The Effects of Web 2.0 Technologies Usage in Programming
Languages Lesson on the Academic Success, Interrogative Learning
Skills and Attitudes of Students towards Programming Languages
1. Introduction
Changes consistently occur in communities due to environmental factors. Within this process, communities
which do not comply with technological developments fall behind the developing world and cannot contribute to
their social development (Gokçearslan $ Bayir, 2011). Communities need to comply with technological
developments. It is easy for communities adapting to technological changes to find their places among developed
communities (Akkoyunlu et al., 2010). Particular developments are being experienced also in computational
fields as well as in other fields of technology. Occurring developments create a particular effect on communities’
lives. These developments also lead to changes in learning and teaching processes. Therefore the adaptation of
learning individuals to technological developments and their raising as individuals accessing information easily
with the help of technology are very important (Seferoglu, 2009). Technology has been being used in
educational environments since 19th century (Ritz $ Martin, 2013). Technology use in communities enable
students the opportunities of developing their skills with different activities and of creating products they
develop in different ways in order to increase their self-confidence. Moreover students have the chance to control
their products again with the help of technology (Autio et al., 2015). Positive attitudes of instructors as well as
students towards technology are important in terms of affecting students’ attitudes in positive way (Rohaan et al.,2012). Changes occur also in educational technologies according to the needs of communities (Goktas et al.,
2012). Erdogmus and Cagiltay (2009) define educational technologies as the usage of technology which emerges
with facts created by behavioral and physical sciences in educational environments in order to increase learning
environments’ productiveness. Within the time we live in, communities need to place enough importance on
education in order to lead a comfortable life and to not fall behind the world. Therefore individuals who catch on
technological improvements quicker and who are used to life-long learning should be raised (Akpinar et al.,
2005).
Today, individuals have the opportunity to realize their learning easily with interacting with themselves without
time and place limitations thanks to developments experienced in information and communication technologies
(Genc, 2010). In 2003, O’Reilly Media put forward a new term named “Web 2.0” which enables the easier
sharing of information on internet. All internet users take advantage of the opportunities of producing
information and developing the existing information with the help of Web 2.0 technologies. Also contents they
produce can be shared more easily by other users (Karaman, Yildirim, $ Kaban, 2008). Applications which
operate depending on internet show increase and with this increase, online learning concept has been occurred
(Yılmaz et al., 2005). Owing to online learning technologies, learning process is realized more rapidly and
productively with the opportunity of studying without time and place limitations of individuals. Additionally,
individuals have the opportunity to access information they desire without the help of anyone else (Mutlu et al.,
2005).
Clements and Gullo (1984) reached to the conclusion that computer programming increases problem solving
skills in their study related to computer programming. The fact that individuals are not interested in
programming languages causes their consideration of programming as boring and difficult (Genc $ Karakus,
2011). Several problems are faced in terms of the way of teaching in programming languages lessons,
programming languages to be taught and learners. One of the biggest problems which individuals newly learning
programming languages face is that programming languages have a complex structure (Catlak et al., 2015).
Computers have a big place in our lives now. Individuals have the opportunity to solve problems they face in
their daily lives with computer software products developed for this purpose. This reveals the importance of
computer software products. This reveals the conclusion that individuals receiving education in the field of
programming need to receive good quality education in order to develop the mentioned software products (Perry,
2009).
One of the instruction applications of constructivist learning is interrogative learning. Directing questions to
individuals in the learning process is important in terms of community’s possession of thinking individuals.
Primarily, questions are posed in learning based on interrogation. Afterwards, solutions to these questions are
produced. A result is reached by collecting relative information regarding the posed question. Lastly the
individuals analyse the process. In constructivist learning process, besides their interrogation skills, also research
skills of individuals develop and their interest in learning increase (Akinoglu, 2004). Interrogative learning
strategy is one of the most efficient learning strategies instructors use primarily (Cotton, 1989). Interrogative
learning is defined as a strategy type in which students learn information they gain depending only on instructors,
books, experiments and activities they perform in a way different than traditional methods in the literature. The
main goal of interrogative learning is the realization of learning in which students interrogate the information
they encounter from childhood to adulthood (Celik et al., 2005). Just as in cooperative learning methods,
students produce ideas by studying as groups also in interrogative learning method. They structure the new
information they gain by sharing the results they found as a result of idea generation process with other group
members in their minds (Taskoyan, 2008).
When analysing researches regarding Web 2.0 technologies:
Karaman, Yildirim and Kaban (2008) concluded in their studies named “Learning 2.0 Becomes Widespread:
Researches Regarding The Usage of Web 2.0 Applications in Education and Their Results” that Web 2.0
applications support learning, create an appropriate environment for group works and serve to develop high-level
thinking skills.
80 computer teacher candidates receiving education in the faculty of education of a state-owned university are
reached in a study by Korucu and Cakir (2014) named “Opinions of Computer Teacher Candidates Towards
Dynamic Web Technologies” and it is determined that a big majority of computer teacher candidates use
dynamic web technologies for communication, sharing and social purposes. Moreover, it is also determined in
the study that they do not use dynamic web technologies for educational purposes. Besides, they suggest that
teacher candidates should be taught regarding technology use and a lesson regarding how to use cooperative
When analysing studies regarding programming languages:
Ozyurt and Ozyurt (2015) have reached to 325 students receiving education in Computer Technologies
Department in their studies named “A Study Regarding the Determination of Attitudes of Computer
Programming Students towards Programming and Their Programming Self-Efficacies”. Data obtained in the
study were analysed with Mann Whitney U-test, Kruskal-Wallis test and Spearman Brown’s rank correlation
coefficient. According to the results obtained in the research, attitudes of students towards programming showed
up as positive and their programming self-efficacies are at medium-level. It is determined that there are
meaningful differences in terms of sexes, class levels and education types of students towards programming.
Besides, it is revealed that there is a positive and medium-level correlation between the attitudes and
self-efficacies of students towards programming. They suggest that activities which enable the development of
problem-solving and critical thinking skills should be performed in programming lessons in order to fertilize this
positive attitude even more.
Lau and Yuen (2008) reached to 217 secondary students between the ages of 14 and 19 in their studies named
“Exploring the Effects of Gender and Learning Styles on Computer Programming Performance: Implications for
Programming Pedagogy”. The effects of sex and learning styles on computer programming are sought in the
study. As a result of the study, they concluded that academic skills have a different effect on programming
knowledge and that sequent students show better performance in general when compared to randomly selected
students.
As a result of their studies named “The Beliefs of Electrical and Computer Engineering Students’ Regarding
Computer Programming”, Anastasiadou and Karakos (2011) suggested that positive attitude development of
students towards computer programming reflects positively on the professional lives of students and that factors
causing negations in students should be eliminated.
1.1 Goal and Importance of the Research
Computers play a big role in our lives now. Software products developed for computers are increasing day by
day. In order to show ourselves as a country in the field of software and to raise individuals capable of coding,
programming lessons given in universities should be productive. This study is considered to be able to contribute
to the productive delivery of programming lessons. Programming languages is a lesson in which applied works
can be more successful rather than theoretical studies. Additionally, the product which will be produced as a
result of group work will probably be more successful than that of individual work. This study is important
because students interact with each other more easily in their studies owing to Web 2.0 technologies. Due to
widespread usage of Web 2.0 technologies, it is estimated that these technologies can be easily integrated into
programming lessons and this study is important because it can create positive effect on students’ attitudes
towards the lesson.
It is obvious that academic success in programming lessons is low in general. As a result of this lowness,
decreases are experienced in motivation of the students. Therefore they usually fail in learning process (Jenkins,
2002). The goal of this study is to analyse the effect of Web 2.0 technologies usage in programming lesson on
students’ attitudes towards programming languages, academic success and interrogative learning skills.
Within this framework, research questions directing this study are as the following:
- Is there a meaningful difference between the “academic success” of students using cooperative learning
environment developed by Web 2.0 technologies and of those not using cooperative learning environments?
- Is there a meaningful difference between the “attitudes towards programming languages” of students using
cooperative learning environment developed by Web 2.0 technologies and of those not using cooperative
learning environments?
- Is there a meaningful difference between the “interrogative learning skills” of students using cooperative
learning environment developed by Web 2.0 technologies and of those not using cooperative learning
environments?
2. Conceptual Framework
2.1 Constructivist Learning
According to Constructivism, individuals are restructuring old knowledge with new knowledge. The
constructivist approach is not like traditional teaching methods, but an approach in which the student is active. Individual characteristics and learning environment are important in organizing information, which is structured
by individuals according to their own information and that individuals acquire information in different forms
(Ozmen, 2004). In the constructivist learning approach, learning by discovering and learning information is an
important part of individuals. Individuals need to make efforts to solve these problems in the face of problems
they encounter (Yasar, 1998).
2.2 Cooperative Learning
There are many definitions in the literature about cooperative learning. When these definitions are examined;
Collaborative learning is defined as the process by which individuals with different abilities, genders and
abilities are grouped in the direction of a determined common goal, and by continuing to work cooperatively in
these groups (Holm et al., 1987).
2.3 Web 2.0
It is a second generation web-based web services announced by O’Reilly Media in 2004, such as social
networking sites, virtual webmasters, and tools for online communication. Web 2.0 is defined as the new
generation of new technologies that meet the needs of individuals as well as their needs on the web (Sendag,
2008). Web 2.0 technologies include Youtube, Delicious, MySpace, Facebook, Second Life, Library Thing,
Ning, Flickr, Twitter, Meebo, etc. (Peltier-Davis, 2009).
2.4 Delphi Programming Language
It is based on the built-in Pascal programming language (Akpinar, 2008). It is a completely visual programming
language. Because of the widespread use of Pascal training, many students prefer the Delphi programming
language (Alabay, 2001).
3. method
3.1 Research Group
The work group chosen from the population for this study consists of N=75 computer teacher candidates in total
from two branches (2B, experimental group-N=40 and 2A, control group-N=35) receiving education in the 2nd
grade of Computer and Instructional Technologies Teaching Department of Faculty of Ahmet Kelesoglu,
Necmettin Erbakan University in 2015-2016 academic year. Table 1 demonstrates the sex status of the work
group.
Table 1. Sex distribution of work group
Sex |
Experimental Group |
Control Group |
Experimental & Control Group |
f |
% |
f |
% |
f |
% |
Male |
22 |
55,0 |
19 |
54,3 |
41 |
54,7 |
Female |
18 |
45,0 |
16 |
45,7 |
34 |
45,3 |
Total |
40 |
100,0 |
35 |
100,0 |
75 |
100,0 |
3.2 Research Model
Quantitative research model is adopted in this study as research model and “Pre-test-Post-test Control Group
Quasi-Experimental Design Model” is used (Campbell & Stanley, 1966). In studies where pre-test-post-test
control group experimental design is used; academic works are applied with the measurement of the
experimental subject in terms of the dependent variable both before and after the research application. Besides,
in cases where all variables can’t be controlled (Cohen et al., 2013) and particularly in studies performed in
education technology field, it is the most frequently used design by researchers (Kılıc-Cakmak et al., 2013).
Participants are divided into two groups as experimental and control group in the research (Karasar, 1999).
These groups are formed randomly. The effect of the experimental operation on different variables is analysed
by applying data collection tools to both groups before and after the application. In other words, measurements
are realized in both groups in the same way before and after the experiment (Buyukozturk et al., 2012).
The independent variables of the research are; learning method supported by face to face and cooperative
learning method supported by face to face and with Web 2.0 technologies. The dependent variables of the research are: academic success, attitude towards programming languages and interrogative learning skill.
Experimental design used in this research is shown on Table 2.
Table 2. Quasi-experimental design table regarding the research model
Groups |
Pre-test |
Method |
Post-test |
GD |
O1 |
XİÖ |
O2 |
GK |
O2 |
XYYÖ |
O2 |
GD=Experimental group
GK=Control group
XİÖ=Learning method supported by Web 2.0 technologies
XYYÖ=Face to face learning method
O1=Experimental and Control group pre-test application
O2=Experimental and Control group post-test application
3.3 Data Collection Tools
“Academic Success Test” developed by researcher in order to determine academic success of students, “Attitude
Towards Programming Languages Scale” which is translated into Turkish by Durak (2013) and “Interrogative
Skills Scale” developed by Aldan, Kandemir and Saracoglu (2013) are used as data collection tools in the study.
A table of specifications related to achievements is prepared while preparing Academic Success Test and each
achievement consists at least of 2 questions. “Attitude towards Programming Languages Scale” is developed as
“Attitude towards Mathematics Scale” by Tapia and Marsh in 2014. Cronbach Alfa credibility coefficient of the
scale is found as 0,97. As a further stage, Durak (2013) translated the scale which is adapted towards
Programming Languages into Turkish. Durak (2013) evaluated the scale in terms of language and meaning unity
in the direction of Turkish and foreign language experts’ opinions. The Turkish form of the scale is completed in
the direction of received opinions by performing the necessary arrangements. As its current situation, the scale is
named as “Attitude towards Programming Languages Scale”. The scale consists of 4 factors, 40 articles and 5
point likert type in total. The Cronbach Alfa credibility coefficient of the scale is found as 0,93. “Interrogative
Skills Scale” is developed by Aldan, Karademir and Saracoglu in 2013. Interrogative Skills Scale consists of 3
factors, 14 articles and 5 point likert type, 3 factor structure is obtained and each factor is named respectively as
“Knowledge Acquisition”, “Controlling Knowledge” and Self-confidence” in the accordance with theoretical
framework. Cronbach-alpha value related to each factor in the scale and to the entirety of the scale is calculated.
Cronbach-alpha credibility coefficients are; .76 for “Knowledge Acquisition”, .66 for “Controlling
Knowledge”, .82 for “Self-confidence” and .82 for the entirety of the scale.
3.4 Analysis of Data
SPSS 21 (Statistical Package for Social Sciences) version program is used for the analysis of data obtained
during the research. T-test for related samples is used for the comparison of data obtained from pre-test applied
to students before the research and from post-test applied to students after the research. T-test for unrelated
samples can be used for testing whether the difference between two unrelated sample averages is meaningful or
not (Buyukozturk, 2011).
4. Findings and Interpretations
4.1 Findings Regarding Academic Success
4.1.1 Research Question 1
Is there a meaningful difference between the “academic success” of students using cooperative learning
environment developed by Web 2.0 technologies and of those not using cooperative learning environments?
4.1.1.1 Experimental Group Pre-Test-Post-Test Comparison (Paired T Test)
Comparison results of pre-tests and post-tests realized to determine the academic development status of
experimental group students at the end of application are shown in Table 3.
Experimental Group |
Test |
N |
|
Ss |
Sd |
t |
P |
Pre-test |
40 |
59,05 |
15,09 |
39 |
24,733 |
.000 |
Post-test |
40 |
85,87 |
10,10 |
*p<0.05.
A difference is observed between the pre-test grades and post-test grades of experimental group (pre-test average
is =59,05; post-test average is =85,87) statistically for *p<.05 relevance level (p<0.05). It is determined that
experimental group students increased their academic success as a result of cooperative application supported by
Web 2.0 technologies (Table 3).
4.1.1.2 Control Group Pre-Test-Post-Test Comparison (Paired T Test)
Comparison results of pre-tests and post-tests realized to determine the academic development status of control
group students at the end of application are shown in Table 4.
Table 4. Comparison results of pre-test-post-test of control group
Control Group |
Test |
N |
|
Ss |
Sd |
t |
P |
Pre-test |
35 |
55,22 |
14,77 |
34 |
22,108 |
.000 |
Post-test |
35 |
78,48 |
10,93 |
*p<0.05.
A difference is observed between the pre-test grades and post-test grades of control group (pre-test average is
=55,22; post-test average is =78,48) statistically for *p<.05 relevance level (p<0.05). It is determined that
there is a meaningful difference in their academic success as a result of application (Table 4).
4.1.1.3 Experimental-Control Group Post-Tests Comparison (Independent T Test)
When compared the “Academic Success” of students used cooperative learning environment (experimental
group) and of students who didn’t used cooperative learning environment (control group), the results are shown
on Table 5.
Table 5. Inter-groups (experimental and control) post-test comparison (t-test) results
Groups |
N |
|
S |
Sd |
t |
P |
Post-test |
Experimental Group |
40 |
85,87 |
10,10 |
73 |
3,040 |
.003 |
Control Group |
35 |
78,487 |
10,93 |
*p<0.05.
The result is .00<.05 thus is meaningful for *p<.05 relevance level in post-tests performed on experimental and
control groups after application. It is determined that post-test grades of experimental group are higher than those
of control group in post-tests performed (experimental group post-test average is =85,87; control group
post-test average is =78,487) (Table 5). This result demonstrates that the realized application is in favour of
the experimental group. Besides, eta-squared value is calculated in order to determine the magnitude of the effect
of cooperative learning environment designed with Web 2.0 technologies on academic success. Effect magnitude
values are calculated as η2=.112. In these circumstances, when considering the effect magnitude value
(η2=0.112), it can be stated that cooperative learning environment designed by Web 2.0 technologies has a
“broad” effect magnitude on academic success.
4.2 Findings Regarding the Attitude towards Programming Languages
4.2.1 Research Question 2
Is there a meaningful difference between the “attitudes towards programming languages” of students using
cooperative learning environment developed by Web 2.0 technologies and of those not using cooperative
learning environments?
4.2.1.1 Experimental-Control Group Post-Tests Comparison (Independent T-Test)
When compared the “Attitudes Towards Programming languages” of students used cooperative learning
environment developed by Web 2.0 technologies (experimental group) and of students who didn’t used
cooperative learning environment (control group), the results are shown on Table 6.
Table 6. Inter-groups post-test comparison results
Groups |
N |
|
S |
Sd |
t |
P |
Post-test |
Experimental Group |
40 |
150,10 |
18,53 |
73 |
3,040 |
.000 |
Control Group |
35 |
134,42 |
14,95 |
*p<0.05.
The result is .00<.05 thus is meaningful for *p<.05 relevance level in post-tests performed on experimental and
control groups after application. It is determined that post-test grades of experimental group are higher than those
of control group in post-tests performed (experimental group post-test average is =150,10; control group
posttest average is =134,42) (Table 6). This result demonstrates that the realized application is in favour of the
experimental group. Besides, eta-squared value is calculated in order to determine the magnitude of the effect of
cooperative learning environment designed with Web 2.0 technologies on attitudes towards programming
languages. Effect magnitude values are calculated as η2=.179. In these circumstances, when considering the
effect magnitude value (η2=0.179), it can be stated that cooperative learning environment designed by Web 2.0
technologies has a “broad” effect magnitude on attitudes towards programming languages.
4.3 Findings Regarding Interrogative Learning Skills
4.3.1 Research Question 3
Is there a meaningful difference between the “interrogative learning skills” of students using cooperative
learning environment developed by Web 2.0 technologies and of those not using cooperative learning
environments?
4.3.1.1 Experimental-Control Group Post-Tests Comparison (Independent T-Test)
When compared the “Interrogative learning skills” of students used cooperative learning environment developed
by Web 2.0 technologies (experimental group) and of students who didn’t used cooperative learning
environment (control group), the results are shown on Table 7.
Table 7. Inter-groups post-test comparison results
Groups |
N |
|
S |
Sd |
t |
P |
Post-test |
Experimental Group |
40 |
39,40 |
14,68 |
73 |
2,638 |
.010 |
Control Group |
35 |
30,77 |
13,46 |
*p<0.05.
The result is .00 <.05 thus is meaningful for *p<.05 relevance level in post-tests performed on experimental and
control groups after application. It is determined that post-test grades of experimental group are higher than those
of control group in post-tests performed (experimental group post-test average is =39,40; control group
posttest average is =30,77) (Table 7). This result demonstrates that the realized application is in favour of the
experimental group. Besides, eta-squared value is calculated in order to determine the magnitude of the effect of
cooperative learning environment designed with Web 2.0 technologies on interrogative learning skills. Effect magnitude values are calculated as η2=.087. In these circumstances, when considering the effect magnitude
value (η2=0.087), it can be stated that cooperative learning environment designed by Web 2.0 technologies has a
“medium” effect magnitude on interrogative learning skills.
5. Discussion and Conclusion
This study aims the easy and efficient understanding of programming languages by students and the provision of
increase of its permanence with new methods rather than traditional methods. In accordance with this goal,
control group students are requested to perform programming languages lesson with traditional methods for 1
semester and experimental group students are requested to perform programming languages lesson with new
technologies for 1 semester and to complete a project they determine in groups by using new technologies.
Web 2.0 technologies play an efficient role in the process of information accession (Kitsantas et al., 2016). It is
observed that Web 2.0 technologies earn cooperative working habits, increase the quality of learning, earn
high-level thinking skills, help constructivist learning, provide positive effect on individual development and
provide individuals to take responsibilities in educational environments (Karaman et al., 2008). Within this
context, a difference is observed between the pre-test grades and post-test grades of experimental group (pre-test
average is =59,05; post-test average is =85,87) statistically for *p<.05 relevance level (p<0.05) as a result of
comparison of pre-tests and post-tests performed in order to determine the effect of Web 2.0 technologies on
academic success. It is determined that experimental group students increased their academic success as a result
of cooperative application supported by Web 2.0 technologies. Ekici and Kiyici (2012) also observed that
academic success of students using Web 2.0 technologies is higher than those of students receiving traditional
education. It is stated that the quality of education can be increased by integrating Web 2.0 technologies into
learning processes of students (Karaman, Ekici, & Akgun, 2011). There is a positive correlation between social
networks within the Web 2.0 technologies and face-to-face communication (Jacobsen & Forste, 2011). Usage of
information and communication technologies in educational environments contributes positively to increasing
educational efficiency and to constructivist learning (Venkateshvd, 2016). AlJeraisy, Mohammad, Fayyoumi and
Alrashideh (2015) state that academic success of students increased and students react to these technologies
positively as a result of Web 2.0 technologies usage in educational environments. In line with this, a difference is
observed between the pre-test grades and post-test grades of control group (pre-test average is =55,22;
post-test average is =78,48) statistically for *p<.05 relevance level (p<0.05) as a result of comparison of
pre-tests and post-tests performed in order to determine the status of academic success of control group students.
It is determined that there is a meaningful difference in their academic success as a result of application.
When compared the “Academic Success” of students used cooperative learning environment (experimental
group) and of students who didn’t used cooperative learning environment (control group), the result is .00<.05
thus is meaningful for *p<.05 relevance level in post-tests performed on experimental and control groups after
application. It is determined that post-test grades of experimental group are higher than those of control group in
post-tests performed. This result demonstrates that the realized application is in favour of the experimental group.
Besides, eta-squared value is calculated in order to determine the magnitude of the effect of cooperative learning
environment designed with Web 2.0 technologies on academic success. Effect magnitude values are calculated
as η2=.112. In these circumstances, when considering the effect magnitude value (η2=0.112), it can be stated
that cooperative learning environment designed by Web 2.0 technologies has a “broad” effect magnitude on
academic success.
Several problems are faced in terms of the way of teaching in programming languages lessons, programming
languages to be taught and learners. One of the biggest problems which individuals newly learning programming
languages face is that programming languages have a complex structure (Catlak et al., 2015). When compared
the “Attitudes Towards Programming languages” of students used cooperative learning environment developed
by Web 2.0 technologies (experimental group) and of students who didn’t used cooperative learning
environment (control group), the result is .00<.05 thus is meaningful for *p<.05 relevance level in post-tests
performed on experimental and control groups after application. It is determined that post-test grades of
experimental group are higher than those of control group in post-tests performed. This result demonstrates that
the realized application is in favour of the experimental group. Besides, eta-squared value is calculated in order
to determine the magnitude of the effect of cooperative learning environment designed with Web 2.0
technologies on attitudes towards programming languages. Effect magnitude values are calculated as η2=.179. In
these circumstances, when considering the effect magnitude value (η2=0.179), it can be stated that cooperative
learning environment designed by Web 2.0 technologies has a “broad” effect magnitude on attitudes towards
programming languages. There are a number of applications which are able to facilitate this process and to maximize the learning in programming education. With these applications, individuals are able to comprehend
how to write software more easily and to determine mistakes they do (Kert & Ugras, 2009).
In accordance with constructivist approach, the minds of individuals in educational environments are defined as
empty plates and this provides individuals learning according to their lives. Ausbel argues that what is important
in educational environments is that the learning should be meaningful (Ozmen, 2004). Interrogative learning is
defined as a strategy type in which students learn information they gain depending only on instructors, books,
experiments and activities they perform in a way different than traditional methods. The main goal of
interrogative learning is the realization of learning in which students interrogate the information they encounter
from childhood to adulthood (Celik et al., 2005). When compared the “interrogative learning skills” of students
used cooperative learning environment developed by Web 2.0 technologies (experimental group) and of students
who didn’t used cooperative learning environment (control group), as the result of the research, the realized
application is in favour of the experimental group. Besides, eta-squared value is calculated in order to determine
the magnitude of the effect of cooperative learning environment designed with Web 2.0 technologies on
interrogative learning skills. Effect magnitude values are calculated as η2=.087. In these circumstances, when
considering the effect magnitude value (η2=0.087), it can be stated that cooperative learning environment
designed by Web 2.0 technologies has a “medium” effect magnitude on interrogative learning skills
It is obvious in the conclusion of the research that the usage of Web 2.0 technologies in programming languages
lesson contributes to a more efficient learning of programming languages by students and to the learning of
programming knowledge permanently and meaningfully by students. Moreover, the usage of Web 2.0
technologies in educational environments increases the quality of the education (Tuzun, 2007).
References
Akinoglu, O. (2004). Constructivist learning and geography teaching. Marmara Geographical Review, 10,73-94.
Akkoyunlu, B., Soylu, M. Y., & Caglar, M. (2010). A study on developing “digital empowerment scale” for university students. Hacettepe University Journal of Education, 39, 10-19.
Akpinar, A. G. E., Aktamis, A. G. H., & Ergin, O. (2005). Students’ opinions regarding the use of educational technology in science lessons. The Turkish Online Journal of Educational Technology, 4(1), 93-100.
Alabay, M. N. (2001). Delphi’ye Giriş. Ankara: Gazi Academic Publishing.
AlJeraisy, M. N., Mohammad, H., Fayyoumi, A., & Alrashideh, W. (2015). Web 2.0 in education: The impact of discussion board on student performance and satisfaction. TOJET: The Turkish Online Journal of Educational Technology, 14(2), 247-259.
Anastasiadou, S. D., & Karakos, A. S. (2011). The beliefs of electrical and computer engineering students’ regarding computer programming. International Journal of Technology, Knowledge & Society, 7(1), 37-51. https://doi.org/10.18848/1832-3669/CGP/v07i01/56170
Autio, O., Soobik, M., Thorsteinsson, G., & Olafsson, B. (2015). The development of craft and technology education curriculums and students’ attitudes towards technology in Finland, Estonia and Iceland. International Journal of Contemporary Educational Research, 2(1), 22-34.
Buyukozturk, S. (2011). Sosyal Bilimler İçin Veri Analizi El Kitabı. Ankara: Pegem Academy Publishing.
Catlak, S., Tekdal, M., & Baz, F. T. (2015). The status of teaching programming with scratch: A document review work. Journal of Instructional Technologies & Teacher Education, 4(3), 13-25.
Celik, S., Senocak, E., Bayrakceken, S., Taskesenligil, Y., & Doymus, K. (2005). A review study on active learning strategies. Ataturk University Journal of Kazım Karabekir Education Faculty, 11(1), 155-185.
Clements, D. H., & Gullo, D. F. (1984). Effects of computer programming on young children’s cognition. Journal of Educational Psychology, 76(6), 1051-1058. https://doi.org/10.1037/0022-0663.76.6.1051
Cotton, K. (1989). Classroom questioning Close-up No. 5. Portland, OR: Northwest Regional Educational
Laboratory.
Durak, G. (2013). The online teaching of programming languages: Examining learner’s attitudes, satisfaction and success (Published PhD thesis). Anadolu University Graduate School of Social Sciences, Eskisehir,Turkey.
Ekici, M., & Kiyici, M. (2012). Using social networks in educational context. Usak University Journal of Social Sciences, 5(2), 156-167.
Erdogmus, F. U., & Cagiltay, K. (2009, February). General trends in master and doctoral dissertations in the field of educational technology in Turkey. XI. Academic Computing Conferences, Sanliurfa. Retrieved from https://goo.gl/2WDP9B
Genc, Z., & Karakus, S. (2011, September). Learning through design: Using scratch in instructional computer games design. In 5th International Computer & Instructional Technologies Symposium. Elazig. Retrieved from http://dspace.beu.edu.tr:8080/xmlui/handle/123456789/451
Genç, Z. (2010, February). Use of web 2.0 advancements in education: A case study of facebook in education. Academic Computing Conferences, Muğla. Retrieved from https://goo.gl/gAZVlz
Gokcearslan, S., & Bayir, E. A. (2011, April). Examination of numerical competence levels of teacher candidates. In 2nd International Conference on New Trends in Education and Their Implications. Antalya. Retrieved from http://www.iconte.org/FileUpload/ks59689/File/200.pdf
Goktas, Y., Kucuk, S., Aydemir, M., Telli, E., Arpacık, O., Yildirim, G., & Reisoglu, I. (2012). Educational technology research trends in turkey: A content analysis of the 2000-2009 decade. Educational Sciences: Theory & Practice, 12(1), 177-199.
Holm, A., Schultz, D., Winget, P., & Wurzbach, L. (1987). Cooperative Activities for the Home: Parents Working with Teachers to Support Cooperative Learning. Califomia State Department of Education,
Sacramento.
Jacobsen, W. C., & Forste, R. (2011). The wired generation: Academic and social outcomes of electronic media use among university students. Cyberpsychology, Behavior, and Social Networking, 14(5), 275-280. https://doi.org/10.1089/cyber.2010.0135
Karademir, Ç. A., & Saracaloglu, A. S. (2013). The development of inquiry skills scale: Reliability and validity study. Asian Journal of Instruction, 1(2), 56-65.
Karaman, K., Ekici, M., & Akgun, E. (2011, June). Examining effects of different levels of blended learning activities on student achievement and retention of learning. In International Conference on New Horizons in Education. Guarda. Retrieved from https://goo.gl/JGC4if
Karaman, S., Yildirim, S., & Kaban, A. (2008, December). Learning 2.0 is becoming common: Research and results on the use of Web 2.0 applications in education. XIII. Internet Conference of Turkey, Ankara. Retrieved from http://inet-tr.org.tr/inetconf13/kitap/karaman_yildirim_inet08.pdf
Kert, S. B., & Ugras, T. (2009, May). Simplicity in programming training and entertainment: Scratch example. In The First International Congress of Educational Research. Canakkale. Retrieved from
https://goo.gl/9KOxOt
Kitsantas, A., Dabbagh, N., Chirinos, D. S., & Fake, H. (2016). College students’ perceptions of positive and negative effects of social networking. In Social Networking and Education (pp. 225-238). Springer International Publishing. https://doi.org/10.1007/978-3-319-17716-8_14
Korucu, A. T., & Cakir, H. (2014, February). The view about dynamic web technologies of computer teacher candidates’. Academic Computing Conferences, Mersin. Retrieved from http://ab.org.tr/ab14/bildiri/299.pdf
Lau, W. W., & Yuen, A. H. (2009). Exploring the effects of gender and learning styles on computer
programming performance: Implications for programming pedagogy. British Journal of Educational Technology, 40(4), 696-712. https://doi.org/10.1111/j.1467-8535.2008.00847.x
Mutlu, M. E., Erorta, O. O., & Gumus, S. (2005, June). Information management training in the internet environment: Example of associate degree program in information management. Biltek 2005 International Information Congress, Eskisehir. Retrieved from https://goo.gl/3mB77g
Ozmen, H. (2004). In science teaching, learning theories and technology-assisted constructivist learning. The Turkish Online Journal of Educational Technology, 3(1), 100-111.
Ozyurt, O., & Ozyurt, H. (2015). A study for determining computer programming students’ attitudes towards programming and their programming self-efficacy. Journal of Theory and Practice in Education, 11(1), 51-67.
Peltier-Davis, C. (2009). Web 2.0, library 2.0, library user 2.0, librarian 2.0: Innovative services for sustainable libraries. Computers in Libraries, 29(10), 16-21.
Perry, G. (2009). Absolute Beginner’s Guide to Programming (Converting: Timur Aksoy). İstanbul: Sistem Publishing.
Ritz, J. M., & Martin, G. (2013). Research needs for technology education: An international perspective. International Journal of Technology and Design Education, 23(3), 767-783.
https://doi.org/10.1007/s10798-012-9215-7
Rohaan, E. J., Taconis, R., & Jochems, W. M. (2012). Analysing teacher knowledge for technology education in primary schools. International Journal of Technology and Design Education, 22(3), 271-280.
https://doi.org/10.1007/s10798-010-9147-z
Seferoglu, S. S. (2009, February). The use of technology in elementary schools and the perspectives of managers. Academic Computing Conferences, Sanliurfa. Retrieved from https://goo.gl/I162Jv
Sendag, S. (2008). New trends on the web: Integration into learning environments. Proceedings of 8th
International Educational Technology, 995-1001.
Tapia, M., & Marsh, G. E. (2004). An instrument to measure mathematics attitudes. Academic Exchange Quarterly, 8(2), 16-21.
Taskoyan, S. N. (2008). The effect of inquiry learning strategies on students? skills of inquiry learning, academic success and attitudes (Published PhD thesis). DokuzEylül University Institute of Educational Sciences, Izmir, Turkey.
Tuzun, H. (2007, January-Februay). Programming 2.0: Using innovative internet tools in programming
education. IX. Academic Computing Conferences, Kutahya. Retrieved from
http://ab.org.tr/ab07/kitap/tuzun_AB07.pdf
Venkatesh, V., Rabah, J., Fusaro, M., Couture, A., Varela, W., & Alexander, K. (2016). Factors impacting university instructors’ and students’ perceptions of course effectiveness and technology integration in the age of web 2.0. McGill Journal of Education/Revue des sciences de l'éducation de McGill, 51(1), 533-562. https://doi.org/10.7202/1037358ar
Yasar, S. (1998). Structuralist theory and learning-teaching process. Anadolu Journal of Educational Sciences International, 8(1-2), 68-75.
Yilmaz, R., Gumus, S., & Okur, M. R. (2005, September). Online learning in higher level teaching in Turkey. 5th International Educational Technology Conference, Sakarya. Retrieved from https://goo.gl/6KqNQt