seating, the mobility
and grouping of students and giving students options and autonomy.
The successful use of ICT in the teaching process is not an obvious
process. Teachers and students have to gain the confidence to use ICT and to
learn with its assistance. Results show that ICT has a positive potential for
science knowledge; therefore, it is important to continue to implement ICT
in the teaching process. Teachers should learn both how to use ICT and how
to teach effectively with ICT. This is not only a task for faculties and schools
that train teachers; the managements of schools are being challenged to offer
teachers different courses and better access to the Internet, where teachers
540
can share information relevant to education. Second, it is important to
understand that the incorporation of ICT in the teaching process needs
time. Exploring new technologies and how to use them effectively takes
more time than making minor adjustments to old lessons from year to
year. Bringing ICT to the classroom is a continuing investment. Third, the
use of ICT is generally helpful for making changes in classroom
organisation and teaching methods to retain students’ attention. Most
students prefer a mixed-mode learning environment, that is, a combination
of face-to-face interaction and online activities. Teachers and students can
build an effective co-learning partnership where they develop their ICT
knowledge and teaching expertise together.
ACKNOWLEDGEMENTS
This paper was supported by the Ministry of Education, Youth, and Sport
of the Czech Republic as part of the Centre for Basic Research on
Schooling project (LC06046) and KEGA 3/6235/08. The authors would
like to thank OECD and PISA for the freely available data used in this
analysis. We would like to thank Andrew Oakland and Sharyl Yore, who
kindly improved the English of the paper.
REFERENCES
Ainley, J., Banks, D., & Fleming, M. (2002). The influence of IT: Perspectives from five
Australian schools. Journal of Computer Assisted Learning, 18(4), 395–404.
Anderson, J. O., Lin, H.-S., Treagust, D. F., Ross, S. P., & Yore, L. D. (2007). Using
large-scale assessment datasets for research in science and mathematics education:
Programme for International Student Assessment (PISA). International Journal of
Science and Mathematics Education, 5(4), 591–614.
Baggott la Velle, L. M., Watson, K. E., & Nichol, J. D. (2001). OtherScope—the virtual
microscope—can the real learning experiences in practical science be simulated?
International Journal of Healthcare Technology and Management, 2(5/6), 539–556.
Baggott la Velle, L. M., McFarlane, A., & Brawn, R. (2003). Knowledge transformation
through ICT in science education: A case study in teacher-driven curriculum development.
Case study 1. British Journal of Educational Technology, 34(2), 183–199.
Barak, M. (2007). Transition from traditional to ICT-enhanced learning environments in
undergraduate chemistry courses. Computers & Education, 48(1), 30–43.
Baylor, A. L., & Ritchie, D. (2002). What factors facilitate teacher skill, teacher morale,
and perceived student learning in technology-using classrooms? Computers &
Education, 39(4), 395–414.
Beauchamp, G., & Parkinson, J. (2005). Beyond the ‘wow’ factor: Developing
interactivity with the interactive whiteboard. School Science Review, 86(316), 97–103.
541
Brewer, C. (2003). Computer in the classroom: How information technology can improve
conservation education. Conservation Biology, 17(3), 657–660.
Castillo, N. (2006). The implementation of information and communication technology
(ICT): An investigation into the level of use and integration of ICT by secondary school
teachers in Chile. Unpublished doctoral dissertation, King’s College London,
University of London, England.
Chambers, A., & Davies, G. (2001). ICT and language learning. A European perspective.
Lisse, The Netherlands: Swets & Zeitlinger.
Charness, N., Kelley, C. L., Bosman, E. A., & Mottram, M. (2001). Word processing
training and retraining: Effects of adult age, experience, and interface. Psychology and
Aging, 16(1), 110–127.
Cox, M. J. (2000). Information and communication technologies: Their role and value for
science education. In M. Monk & J. Osborne (Eds.), Good practice in science teaching—
what research has to say (pp. 142–158). Buckingham, England: Open University Press.
Cox, M. J., & Abbott, C. (2004). ICT and attainment: A review of the research literature.
London: British Educational Communications & Technology Agency, Department for
Education & Skills.
Cox, M. J., & Marshall, G. (2007). Effects of ICT: Do we know what we should know?
Education and Information Technologies Journal, 12(1), 59–70.
Dede, C., & Palombo, M. (2004). Virtual worlds for learning. Threshold (Summer), 16–20.
Demiraslan, Y., & Usluel, Y. K. (2008). ICT integration processes in Turkish schools:
Using activity theory to study issues and contradictions. Australasian Journal of
Educational Technology, 24(4), 458–474.
Dondlinger, M. J. (2007). Educational video game design: A review of the literature.
Journal of Applied Educational Technology, 4(1), 21–31.
Feinsinger, P. (2001). Designing field studies for biodiversity conservation. Washington,
DC: Island Press.
Finlayson, H., & Rogers, L. (2003). Does ICT in science really work in the classroom?
Part 1: The individual teacher experience. School Science Review, 84(309), 105–111.
Hand, B., Prain, V., & Yore, L. D. (2001). Sequential writing tasks’ influence on science
learning. In P. Tynjälä, L. Mason, & K. Lonka (Eds.), Writing as a learning tool:
Integrating theory and practice (pp. 105–129). Dordrecht, The Netherlands: Kluwer.
Hennessy, S., Ruthven, K., & Brindley, S. (2005). Teacher perspectives on integrating
ICT into subject teaching: Commitment, constraints, caution and change. Journal of
Curriculum Studies, 37(2), 155–192.
Hitch, M. (2000). Another dimension: Introducing ICT into science lessons is easy, time-saving
and enjoyable. Times Educational Supplement Curriculum Special, Spring, pp.18–19.
Jedeskog, G., & Nissen, J. (2004). ICT in the classroom: Is doing more important than
knowing? Education and Information Technologies, 9(1), 37–45.
John, P. (2005). The sacred and the profane: Subject sub-culture, pedagogical practice and
teachers’ perceptions of the classroom uses of ICT. Educational Review, 57(4), 471–
490.
Kennewell, S., & Morgan, A. (2006). Factors influencing learning through play in ICT
settings. Computers & Education, 46(3), 265–279.
Korte, W. B., & Hüsing, T. (2007). Benchmarking access and use of ICT in European
schools 2006: Results from head teacher and a classroom teacher surveys in 27
European countries. eLearning Papers, 2(1). Available from http://www.elearningeuropa.
info/files/media/media11563.pdf.
542
Lim, P. C., & Tay, L. Z. (2003). Information and communication technologies (ICT) in an
elementary school: Students’ engagement in higher order thinking. Journal of
Educational Multimedia and Hypermedia, 12(4), 425–451.
Lin, J. M. C., Lee, G. C., & Chen, H. Y. (2004). Exploring potential uses of ICT in
Chinese language arts instruction: Eight teachers’ perspectives. Computers &
Education, 42(2), 133–148.
Munro, R. (2002). Curriculum focused ICT—the critical resource. In D. M. Watson & J.
Andersen (Eds.), Networking the learner. Computers in education (pp. 179–188).
Boston: Kluwer.
O’Neil, H. F., Wainess, R., & Baker, E. L. (2005). Classification of learning
outcomes: Evidence from the computer games literature. The Curriculum Journal,
16(5), 455–474.
Organisation for Economic Co-operation and Development (2007). PISA 2006 science
competencies for tomorrow’s world (vol. 1: Analysis). Paris: Author.
Osborne, J., & Hennessy, S. (2003). Literature review in science education and the role of
ICT: Promise, problems and future directions. Futurelab Report No. 6. Available from
http://www.futurelab.org.uk/resources/documents/lit_reviews/Secondary_Science_
Review.pdf.
Preston, C. J. (2008). Braided learning: An emerging process observed in e-communities
of practice. International Journal of Web Based Communities, 4(2), 220–243.
Reece, G. J. (2005). Critical thinking and cognitive transfer: Implications for the development
of online information literacy tutorials. Research Strategies, 20(4), 482–493.
Reynolds, D., Treharne, D., & Tripp, H. (2003). ICT—the hopes and the reality. British
Journal of Educational Technology, 34(2), 151–167.
Robertson, S. L. (2005). Re-imagining and rescripting the future of education: Global
knowledge economy discourses and the challenge to education systems. Comparative
Education, 41(2), 151–170.
Ruthven, K., Hennessy, S., & Brindley, S. (2004). Teacher representations of the
successful use of computer-based tools and resources in teaching and learning
secondary English, Mathematics and Science. Teaching and Teacher Education, 20
(3), 259–275.
Shachaf, P. (2008). Cultural diversity and information and communication technology
impacts on global virtual teams: An exploratory study. Information & Management, 45
(2), 131–142.
Smeets, E. (2005). Does ICT contribute to powerful learning environments in primary
education? Computers & Education, 44(3), 343–355.
Sohail, M. S., & Daud, S. (2009). Knowledge sharing in higher education institutions:
Perspectives from Malaysia. VINE, 39(2), 125–142.
Speier, C., Vessey, I., & Valacich, J. S. (2003). The effects of interruptions, task
complexity, and information presentation on computer-supported decision-making
performance. Decision Sciences, 34(4), 771–797.
Stephenson, J. (Ed.). (2001). Learner-managed learning—an emerging pedagogy for
online learning. Teaching and learning online: Pedagogies for new technologies.
London: Kogan Page.
Vogel, D., & Klassen, J. (2001). Technology-supported learning: Status, issues and trends.
Journal of Computer Assisted Learning, 17(1), 104–114.
Volman, M., & Van Eck, E. (2001). Gender equity and information technology in
education: The second decade. Review of Educational Research, 71(4), 613–634.
543
Volman, M., Van Eck, E., Heemsker, I., & Kuiper, E. (2004). New technologies, new
differences. Gender and ethnic differences in pupils’ use of ICT in primary and
secondary education. Computers & Education, 45(1), 35–55.
Wang, T. J. (2008). Using ICT to enhance academic learning: Pedagogy and practice.
Educational Research and Review, 3(4), 101–106.
Wentling, T. L., Park, J., & Peiper, C. (2006). Learning gains associated with annotation
and communication software designed for large undergraduate classes. Journal of
Computer Assisted Learning, 23(1), 36–46.
Wood, D. (2009). Comments on “Learning with ICT: New perspectives on help seeking
and information searching.” Computers & Education, 53(4), 1048–1051.
Yore, L. D., Pimm, D., & Tuan, H.-L. (2007). The literacy component of mathematical
and scientific literacy. International Journal of Science and Mathematics Education, 5
(4), 559–589.
Educational Research Centre, Faculty of Education Masaryk University
Porici 31, 603 00, Brno, Czech Republic

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