Analyzing rate of cognitive and metacognitive strategies in learners with
respect to interactive effect of learning environments (University and
guidance school) and location (urban and rural)
Koorosh Parviz, MA
Psychology Group, Payame Noor University (PNU), Iran
[email protected]
Paper presented at the British Educational Research Association Annual Conference,
Heriot-Watt University, Edinburgh, 3-6 September 2008
Abstract
This research is going to study who learners use of cognitive and metacognitive strategies and
how location (rural and urban) and environment education interactively affect on these strategies.
The total number of participants in this study was 241 rural and urban female students in
Slamabadegharb, Iran. A total of cases are divided to 4 subgroups so that 1- urban guidance
school students, 2- rural guidance school students, 3- urban students of university, and 4- rural
students of university. The results show cognitive and metacognitive strategies of urban guidance
school students is more than rural guidance school students but between urban and rural students
of university there is not any significance different. Also The result show metacognitive
strategies of urban guidance school students are more than urban students of university but in
others comparing different cannot be observed. Finally this research show there is a significance
relationship between average of grades with cognitive and metacognitive strategies just in urban
guidance school students but in other group there is no. overall outcome of this study is location
(urban and rural) cannot affect on rate of cognitive and metacognitive strategies in students of
university despite its effect on the strategies in guidance school students.
A UTHOR KEYWORD : COGNITIVE STRATEGIES, METACOGNITIVE STRATEGIES, AVERAGE OF GRADES,
GUIDANCE SCHOOL STUDENTS , STUDENTS OF UNIVERSITY, URBAN , RURAL
1. Introduction
Learning strategies refer to those techniques, procedure or processes that
students apply in learning situations to help acquire, store or express information
more effectively. In a sense, strategies empower students by arming them with
techniques that facilitate learning. For example, reading strategies such as
paraphrasing and summarizing help students acquire important information from
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written word; listening strategies such as note taking help students enhance their
abilities to glean important information from lectures; memory strategies first-letter
mnemonics help students learn and retain facts (Deshler and Schumaker, 1986).
However, as Palincsar (1986) points out, knowing strategies along is not enough
to ensure their effective and appropriate use. Something is required, and that
something is metacognation. As defined by Baker and Brown (1984),
metacognation is an awareness of the skill, strategies, and resource that are needed
to perform a task and the ability to use self-regulatory mechanisms to successfully
complete the task. As the above definition indicates, metacognation generally
thought to have two components. The first related to individual abilities to assess
the demands of the task at hand and also to understand his or her own strengths and
weaknesses in relationship to the task (Reeve and Brown, 1985). The second
component of metacognation is concerned with regulating the performance a task.
In learning situations, this form of metacognation involves applying a variety of
processes that, in information processing parlance, are often referred to as
“exclusive” function; they include planning, monitoring, and evaluating the
learning processes (Baker & Brown, 1984).
Weinstein and Meyer (1991, P.17) state ‘A cognitive learning strategies is a plan
for orchestrating cognitive resources, such as attention and long-term memory to
help reach a learning goal’. They indicate that there are several characteristics of
cognitive learning strategies, including that they are goal-directed, intentionally
invoked, effortful and are not universally applicable, but situation specific.
Metacognitive strategies appear to share most of these characteristics, with the
exception of the last one, since they involve more universal application through
focus upon planning for implementation, monitoring and evaluation (Schraw,
1998).
The result of the research of Corenford (2005) implies that it is in postcompulsory education that the teaching and fostering of these specific skills is
likely to be the most fruitful. Effective learners routinely and often unconsciously
use there metacognitive capacity as they select cognitive strategies [that] they
think will work in a learning situation, apply the strategies, monitor their use,
evaluate their effectiveness, and make adjustment as necessary. For effectiveness
learning cognitive and metacognitive strategies need be used in concert (Schied,
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1989). The importance cognitive and metacognitive skills in effective learning and
performance have been recognized for some time (Weinstein & Meyer, 1986,
Sternberg, 1998). Indeed the metacognitive skills of planning, monitoring and
evaluation constitute the essence of skilled professional performance in the adult
world of work. But there is still little evidence that cognitive and metacognitive
skills per se are being taught widely or effectively at all levels of schooling or
beyond in tertiary education, at either university or college levels (Wallis, 2004).
Although Parviz (2005) in his research high school students take part in it, showed
between educational success and cognitive/metacognitive strategies there is a
positive relationship and also urban use these strategies more than Rural.
From above result, united statement about effect of learning strategies on
learning in variety situations cannot be deduced. Therefore with respect to different
environment, it is not clear how its changes are. In this research researcher focuses
on environment and its relationship with learning strategies. Since other variables
of this research are learning environments (guidance school and university) and
location (Urban and Rural). Author intends to analyze interactive effect of both
variables with learning strategies based on theory of constructivism.
Constructivism
The theory of constructivism has been one of the major conceptual frameworks
which guide and shop contemporary educational reforms and practice (Fosnot,
1996; Wilson, 1996). Constructivism means that learning is an active process in
which learner construct new ideas or concepts passed on current and past
knowledge. To constructivist, the concept of knowledge is based on the
developmental theories of Piaget (1972) and Vygotsky (1978). Both believed that
learners construct knowledge by interacting with their environment (Wadsworth,
1996). Although there may be many forms of constructivism, the constructivism
generally assert that knowledge is actively constructed by individuals, and social
interaction whit others also play an important role in construction process (Perkins,
1999; Tsai 1998, 2000). Numerous studies have suggested that learners`
perceptions of the learning environment will guide attitudes, behaviors, knowledge
construction in that environment (Dart et al., 1999; Fraser, 1998). In this research
is tried to focus on roll of learning environment and location so in constructivism
theory is noticed (only interactively) and not downright.
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2. Method
Participates
The total number of participants in this study was 241 rural and urban female
students in Slamabadegharb, Iran. The subjects were divided into two groups based
on their learning environment (guidance school and university). The first group
consisted of 120 urban and rural guidance school students (60 rural and 60 urban).
The second group consisted of 119 urban and rural students of Payame Noor
University (59 rural and 60 urban). In this research it was be wanted that for
making maximum of variance between level of learning environments, lowest level
and highest level compared but the instrument used in the research was more
difficult than elementary student can understand it. Since guidance school chose.
Instrumentation
For accessing of learning strategies (cognitive and metacognitive), Karami`s
learning and study questionnaire in Persian is used. The questionnaire consisted of
three parts. The first section elicited respondents` demographic information as
location (urban and rural), learning environments (high school and university) and
grade point average. The second part included 49 items representing three
subcategories of cognitive strategies namely: repetition and revision, organization
and semantic elaboration. The third part included 37 items representing two
subcategories of metacognitive as knowledge and controlling of self and
knowledge and controlling of process. Stability of this questionnaire is assessed by
retest method. A relationship quotient between first and second administration for
all strategies is 0.98 and for subscales is ranged from 0.85 to 0.91. For assessing
reliability of this questionnaire it was presented to 30 faculties and student of PHD.
From 26 come bag questionnaire all of the experts confirmed all questions but they
have some reforms that have to be were corrected. Internal quotient for per scale
was accounted that ranged from 0.69 to 0.88(Karami, 2002).
Analysis
To analyze group differences (urban/rural and students of guidance
school/university) one way ANOVA that is followed by post-hoc test (LSD) to
detect the significant differences and independent samples test are used. Also to
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analyze relationships (grades point average and cognitive/metacognitive strategies)
Pearson product moment correlation is used (SPSS version 11.5).
3. Results
Descriptive data: with respect to grades point average, the average of students of
guidance school (urban and rural) is more than students of guidance school and
university (urban and rural). In cognitive and metacognitive strategies rural
students of guidance school are the least whereas urban students of guidance
school are the most. Detailed information is receivable in table 1.
With respect to cognitive strategies, independent samples test shows there is
significance difference between urban and rural students of guidance school (t =
2.006, sig = 0.048). Whereas there is not any significance difference in other
comparisons (table 2).
Table 1: Descriptive statistics
Grades point average
Frequency
Urban
guidance
school
students
Rural
guidance
school
students
Urban
students
of
university
Rural
students
of
university
Total
5
Mean
Standard
deviation
60
16.4
1.9
60
16.05
60
Cognitive strategies
Frequency
Mean
Standard
deviation
60
71.7
12.4
2.05
60
66.4
16.9
2.01
60
59
14.4
1.6
239
15.6
2.1
Metcognitive strategies
Frequency
Mean
Standard
deviation
60
75.9
11.6
13.9
60
68.4
18.1
69.4
12.0
60
68.8
12.2
60
69.8
11.6
60
69.5
11.8
240
69.3
12.6
240
70.7
14.01
Source
Urban guidance school
students
Rural guidance school
students
Urban students of university
Rural students of university
t
2.006
sig
0.04
8
df
98
-.129
0.
898
98
Urban guidance school
students
Urban students of university
Rural guidance school
students
Rural students of university
963.
0.3
38
98
-1.197
.235
98
Table 2: independent samples
test for analyzing cognitive
strategies
With respect to metacognitive strategies there is significance difference between
groups (F=3.25, sig=0.02) (table 3). Post hoc test (LSD) show that in guidance
school students, the urban use more metacognitive strategies than rural (sig=0.007)
and in urban, guidance school students use more meatcogiive strategies than
students of university but in rural is not obtained any significance difference (table
4).
Table 3: One way ANOVA test for analyzing metcognitive strategies
Source
Between
groups
Within group
total
Sum of
square
1854.146
35489.894
37344.043
Mean
square
618.049
189.786
df
F
sig
3
187
190
3.25
6
0.02
3
Table 4: Post hoc test (LSD) for analyzing metcognitive strategies
Source
Urban guidance school
students
Rural guidance school
students
Urban students of university
Rural students of university
Urban guidance school
students
Urban students of university
Rural guidance school
students
6
Mean
difference
7.5
sig
0.00
7
-.77
2.90
7.11
0.01
1
-1.16
0.68
Rural students of university
Finally results indicate in urban guidance school students there is a significance
correlation between grades point average and cognitive strategies (sig=0.001) and
between grades point average and metacognitive strategies (sig=0.02). In rural
students of guidance school there is a significance correlation between grades point
average and metacognitive strategies (sig=0.032). Results show that in urban and
rural students of university there is not any significance correlation between grades
point average and learning strategies (table 5).
Table 5: Pearson product moment correlation
Source
Urban
guidanc
e
school
students
Rural
guidanc
e
school
students
Urban
students
of
universit
y
Rural
students
of
universit
y
7
Grades point
average
Cognitive strategies
Grades point
average
Metacognitive
strategies
Grades point
average
Cognitive strategies
Grades point
average
Metacognitive
strategies
Grades point
average
Cognitive strategies
Grades point
average
Metacognitive
strategies
Grades point
average
Cognitive strategies
Grades point
average
Metacognitive
strategies
correlati
on
0.5
sig
0.00
1
0.34
0.02
0.2
0.16
4
0.3
0.03
2
-.045
0.8
-.020
0.9
0.012
0.94
0.095
0.6
4. Discussion
This study profiled learning strategies of urban and rural students of guidance
school and university. The results show that in guidance school students the urban
use more the cognitive and metacognitive strategies than the rural. This result is in
line with Parviz (2005) and is comparable with Piaget (1972), Vygotsky (1978)
and Dart et al. (1999), Fraser (1998) furthermore just in the metacognitive
strategies the urban guidance school student is higher than the urban student of
university. It means that effect of urbanism on learning strategies in metacognitve
is more than cognitive strategies. But result show that there is no difference
between learning strategies of urban and rural students of university. These results
imply location (urban and rural) affect on learning strategies of students but this
effect is depended to the type of strategies (cognitive and metacognitive) and
learning environment (guidance school and university). Abraham and Vann (1979)
state the use of learning strategies (for vocabulary retention) varies among learners.
Learners adopt strategies that are in line with their previous learning experience
and consistence with their beliefs about vocabulary and vocabulary learning (cited
in Gu and Johnson (1996). These findings show that previous experience and
beliefs of learner about learning and what should be learned, are the factor that
verify learner with respect to use of learning strategies. In developing country like
Iran, rural environments are poorer than urban environment based on the most
factors of welfare and facilities of schooling. Also rural and urban have cultural
and social environments that can compose different beliefs about objects as
learning strategies. Since we can expect rural and urban students differently use of
learning strategies, so that urban apply more this strategies than rural. This
different in higher level of education and university is not apparent because
university as a reach environment can remedy dysfunctions of rural environment.
The results also indicate that in guidance school students there is significance
positive correlation between grades point average and cognitive and metacognitive
strategies. This result is in line with Parviz (2005). Although in students of
university, there is not significance correlation between average and learning
strategies. These findings are comparable with Wallis (2004) that hesitates about
effectiveness of learning strategies in all levels of schooling, Weinstein and Meyer
(1986) and Sternberg (1998) that believe learning strategies are importance in
effective learning for some time. Research show that in high level of education
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effect of some ability likes intelligence on educational success go to reducing
because different between people related to these abilities go to decreasing. The
learning strategies are abilities like intelligence that in great deal is influenced by
environments. Different in environment is followed by different in abilities such as
intelligence and learning strategies. Since that is rational in university level there is
no relationship between grades point average and learning strategies.
Finally all of explanations that have stated above are adapted with theory of
constructivism. This research was a local study since performing it in national level
can be useful. Also in this research the questionnaire cannot be used for elementary
level. It will be good, if in next research a questionnaire that can be used for
elementary level is applied. With respect to results it was found that effect of
learning environment on learning strategies in lower level is more than higher level
especially in rural students so it was recommended to focus on training these
strategies in lower level and it is necessary guidance school in villages is improved
and enriched.
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This document was added to the Education-line database on 6 February 2009
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