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Applied Psychology, January 2015
Applied Psychology
Citation this paper:
Zarabiyan F., Latifi Z., MirMahdi S R., Ghaznavi R. (2015). The Relationship between Smart and
Attitudes to ICT and Teaching and Learning Process Promotion. Applied Psychology, 11,
17-26.
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http://www.jourpsyc.com/majaleh/1102.pdf
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Journal.
The Relationship between Smart and Attitudes to ICT and Teaching and Learning Process Promotio
Applied Psychology
Vol. 3(11), pp. 17-26, January 2015
http:// www. Jourpsyc.com
The Relationship between Smart and Attitudes to ICT and
Teaching and Learning Process Promotion
Frozan Zarabiyan
Assistant professor at Tehran Payame Noor University
Zohreh Latifi
Assistant professor at Isfahan Payame Noor University
Seyed Reza MirMahdi
Assistant professor at Isfahan Payame Noor University
Rahim Ghaznavi
MA student of History and Philosophy of Education South Tehran Payame Noor University
Received: 11 Nov, 2014
Accepted: 15 Dec, 2014
Abstract
This research aimed at investigation the relationship between smart and
attitudes to ICT and teaching and learning process promotion among the grade
one high school students. This research is descriptive, casual and comparison.
The statistical population consisted of all smart and normal schools in the city
of Ardabil. By multistage cluster sampling method, 218 students were selected
by cluster sampling. Questionnaires of teaching-learning process, attitudes to
ICT were used to collect data. For data analysis, multivariate analysis of
variance (MANOVA), and t-test and ANOVA were used. The results showed
that there is a difference between the normal schools teaching and learning
processes and smart schools teaching and learning processes. But there is no
significant difference between the learning process in schools and school
interaction and attitude to ICT in normal and smart schools.
Keywords: Smart Schools, Attitudes to ICT, Teaching and Learning Process.
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Applied Psychology, January 2015
Introduction
Education is very important in today’s world. And ever-increasing developments have caused to pay
attention to education. Nowadays, education is one of the inevitable needs of the human. Training
and skill enhancement have converted into an essential tool for coping with the complex and
revolutionary issues. Training particularly education that focuses on educating new generations is one
of the primary needs of a civilized society (Moayeri, 2010). Also, due to its pervasive nature, it is the
best way to achieve new development. It can be said that the most important criterion for
development in today’s world is technology and education is a tool for identification and achieving
new technologies (Noruzi, Zandi and Mosavi Madani, 2007).Application of technology in education
is an important aspect of ICT considered as a great revolution in the social, occupational and
educational life in the 21st century that has opened new horizon on the educational institutes like
schools and universities (Rahimi and Yadollahi, 2011). Several studies suggest that the use of
technology in education has caused to reduction of training costs, saving time, increasing learning
opportunities, increase academic success and instant access to information. Therefore, the policy
makers of education in many developing countries including Iran have shown special attention to elearning (Rahimi and Yadollahi, 2011). Extended use of ICT in the teaching process concurrent with
the evolution of approaches of education in the world, the background has been provided for
formation of smart schools (Jalali, 2009). Smart Schools are learning organizations in which train a
creative and competent generation that enable to create knowledge. These schools are requirements
of a knowledge-based society and follow knowledge and entrepreneurial skills development
approaches for the students (Jalali, 2009). Because of offering flexible curriculum and possibility of
teaching with new methods, having broad scopes of educational plans and student-based education
and considering the needs and attitudes of the students, the smart schools can be useful to eliminate
the weakness of the educational gap (Movaydnia, 2009).
These schools have been designed in order to provide an environment for learning and improving
school management system and educating researcher- students (Jalali, 2009). The role of ICT in
smart schools is empowering and promoting teaching and teaching (I am. pvndva.am Vykzyany,
2011). In these schools, the students learn proportionate with their skills and talents and all students
pay attention to self-actualization in all educational activities and also, there is no limitation in
learning and achievement processes. The teachers are the capable specialists that guide the students
in access to the knowledge resources and they play the role of facilitator (Tehran Educational
Organization, 2007). Indeed, the traditional role of the teachers as the main source of knowledge is
converted into a guide and facilitator. The teachers show the students how to learn and use their
knowledge in order to improve the quality of their life (quoted from Mahmoudi and colleagues,
2008). Teaching method in the smart schools combines learning strategies enhance the competencies
of students (UNESCO, 2005).Important changes caused by information technology, has been a
source of major changes in the classroom. The important changes can be mentioned as access to the
external information that has caused to motivating in learning (Mishra, 2005).By taking advantage of
information technology the teachers access to the training resources and information and provide
training needed resources easily(Loveless,2003). The computer is used in schools to develop and
enrich learning process (Anderson, 2003). Technology-enriched learning environments have a
positive effect on the attitudes of students towards motivation, creativity and the importance of the
computer (Agarkalaki, Safari and Hafezi, 2011). Students’ attitude to the deployment of information
technology is very effective; in other words, to understand students’ attitudes to learning can help to
create a better learning environment (Nagavi, 2010). This positive attitude towards technology can
The Relationship between Smart and Attitudes to ICT and Teaching and Learning Process Promotio
lead to self-efficiency of the students. As the research of Zamani and Saeidi(2012) by the title of the
effect of multi-media use on self-efficiency and motivation in mathematics lesson in the female
students of the high schools of Izeh showed that multi-media has a positive effect on self-efficacy
and academic motivation.
The research was conducted on the impact of smart schools in the learning process. In this research,
the effect of moderator variable has not been investigated. This study sought to evaluate the
relationship between smart and attitudes to ICT in the teaching and learning process promotion.
Method
The present study is description in terms of the nature and objectives, of the causal comparative
research type or retrospective. In other words, in a retrospective study, the researcher investigates the
likelihood causes and tries to find out the cause from effect (Delavar, 2012).
The statistical population
The study population included all secondary male normal and smart schools of Ardabil, which the
total number of normal and smart schools in the survey is 218 schools.
Sample
In this study, the sample size is 8 normal and smart schools, which grade one experiential class of
each school was selected. The total number of students in the academic year 2013-2014 was 1211
students that, 218 students were chosen as sample in this study.
Sampling
procedure
The sampling method used in this study is cluster random sampling. So that from each area, a smart
school and a normal school was selected.
Data collection
Three questionnaires were used to collect data, which are:
Author-made teaching and learning process questionnaire includes 35 items (which 13 items are
about learning and 22 items are about teaching that divided into three components of prior to
teaching, teaching, the after-teacher) was designed based on Likert 5 grades scale. In terms of
scoring, 1 depicts strongly disagree, 2 disagree, 3 have no idea, 4 agree and 5 strongly agree.
Inventory attitude towards ICT: The questionnaire was adapted from questionnaires ICT that
Christens Ketzek (1995-1997) designed this questionnaire at the University of North Texas to assess
the students’ attitude towards ICT in school including 107 items (Agh kalki, 2011). But 27 items
were used in this study (with two components of approach to e-mail and computer). The scale of this
questionnaire is Likert 5 scales which, 1 depicts strongly disagree, 2 disagree, 3 have no idea, 4 agree
and 5 strongly agree. In this study, Cronbach’s alpha reliability was calculated with total reliability of
0.70 respectively. The lowest score was 80 and the highest score was 109.
Descriptive and inferential statistical methods have been used in this study. In the descriptive
statistics section, indictors such as mean, standard deviation have been employed to show the
presented data. In the inferential section for analysis of the research hypotheses, MANOVA was used
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Applied Psychology, January 2015
for the first hypothesis and independent t was used for the second hypothesis and MANOVA was
employed for the third hypothesis.
Results
H1: There is a difference between the teaching and learning process in smart and normal schools.
Multivariate analysis of variance was used to test this hypothesis. Multivariate analysis of variance
allows us to compare several dependent variables in different levels on the dependent variable.
Dependent variable
Learning
Teaching
Table 1: Normality test
Kolomogrov-Smearnov
Statistics
FD
176
893.0
176
699.0
Sig
402.0
713.0
Table 1 shows the description of normality of teaching and learning process. Non-significant results
for the learning and teaching variable indicate that the data are normal.
Table 2: Results of MANOVA of teaching and learning process between smart and normal schools
Resources
Dependent
Sum squares
FD
Sum squares
F
Sig
variables
School
Learning
744.86
1
744.86
542.1
215.0
Teaching
216.1103
1
216.1103
120.6
014.0
Error
Learning
118.19411
345
264.56
Teaching
671.62189
345
260.180
Total
Learning
688389
347
Teaching
1699528
347
According to Table 2 and the statistical value of (f=1.542) and (p>=0.215), there is no significant
difference between smart and normal schools in the learning process. But in the teaching process
with respect to the statistical value of (F=6.120) and (P, 0.014), there is a significant difference
between normal and smart schools.
H2: Attitudes to ICT in the relationship between smart schools and teaching and learning process
promotion plays an interactional role.
For analysis of this hypothesis, MANOVA was used because we want to investigate the influence of
attitudes to technology as a moderator variable on the dependent variable of the teaching and learning
process the smart and normal schools.
Table 3: Results of MANOVA of the impact of school type and attitudes to technology in teaching process
Effect
Sum squares
FD
Sum Means
F
Sig
coefficients
School
216.604
1
216.604
43.3
06.0
010.0
Attitude towards
school technology
75.1085
2
87.542
08.3
04.0
019.0
Attitude towards
technology
088.864
2
044.432
45.2
08.0
015.0
The Relationship between Smart and Attitudes to ICT and Teaching and Learning Process Promotio
According to the results reported in Table 3, the main effect of school on teaching process in level of
0.05 is not meaningful (P.0.65), which depicts that school type has no effect on teaching process, but
the attitude to technology is meaningful in 0.05 (P, 0.47) and statistics (F=3.08) indicates that there is
a significant difference between the smart school and normal school in terms of attitudes to
technology. But there is no interaction between the impact of school and attitudes to technology on
teaching process (P.0.8 and statistics F=2.45).
Table4: The results MANOVA of the impact of school and attitude to technology in the learning process
Effect
Sum squares
FD
Sum Means
F
Sig
coefficients
School
74.3
1
74.3
070.0
79.0
000.0
Attitude towards
school technology
Attitude towards
technology
41.1130
2
208.565
55.10
000.0
06.0
81.142
2
41.71
33.1
265.
0080.
According to the results reported in Table 4, the main effect of school on learning process in level of
0.05 is not meaningful (P>79), which depicts that school type has no effect on learning process, but
the attitude to technology is meaningful in 0.05 (P, 0.00) But there is no interaction between the
impact of school and attitudes to technology on learning process (P>265).
Attitude
1
2
3
Table 5: Mean difference in attitude to technology in learning
School
Mean
Mean error
Confidence level
0.95/Low
Normal
26.41
43.1
44.37
Smart
76.39
59.1
62.36
Normal
84.42
695.0
48.41
Smart
50.44
665.0
19.43
Normal
90.46
27.1
40.44
Smart
89.47
67.1
59.44
Sig 0.95/High
09.44
90.42
21.44
81.45
41.49
19.51
As Table 5 shows in level 1 attitude to technology in interaction with learning the mean of normal
schools (41.26) is higher than the smart schools (39.76) respectively. In level 2, mean of normal
schools (42.84) is lower than the smart schools (44.50). . In level 3, mean of normal schools (46.90)
is lower than the smart schools (47.89).This shows that the smart school students have higher
attitudes towards technology in learning.
Attitudes
1
Table 6: Tokay test for mean differences in learning
Attitudes levels Mean difference
SD
Sig
0.95/Low
2
12.-3
17.1
022.0
87.-5
Sig 0.95/high
-0.36
2
3
1
67.-6
12.3
47.1
17.1
0.000
0.002
-10.14
0.36
-3.21
5.87
3
3
1
56.-3
67.6
12.1
47.1
0.005
0.000
-6.20
3.21
-0.91
10.14
2
56.3
12.1
0.005
0.91
6.20
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Applied Psychology, January 2015
As the table shows there is a significant difference in means in the levels of attitude towards
technology in interaction with learning.
Attitude
1
2
3
Table 7: Mean difference in attitude towards technology in teaching
School
Mean
Mean error
Confidence level
0.95/Low
Normal
26.65
60.2
15.60
Smart
33.63
89.2
63.57
Normal
57.67
25.1
10.65
Smart
21.70
20.1
84.67
Normal
73.65
04.3
74.59
Smart
63.75
31.2
09.71
Sig 0.95/High
38.70
02.69
03.70
58.72
72.71
80.18
As Table 7 shows attitudes in schools in level 1 of attitudes towards technology in interaction with
teaching the mean of normal schools (65.26) is higher than the smart schools (63.33). In level 2 the
mean of normal schools (67.57) is lower than the smart schools (70.21) and in level 3 the mean of
normal schools (65.73) is lower than the smart school (75.63) which suggests that the students of the
smart schools have higher attitudes towards interaction of technology in teaching.
Table 8: Tokay test for mean differences in teaching
Attitudes
1
2
3
Attitudes levels Mean difference
SD
Sig
Confidence level Sig 0.95/high
0.95/Low
54.-9
46.
2
54.-4
12.2
08.0
3
-7.61
2.67
01.0
1
3
1
4.54
-3.08
61.7
2.12
2.03
2.67
0.08
0.28
0.01
-7.87
1.33
9.54
1.72
13.90
2
08.3
2.03
0.28
-1.72
7.87
-13.90
-0.46
-1.33
There is a difference in attitude at level 1 and level 3 with a mean (-7.61) and significant level (0.1)
and there is no difference between the levels in level 2 but at level 3 and level 1 a significant
difference is seen with mean of 7.61 and meaningful level of 0.01.
Conclusion
This research aimed to investigate the relationship smart school in interaction with attitude towards
ICT in teaching and learning process promotion. There is a difference between teaching and learning
processes in smart and normal schools. Findings from the multivariate analysis of variance showed
that there is no significant difference between teaching and learning process in smart and normal
schools. However, there is a significant difference in teaching process between smart and normal
schools. It means that smart schools have no impact on learning process and there is no difference
between the smart and normal schools but it has impact in teaching process in the smart schools.
The Relationship between Smart and Attitudes to ICT and Teaching and Learning Process Promotio
The results are inconsistent to the results of Ansari (2011), Hajjfroush (2004), Atkinson (2004), and
the results of the professors at the University of Laval and Macgill (1996). As the research by
Atkinson (2004) that has compared learning in the traditional environment and computer-assisted
learning and its relationship with cognitive style. His report suggests that people with verbal
cognition have more positive attitude towards this environment and have better performance in
computer-assisted learning environment. In a research by professors at the University of Laval and
Macgill in 1996, entitled “The role of new technologies in learning and teaching in elementary and
secondary school”, it was concluded that students who have access to a global network have better
performance (quoted by Hagshenas, 2009) and these results are consistent to the research on teaching
by Hanizar and Halim(2005). According to the findings of the first hypothesis, it is clear that smart
schools have no effect on students learning. In explaining of this hypothesis it can be said that the
teachers yet teach with traditional method and they have not learned to use technology in improving
of learning. The role and responsibility of teachers in school is management of educational
technology, doing specialized tasks in the teaching – learning environment, effective teaching
according to sources, familiar with the types of student and proper use of technology (Jalali,
2009).Indeed, the traditional role of the teachers in these schools changes to guiding the students in
self-learning and facilitating access to the knowledge resources (Mahmoudi and colleagues, 2009).
Teachers are the main actors of successful interaction with information technology in educational
system (Enayati, Medanloo, Alipour and Mirkazemi, 2012). While, if teachers are interested in the
use of information technology in education and learn training skills it will lead to good incentives for
the use of technology in learning (Akhavan and Doust Mohammadi, 2010). The research conducted
by Hakimi on the effective factors in non- usage of computers and related software by teachers show
that the teachers are not prepared to teach with technology and also they are not ready to teach with
computer and related hardware (Farahani, Rezaisharif and Hasanlu,2012). Monaganiyan introduced
five factors of shortage of equipments, institutional support, unbelief in information technology,
disbelief and time limitation as barriers in electronic teaching and learning (quoted by Farahani,
Rezaisharif and Hasanlu, 2012). Other studies show that investment in education sector and training
of skilled human force is another important issue in the development of e-learning. Since
development without expert labor and empowerment will fail and will increase the resistance of the
traditional system and training in information technology will make it harder.
In explaining first hypothesis it can be said that the definition of smart schools in Iran is as follows:
Iran smart schools are developed schools that use ICT for transfer of the traditional concepts. These
tools include computer programs such as software such as PowerPoint, mapping and web pages and
internet and the teacher plays the role of instructor and the lessons are taught electronically (Jalali,
2009). The smart schools selected in this research by the experts of educational technology were in
higher level but their equipments included a smart screen and a small site with few computers and
they lack equipments influencing learning process and there was no difference between these schools
and normal schools and only the teachers could teach through PowerPoint in lessons of biology and
history and they used screens and for other lessons they used traditional methods.
The findings of this research show that the smart schools were effective in learning process and the
studied schools had smart screens and the teachers used them for teaching of some lessons. The
results of the research conducted by Hanizar and Halim(2005) in smart schools of Puerto Rico
educational area showed that use of technology improves the education of the students. However, the
findings of this study were not enough to have an impact on learning.
According to other research, many teachers believe that ICT can be used to improve the efficiency
and enrich the educational resources available to learners (Ming, Carol Hall, Azman, Gordon, 2010).
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Applied Psychology, January 2015
- Attitudes to ICT has interactive role related to the smart schools in teaching- learning process
promotion.
Interaction in the type of school and attitude towards school has no effect in learning process, but the
type of school in interaction with technology is effective. These results are consistent to the findings
of Kenzek and Christianson (1997), Ag Arkali and colleagues (2011) and inconsistence to the
findings of the King (1994-1995) Almjbob (2000), Mozhdehavar(2006), Atkinson (2004) and
Rampagapran
(2007).
In explanation of this result it can be said that the attitude towards technology is not likely as a
mediator. Regarding to the attitude towards technology, the students of these schools yet have no
better attitude on the impact of technology on teaching and learning process. However, understanding
attitudes to e-learning can create a better learning environment for teaching (Nagavi, 2010). In view
of the impact of technology on teaching and learning culture of acceptance of technology by students
is necessary. Smart schools were considered as an educational plan in 2004 in Iran and this plan was
developed gradually. According to the research of Aydin and Tasci(2005) and Chan and Nagi(2007)
the users attitude and human resources are two important factors influencing the use of technology.
Attitude can cover fitness, fun and pleasure, importance, motivation and so on. Regardless of the
attitude and acceptance of ICT, development is not possible. Along with the development of
infrastructure, equipment and training are necessary to strengthen positive attitudes about technology
(Mutiaradevi, 2009 quoted Abdullvahabi, Mehralizadeh and Parsa,2012).
Acknowledgment
we would like to thank all professors and administrators and teachers who helped us in this study.
The Relationship between Smart and Attitudes to ICT and Teaching and Learning Process Promotio
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