Effects of Cognitive Learning Strategies for Korean Learners: A Meta-Analysis

Abstract

The purpose of this study was to synthesize the cognitive learning strategy intervention studies conducted in Korea between
1990 and 2006, using meta-analysis. By means of pre-established systematic criteria, 50 articles were selected and 97 effect
sizes were calculated. Effect size was calculated using ‘the Cohen’s d’ (Cooper & Hedges, 1994). The research questions of
the present study were as follows: (a) Are cognitive learning strategies generally effective? (b) What type of cognitive learning
strategy is most effective? (c) Are effect sizes of different types of cognitive learning strategies different according to
the applied domains, grade levels, and achievement levels? The results of the study indicate that, first of all, the overall
cognitive learning strategies (97 ESs) yielded a large effect size (ESsm=.96), which was not homogenous (Q=55.19,p <.05). Thus, in each subcategory of learners’ characteristics and applied domains, we calculated effect sizes and conducted
the test of homogeneity separately. Except for grade level, the effect sizes were generally homogenous in each subcategory.
The findings revealed that cognitive strategies had large effect sizes (.82–1.69). For average achieving students as well
as underachieving students (Learning Disabilities), cognitive learning strategies were very effective (.82–1.42). The effect
of cognitive learning strategies was very large in terms of students in all grades (1.02–1.34), except for middle school students
(.70). Lastly, the implications for the application of different cognitive learning strategies were discussed.

Full text

Asia Pacific Education Review Copyright 2008 by Education Research Institute
2008, Vol. 9, No.4, 409-422.
409
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Dongil Kim, Associate Professor, College of Education, BK21
Academic Leadership Institute for Competency-based Education,
Seoul National University, Korea; Boong-nyun Kim, Assistant
Professor, College of Medicine, Seoul National University, Korea;
Kijyung Lee, Ph.D. candidate, College of Education, Seoul
National University, Korea; Joong-kyu Park, Assistant Professor,
College of Rehabilitation Science, Daegu University, Korea;
Sungdoo Hong, Kwangju Women’s University, Korea; Hyoungsoo
GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG
Kim, Assistant Professor, Counseling Department, Luther University,
Korea.
This work was supported by the Korea Science and Engineering
Foundation (KOSEF) grant funded by the Korea government
(MEST) (No. R01-2008-000-20528-0)
Correspondence concerning this article should be addressed to
Hyoungsoo Kim, Sanggal-dong17, Giheung-gu, Yongin-si,
Gyeonggi-do, Korea (446-700). E-mail: hskim70@ltu.ac.kr
Effects of Cognitive Learning Strategies for Korean Learners:
A Meta-Analysis
Dongil Kim Boong-nyun Kim Kijyung Lee
Seoul National University
Korea
Joong-kyu Park Sungdoo Hong Hyoungsoo Kim
Daegu University Kwangju Women’s University Luther University
Korea
The purpose of this study was to synthesize the cognitive learning strategy intervention studies conducted in Korea
between 1990 and 2006, using meta-analysis. By means of pre-established systematic criteria, 50 articles were
selected and 97 effect sizes were calculated. Effect size was calculated using 'the Cohen's d' (Cooper & Hedges,
1994). The research questions of the present study were as follows: (a) Are cognitive learning strategies generally
effective? (b) What type of cognitive learning strategy is most effective? (c) Are effect sizes of different types of
cognitive learning strategies different according to the applied domains, grade levels, and achievement levels? The
results of the study indicate that, first of all, the overall cognitive learning strategies (97 ESs) yielded a large effect
size (ESsm=.96), which was not homogenous (Q=55.19, p< .05). Thus, in each subcategory of learners'
characteristics and applied domains, we calculated effect sizes and conducted the test of homogeneity separately.
Except for grade level, the effect sizes were generally homogenous in each subcategory. The findings revealed that
cognitive strategies had large effect sizes (.82-1.69). For average achieving students as well as underachieving
students (Learning Disabilities), cognitive learning strategies were very effective (.82-1.42). The effect of cognitive
learning strategies was very large in terms of students in all grades (1.02-1.34), except for middle school students
(.70). Lastly, the implications for the application of different cognitive learning strategies were discussed.
Key words: cognitive learning strategy, meta-analysis, academic achievementG
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Dongil Kim, Boong-nyun Kim, Kijyung Lee, Joong-kyu Park, Sungdoo Hong, Hyoungsoo Kim
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410
Introduction
Academic difficulties are generally regarded as the
most serious problem for children and adolescents in Korea.
Actually, many youngsters in Korea spend more time
worrying about their schoolwork and grades than any other
issue (Kim, 1998). Over the past decades, a considerable
number of studies have been conducted to help students
overcome academic problems or underachievement. Among
these previous studies, many correlates of both achievement
and underachievement were systematically examined,
including easy-to-control factors and hard-to-control factors.
Unlike the hard-to-control factors, such as intelligence and
personality, learning strategy, cognitive learning strategy in
particular, was perceived as one of the significant
‘controllable’ components for academic success.
Cognitive learning strategies which are composed of
‘elaborate strategy’, ‘organized strategy’, ‘meta-cognitive
strategy’, and ‘affective strategy’ (Weinstein & Mayer,
1986) are sometimes regarded as much the same as learning
strategy. What then is a learning strategy? Devine (1987)
defined ‘learning strategies’ or ‘study skills’ as
“competencies associated with acquiring, recording,
organizing, synthesizing, remembering, and using
information and ideas found in school” (p. 5). Kim (1986)
describes learning strategies as ‘the systematic procedures’
that students initiate to complete such complex tasks as
skimming, determining relevant information, taking notes,
and studying materials for a test. As stated already, learning
strategies also indicated the systematic techniques involving
the use of cognitive and metacognitive elements to respond
independently to specific tasks (Deshler & Schumaker,
1986; Ellis, Lenz, & Sabornie, 1987a; 1987b). There are also
different taxonomies for classification of learning strategies
(Dansereau, 1985; Pressley, 1986; Weinstein & Mayor,
1986; McKeachie et al., 1991).
Many studies (Bos & Anders, 1990; Swanson, 1993;
Swanson & Alexander, 1997; Stanovich & Siegel, 1994)
showed academic problems are significantly related to
learning strategy deficits, and found that learning strategy
plays a major role in academic performance. These previous
studies also showed that a great deal of evidence existed
that the students with academic difficulties lack the
organizational and study skills needed to respond to the task
demands of the regular classroom and that they experienced
difficulty in acquiring those skills. For example, Torgesen
(1977) has found that the students with academic difficulties
are not actively involved in learning and show deficiencies
in spontaneous use of learning strategies. They were passive
in their approach to classroom tasks (Torgesen, 1982).
Additionally, they often did not recognize the need for, or
know how to apply, a learned learning strategy in a new
situation (Chan & Cole, 1986).
According to the meta-analysis studies in the field of
learning problems, efforts to train students with learning
problems to use specific cognitive strategies to improve
learning have been successful. Swanson and McMahon
(1996) synthesized a total of 236-intervention research
studies published between 1963 and 1995 that exclusively
included students identified with learning disabilities (LD).
The results addressed the effects of interventions on array of
dependent measures including reading, math, writing, social
skills, creativity, and perceptual domain. This particular
study reported quantitative effect magnitude of learning
strategies using the meta-analysis method. The average
effect size was about .70. Swanson and Hoskyn (1998)
comprehensively synthesized experimental intervention
studies from 1963 to 1997 that included students identified
as LD. The effect sizes were calculated for 17 categories
such as reading comprehension, memory, mathematics,
writing, and etc. However, the previous analyses did not
show the relationship between targeted behaviors and
treatment.
Additionally, in Korea, a large number of studies have
been conducted, regarding learning strategy programs and
their overall effectiveness. What seems to be lacking,
however, is the comprehensive and systematic summary of
the research findings. When we want to help teachers and
students to be more effective in teaching and learning, it is
not enough just to suggest a wide array of learning strategies
and their overall effects. We want to know what strategies
can be more effective when used upon whom and how to use
these strategies.
Based on a teaching and learning model by McKeachie
et al. (1991), learning behavior is directly influenced by
learner’s cognition and motivation. This indicates when we
apply learning strategies for learners we should consider
learners’ intrapersonal conditions and characteristics. By
examining Piaget’s cognitive development theory, we learn
what to expect in terms of learners’ thinking across different

Meta-analysis on Cognitive Learning StrategiesG
411
grade levels (Kim, 1998). This notion implies that not all
strategies can be used by all learners.
However, these theoretical ideas have not been verified
empirically in the field of strategy instruction, which need to
be done for educational practice. Many previous studies in
Korea have mainly offered immediate effects of the
cognitive learning strategies program in accordance with the
variables including academic achievement, cognitive ability,
efficacy of using learning strategies, and general affective
domains (Kim et al., 2002). A great deal of time is assigned
to subject specific learning in Korea. To help students learn
strategies effectively in time-bound situations, we clarify the
effect sizes of subcategories of learning strategies to apply
efficiently in practice. By integrating and comparing the
findings of related studies, researchers can capture general
patterns among different studies on similar topic, and
identify potentially robust relationships between learners and
appropriate learning strategies.
The main purpose of the present study was to provide a
comprehensive quantitative synthesis of cognitive learning
strategies studies that focused on intervention to improve
students' academic performance. More specifically, the topic
of the study was the general and detailed effectiveness of
cognitive learning strategies, which were provided in the
researches conducted in Korea from 1990 to 2006. Thus, the
research questions of this study were as follows: (a) Are
cognitive learning strategies generally effective? (b) What
type of cognitive learning strategy is most effective? (c) Are
effect sizes of different types of cognitive learning strategies
different by the applied domains, grade levels, and
achievement levels?
Method
Data Collection
Computerized literature searches of two extensive
databases (the National Assembly Library and the National
Library of Korea) were carried out to find relevant articles in
the peer-reviewed journals from 1990 to 2006. The computer
searches were conducted using combinations of the
following descriptors: learning strategy, meta-cognitive
strategy, cognitive strategy, and strategy education. From
this initial pool of identified studies, the following selection
criteria were applied.
First, the identified studies should include learning
strategies and outcome measures. Second, the identified
studies were limited to only those studies that compare
learning strategy treatment group(s) with control group(s).
Third, effect sizes should be obtainable to meet the
following criteria: the study must report (a) means and
standard deviation of each group, or (b) test statistics, such
as z-value, t-value, or F-value. Using the search and
screening procedures, 50 studies were identified that met the
criteria to be included in the meta-analysis.
Coding
A coding form was developed that included the study
information (e.g., authors, published year, a title), subject
characteristics (e.g., demographic data including grade level,
academic achievement, gender, sample size), intervention
dimensions (e.g., the categories of learning strategies,
number of sessions), the categories of applied domains, and
calculated effect sizes.
In most cases, encoding the studies was obvious.
However, coding the subtypes of learning strategies and the
categories of applied domains was not a simple matter.
Classification of cognitive leaning strategies was conducted
based on Weinstein and Mayer (1986): ‘elaborate strategy’,
‘organized strategy’, ‘meta-cognitive strategy’, ‘affective
strategy’, and ‘combined strategy’. The elaborative strategy
involved the strategy to integrate prior knowledge with
current information. The organized strategy is also related to
the mnemonic skills to categorize academic contents and
items or make them hierarchical array. The affective strategy
concerned the students’ strategies to facilitate their
motivation or to relieve the tension to overcome test anxiety.
The meta-cognitive strategy involved the strategy related to
planning, regulating, monitoring, and modifying cognitive
processes. If the intervention in the target article was
composed of more than two types of learning strategies, the
article was classified as the combined strategy.
Categories of applied domains were identified based on
the dependent variables of the target article: academic
achievement, cognitive ability, efficacy of using learning
strategies, and general affective domain. As for the academic
achievement level, in the articles we used in the present
study, underachievement student indicates whose academic

Dongil Kim, Boong-nyun Kim, Kijyung Lee, Joong-kyu Park, Sungdoo Hong, Hyoungsoo Kim
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412
achievement was far lower than his or her potential ability,
that is, LD (Learning Disability). The rest of them were
classified average achievement students.
Two coders coded all of the studies independently. Inter-
coder consistency was examined in order to indicate the
reliability of the coding procedures by calculating the inter-
rater reliability using Cohen’s Kappa, which was .79.
Calculation of Effect Size
The general procedures to obtain effect sizes were (a)
calculating the effect size(s) within a study and aggregating
across studies, (b) testing homogeneity of the aggregating
effect size, and (c) examining the confidence interval to
verify whether overall effect size includes zero.
The effect size index used in this meta-analysis was
Cohen's d (Cooper & Hedges, 1994), calculated as the mean
of the treatment group posttest score minus the mean of the
comparison group posttest score divided by the pooled
standard deviation; that is,
(1)
where MA and MB were the means for the variables for
treatments A and control B, respectively, and s was the
pooled SD. The pooled standard deviation was calculated as
indicated in Cooper and Hedges (1994). Effect sizes were
calculated for each treatment group and associated
dependent variables. Effect size g is the effect size from a
comparison in a study. Unbiased estimates of the population
effect size d were calculated by correcting (approximately)
for the bias in g(Hedges & Olkin, 1985):
(2)
where N= nA+nB, the sum of the number of
participants in Treatment A and in non-treatment B. The
variance of d was estimated by
(3)
When two or more effect sizes were produced in a
single article, the effect sizes were not independent. In this
case the Equations (4) and (5) were used to aggregate the
effect sizes.
(4)
with an estimated variance of
(5)
Table 1
Coding Categories
Categories Subcategories
Study Information author(s), published year, title
Grade level elementary school(6yr.), middle school(3yr.), high school(3yr.), college(2-4yr.)
Academic achievement level average achievement student, underachievement student (learning disabilities)
Gender male, female
Sample
Characteristics
Sample size sample size of treatment and non-treatment group
Subtypes of Learning
Strategies
elaborate strategy, organized strategy, meta-cognitive strategy, affective
strategy, and combined strategy
Intervention
Dimensions Number of Sessions under 5 sessions, 6-10 sessions, 11-15 sessions, 16-20 sessions, 21-25 sessions,
over 26 sessions
Dependent
Measures
Categories of Applied
Domains
academic achievement, cognitive ability, efficacy of using learning strategies,
and general affective domain

Meta-analysis on Cognitive Learning StrategiesG
413
The Equations above are the methods used to form an
aggregated effect sizes for several dependent measures used
in the target articles analyzed (Hedges & Olkin, 1985, pp.
212-213). The estimates produced by Equations (4) and (5)
were used in all of the subsequent analyses.
To determine the estimated aggregated effect size, we
used
(6)
where dc-agg is the aggregate of the set of values of the
effect sizes, weighted by the inverse of variance; dci is the
estimated effect size for comparison I; and k is the number of
effects aggregated (Hedges & Olkin, 1985, p. 111). The
estimate of the variance of this aggregate is given by
(7)
The Chi-square test (Q-test) was used to test for
homogeneity (Hedges & Olkin, 1985). The effect sizes could
be discussed in much the same way as a Z-score. An effect
size of +1.00 indicates that the performance of the
experimental group exceed the control group’s performance
on the dependent measure by one standard deviation. A
negative effect size indicates the superior performance of the
control. For the purpose of interpretation, Cohen’s (1988)
distinctions on the magnitude of the effect sizes were
used .20 in absolute value is a small size, .50 is of moderate
size, and .80 is a large effect size. We also offered standing
percentiles (U3) to interpret the effect size more
meaningfully. Additionally, effect size can be assessed from
its 95% confidence interval (CI). If the confidence interval
doesn’t include zero, then the positive mean effect is
significantly different from zero (p
G
< .05). The statistical
significance of ES was determined by examining the 95% CI.
Results
Description of the Identified Studies
Our literature search identified 50 different articles that
met the inclusion criteria. We computed 97 different effect
sizes from these 50 target articles. Among 50 articles that
reported the effects of learning strategies, one study
contained the primary level (Grade 1 through Grade 3) of
elementary students, twenty four studies involved the
intermediate level (Grade 4 through Grade 6), eighteen
studies were for middle school students, five studies
involved high school, and two studies were focused on
college students. Thus, the majority of the articles were
drawn from intermediate level of elementary schools and
middle schools. As for the achievement level of the subjects
in the studies, the majority (40, 79.6%) of the studies
involved the average achievement students, the rest of them
(10, 20.4%) involved the underachievement students
(Learning Disabilities).
The estimated aggregate effect size was .96, and, as a
result of Q-test analysis, it was found to be not homogenous
(Q = 55.19, p
G
< .05). Thus, in each subcategory of learners'
characteristics and applied domains we calculated effect
sizes and conducted the tests of homogeneity.
Effect Sizes of Subtypes of Cognitive Learning Strategies
The effect sizes of subtypes of cognitive learning
strategies were provided in Table 2. According to the second
column of Table 2, the variation of the number of effect size
of each learning strategy was wide. There were meta-
cognitive strategy (21, 42.0%), elaborate strategy (10,
20.0%), and organized strategy (8, 16.3%).
The effect sizes were significant and homogenous.
Organized strategy produced the moderate effect sizes (.45).
Generally the effect sizes of subcategories of cognitive
learning strategies were regarded as large enough (.93-.1.13).
Effect Sizes by Applied Domains of Learning Strategies
In the present study, the applied domains of learning
strategies (dependent variables in the target articles) were
classified into four categories; (a) academic achievement, (b)
cognitive ability, (c) efficacy of using learning strategies,
and (d) general affective domain. The number of studies of
the applied domains was reported in Table 3. The most
frequent ‘applied domain’ was cognitive ability (36.0%),
followed by academic achievement and general affective
domain (16.0%).

Dongil Kim, Boong-nyun Kim, Kijyung Lee, Joong-kyu Park, Sungdoo Hong, Hyoungsoo Kim
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414
In Table 4, since any confidence interval (CI) of the
mean effect sizes of all applied domains did not contain zero,
a null hypothesis was rejected. The cognitive learning
strategies were very effective in any category of applied
domains. The effect sizes were identified as large enough
(.83-1.69).
Effect Sizes by Student Grade Levels
Mean effect sizes of cognitive learning strategies by
student grade levels. The mean effect sizes of learning
strategies were analyzed by grade levels. Table 5 showed the
mean effect size of each cognitive learning strategy. The
effect sizes of all the grade levels were generally large and
were not homogenous. The effect of cognitive learning
strategies was very large to students in all grades (.85-1.34),
except for middle school students. The effect size of middle
school had a moderate effect size (.70). In Table 5, while all
subtypes of cognitive learning strategies except organized
strategy for the intermediate level (Grade 4 through Grade 6)
of elementary school students produced relatively large
effect sizes. Combined strategy for middle school students
Table 2
Effect Sizes of Subtypes of Cognitive Learning Strategies
CI (95%)
Number of
studies
Number of
ES Mean ES SD of Mean
Effect Size U3(%) Lower Upper
Elaborate strategy 10 12 .93 .84 82.38 .40 1.46
Organized strategy 8 14 .45 .30 67.36 .28 .62
Combined strategy 7 20 1.13 .82 87.08 .74 1.51
Meta-cognitive strategy 21 42 1.04 .95 85.08 .74 1.34
Affective strategy 4 9 1.10 1.64 86.43 .17 2.36
Total 50 97 .96 .10 83.15 .77 1.16
Table 3
Number of Studies by Applied Domains
Applied domains 1 2 3 4 1,2 1,4 2,3 2,4 3,4 1,2,4 1,3,4 2,3,4 Total
Number of Studies 5 18 1 2 1 8 4 3 1 1 3 3 50
Percentage (%) 10.0 36.0 2.0 4.0 2.0 16.0 8.0 6.0 2.0 2.0 6.0 6.0 100
Note. 1. Academic achievement 2. Cognitive ability 3. Efficacy of using learning strategies 4. General affective domain
Tabel 4
Effect Sizes of the Applied Domains
CI
Applied domains Number of
Effect Size
Mean Effect
Size
SD of Mean
Effect Size U3(%) Lower Upper
Academic achievement 21 .96 1.18 83.15 .42 1.50
Efficacy of using learning strategies 12 1.69 1.22 95.45 .91 2.46
Cognitive ability 40 .83 .81 79.67 .57 1.09
General affective domain 24 .83 .12 79.67 .58 1.07
Total 97 .96 .10 83.15 .77 1.16

Meta-analysis on Cognitive Learning StrategiesG
415
showed large effect sizes (1.06) compared to the other
strategies which were moderate in their effect sizes. As for
high school and college students, meta-cognitive strategy
and combined strategy yielded large effect sizes (1.06, 1.02).
Mean effect sizes by applied domains and grade levels.
Table 6 showed the effect sizes of applied domains by grade
levels. The effect sizes of applied domains by grade levels
were not homogenous. Cognitive learning strategies were
comprehensively used in four applied domains across the
grade levels and also yielded generally large effect sizes. For
the primary grade level of elementary school students, the
learning strategies applied to general affective domain was
very effective (1.19), the learning strategies applied to
academic achievement produced the moderate effect sizes
(.51). However due to the small sample size, further studies
were in order. For the intermediate level of elementary
school students, the learning strategies were very effective in
all domains. Especially in terms of learning strategies when
applied to efficacy of using learning strategies and academic
achievement, yielded the very large effect sizes (1.97, 1.55).
For middle school students, the learning strategies applied to
efficacy of using learning strategies, produced large effect
sizes (1.24), and the learning strategies applied to the other
domains produced moderate effect sizes. For high school
students, the learning strategies applied to the efficacy of
Table 5
Mean Effect Sizes of Learning Strategies by Grade Levels
CI(95%)
Grade Level Cognitive Learning
Strategy
Number of
Effect Size
Mean
Effect Size
SD of Mean
Effect Size U3(%) Lower Upper
Primary grade level of
elementary school Meta-cognitive strategy 4 .85 .27 80.23 .20 1.69
Elaborate Strategy 5 1.19 .45 88.30 .05 2.43
Organized Strategy 6 .53 .17 70.19 .08 .98
Meta-cognitive strategy 17 1.18 .22 88.10 .71 1.66
Affective strategy 3 1.82 .78 96.56 .29 3.35
Intermediate grade
level of
elementary school
Combined strategy 5 1.37 .68 75.17 .52 3.26
Sub Total 36 1.15 .20 87.49 .77 1.16
Elaborate Strategy 7 .74 .27 77.04 .07 1.41
Organized Strategy 7 .38 .06 64.80 .23 .53
Meta-cognitive strategy 13 .58 .19 71.90 .17 .99
Affective strategy 4 .74 .14 77.04 .29 1.19
Middle school
Combined strategy 9 1.06 .20 85.54 .60 1.53
Sub Total 40 .70 .10 75.80 .51 .89
Organized Strategy 1 .49 .00 68.79 * *
Meta-cognitive strategy 8 1.60 .47 94.52 .50 2.71
High school
Affective strategy 2 .72 .05 76.42 * *
Sub Total 11 1.34 .36 90.99 .54 2.14
College Combined strategy 6 1.02 .11 84.61 .75 1.29
Total 97 .96 .10 83.15 .77 1.16
Note. * Due to the limited sample size (n< 3), the CI was not calculated.

Dongil Kim, Boong-nyun Kim, Kijyung Lee, Joong-kyu Park, Sungdoo Hong, Hyoungsoo Kim
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416
using learning strategies, general affective domain, and
academic achievement produced large effect sizes. Moreover,
the learning strategies applied to cognitive ability were
moderate (.45). For college students, the learning strategies
were generally very effective. Nevertheless, we should be
cautious in interpreting the result due to the limited sample
size of the studies.
Effect Sizes by Achievement Level
Mean effect sizes of cognitive learning strategies by
achievement level. Table 7 provided the effect size of each
cognitive learning strategy for average achievement students,
as well as for underachieving students (LD). The effect sizes
of achievement level were homogenous. Cognitive learning
strategies were more frequently applied for average
achievement students. The effect sizes of cognitive learning
strategies for both groups yielded generally large effect sizes.
Mean effect sizes by applied domains and achievement
level. Table 8 indicated the effect sizes by applied domains
and achievement level. The effect sizes of achievement level
were not homogenous. Cognitive learning strategies were
widely used in four applied domains across the academic
level and also yielded generally large effect sizes.
G
Summary and Discussion
The purpose of the present study was to synthesize the
Table 6
Mean Effect Sizes by Applied Domains and Grade Levels
CI (95%)
Grade Level Applied Domains Number of
Effect Size
Mean
Effect Size
SD of Mean
Effect Size U3(%) Lower Upper
Academic achievement 2 .51 .35 69.50 * *
Primary grade level
of elementary school General affective domain 2 1.19 .25 88.30 * *
Academic achievement 6 1.55 .84 93.94 .60 3.70
Cognitive ability 20 1.02 .22 84.61 .56 1.49
Efficacy of using learning strategies 3 1.97 .60 97.56 .80 3.15
Intermediate grade
level of elementary
school General affective domain 6 .80 .11 78.81 .53 1.07
Academic achievement 10 .75 .20 77.34 .30 1.20
Cognitive ability 14 .63 .14 73.57 .32 .93
Efficacy of using learning strategies 5 1.24 .37 89.25 .21 2.27
Middle school
General affective domain 11 .49 .14 68.79 .18 .80
Academic achievement 2 .83 .06 79.67 * *
Cognitive ability 4 .45 .10 67.36 .14 .76
Efficacy of using learning strategies 2 3.18 .97 99.93 * *
High school
General affective domain 3 1.65 .50 95.05 .51 3.81
Academic achievement 1 .74 .00 77.04 * *
Cognitive ability 1 1.36 .00 91.31 * *
Efficacy of using learning strategies 2 .93 .18 82.38 * *
College
General affective domain 2 1.13 .14 87.08 * *
Total 97 1.05 .22 85.31 .62 1.48
Note. * Due to the limited sample size (n< 3), the CI was not calculated.

Meta-analysis on Cognitive Learning StrategiesG
417
results of the cognitive learning strategies intervention
studies conducted in Korea from 1990 to 2006. By the use of
pre-established and systematic criteria, 50 articles were
selected and analyzed. Effect size was calculated using 'the
Cohen's d' (Cooper & Hedges, 1994).
The results of the study indicated that overall cognitive
learning strategies (97 ESs) yielded a large effect size (.96),
which implied that the mean of the treatment group was
located on the .82 percentile in the normal curve distribution
of control group. However, the aggregated effect sizes were
not homogenous. Thus, we were advised to calculate effect
sizes and do the test of homogeneity in each subcategory of
cognitive strategies. Except for grade levels, the effect sizes
turned out to be homogenous in each subcategory, meaning
that the differences of effect sizes of cognitive learning
strategies were not significant.
Table 7
Mean Effect Sizes of Cognitive Learning Strategies by Achievement Level
CI(95%)
Achievement
level
Cognitive learning
strategies
Number of
Effect Size
Mean Effect
Size
SD of Mean
Effect Size U3(%) Lower Upper
Elaborate strategy 9 .79 .30 78.52 .09 1.48
Organized strategy 14 .45 .08 67.36 .28 .62
Meta-cognitive strategy 32 .88 .15 81.06 .57 1.18
Affective strategy 7 1.26 .70 89.62 .45 2.98
Average
Achievement
Student
Combined strategy 12 .88 .12 81.06 .62 1.15
Sub Total 74 .82 .10 79.39 .62 1.02
Elaborate strategy 3 1.36 .29 91.31 .01 2.62
Meta-cognitive strategy 10 1.56 .36 94.06 .74 2.37
Affective strategy 2 .51 .06 69.50 .22 1.24
Under-achievement
Student
Combined strategy 8 1.50 .41 93.32 .54 2.45
Sub Total 23 1.42 .21 92.22 1.01 1.83
Table 8
Mean Effect Sizes of Applied Domains by Achievement Level
CI(95%)
Achievement level Applied domains Number of
Effect Size
Mean Effect
Size
SD of Mean
Effect Size U3(%) Lower Upper
Academic achievement 17 .95 .32 82.89 .28 1.62
Cognitive ability 34 .66 .11 74.54 .44 .87
Efficacy of using learning strategies 7 1.57 .42 94.18 .53 2.61
Average
Achievement
Student General affective domain 16 .70 .12 75.80 .45 .95
Academic achievement 4 1.01 .26 84.38 .20 1.82
Cognitive ability 6 1.77 .48 96.16 .54 3.01
Efficacy of using learning strategies 5 1.86 .65 96.86 .05 3.67
Under-achievement
Student
General affective domain 8 1.08 .26 85.99 .47 1.69

Dongil Kim, Boong-nyun Kim, Kijyung Lee, Joong-kyu Park, Sungdoo Hong, Hyoungsoo Kim
G
418
The findings revealed that cognitive strategies had a
significantly large effect size (.82-1.69). Moreover, cognitive
learning strategies were very effective for average achieving
and Learning Disabilities together (.82-1.42). The effect of
cognitive learning strategies was very large for students in
all grades (1.02-1.34), except for middle school students.
The effect size for middle school students had a moderate
effect size (ESsm = .70).
The present study focused on the cognitive learning
strategy, which turned out to be similar to the previous study
in Korea (Kim, Shin, & Hwang, 2002). The previous study
in strategy instruction dealt with the whole package of
learning strategies including cognitive learning strategy,
which was designed to enhance motivation, self-efficacy,
and to improve strategies for test skills and self-management.
A plausible conclusion about the effects of the various
types of cognitive learning strategies was that, in general,
cognitive learning strategies were quite effective, even
though the effective sizes of cognitive learning strategies for
middle school students were still moderate. Additionally, the
results indicated that all of the subtypes of cognitive learning
strategies were effective interventions in the applied
domains for both average achieving students and those with
Learning Disabilities.
The present study indicated that cognitive learning
strategies would be effective for all grade levels. However,
the effect sizes among grade levels were not homogenous,
which indicates the effect sizes among grade level could be
different. From this finding, we need to emphasize our
understanding of learner’s cognitive developmental stages.
Moreover, elaborate strategy as a cognitive skill was
regarded to be voluntarily used after middle school ages.
Considering the complexity of connecting two or more items
of information, a learner is old enough to have the ability to
enhance and integrate the meaning of given information and
also have background knowledge (Pressley, 1986; Song,
2000). However, the results of this study suggested that
learners in the intermediate grade level of elementary school
could adopt learning strategies efficiently as well as
voluntarily.
Further studies are in order to analyze the reasons why
the effect sizes for middle school students were smaller than
the other grade levels. This finding suggested that early
interventions of learning strategies in the elementary level
might be very helpful later on. Given the small number of
subjects in the lower elementary school and college students,
one must be cautious in drawing any broad conclusions. To
sum up, the results of the study indicated the following
implications: First, this study confirms that most of the
cognitive learning strategies are effective across a range of
diverse learners and can be applied to different subject
matter. Second, early interventions using learning strategies
could be very effective and it is a recommended practice for
both teachers and students.
References
Bos, C. S., & Anders, P. L. (1990). Effects of interactive
vocabulary instruction on the vocabulary learning and
reading comprehension of junior-high learning disabled
students. Learning Disability Quarterly, 12(1), 31-42.
Chan, L. K. S., & Cole, P. G. (1986). The effects of
comprehension-monitoring training on the reading
competence of learning disabled and regular class
students. Remedial and Special Education, 7, 33-40.
Cohen, J. (1988). Statistical power analysis for the
behavioral sciences (2nd ed.). New York: Academic
Press.
Cooper, H., & Hedges, L. V. (1994). Research synthesis as a
scientific enterprise. In H. Cooper & L. V. Hedges
(Eds.), The handbook of research synthesis (pp. 3-16).
New York: Russell Sage Foundation.
Dansereau, D. F. (1985). Learning strategy research. In J.
Segal, S. Chipman, & R. Glaser (Eds.), Thinking and
learning skills: Relating instruction to research (Vol. 1).
Hillsdale, NJ: Erlbaum.
Deshler, D. D., & Schumaker, J. B. (1986). Learning
strategies: An instructional alternative for low-
achieving adolescents. Exceptional Children, 52(6),
583-590.
Devine, T. G. (1987). Teaching study skills: A guide for
teachers (2nd ed.). Boston: Allyn & Bacon.
Ellis, E. S., Lenz, B. K., & Saborine, E. J. (1987a).
Generalization and adaptation of learning strategies to
natural environments: Part 1: Critical agents. Remedial
and Special Education, 8(1), 6-20.
Ellis, E. S., Lenz, B. K., & Saborine, E. J. (1987b).
Generalization and adaptation of learning strategies to
natural environments: Part 2: Research into practice.

Meta-analysis on Cognitive Learning StrategiesG
419
Remedial and Special Education, 8(2), 6-23.
Hedges, L. V., & Olkin, I. (1985). Statistical methods for
meta-analysis. Orlando: Academic Press.
Kim, D. (1998). Counseling on the academic development.
Encyclopedia on Education, Seoul: Hawoo.
Kim, D., Shin, E., & Hwang, A. (2002). A meta analysis on
learning strategy. Asia Journal of Education, 7(3), 53-
76.
Mckeachie, Wilbert J., Pintrich, P. R., Lin. Y., & Smith, D.
A. F. (1991). Teaching and learning in the college
classroom. Review of the Research Literature.
University of Michigan: MCRITAC.
Moon, S., & Bae, H. (1995). Effects of text structure/
summarization training on expository text processing.
The Journal of Education Research, 33(5). 21-43.
Pressley, M. (1986). The relevance of the good strategy user
model to teaching of mathematics. Educational
Psychologist, 21, 39-161.
Song, M. (2000). Developmental psychology. Seoul: Hakjisa.
Stanovich, K. E., & Siegel, L. S. (1994). The phenotypic
performance profile of reading-disabled children: A
regression-based test of the phonological-core variable
difference model. Journal of Educational Psychology,
86, 24-53.
Swanson, H. L. (1993). Working memory in learning
disability subgroups. Journal of Experimental Child
Psychology, 56, 87-114.
Swanson, H. L., & Alexander, T. E. (1997). Cognitive
processes as predictors of word recognition and reading
comprehension in learning-disabled and skilled readers:
Revisiting the specificity hypothesis. Journal of
Educational Psychology, 89(1), 128-158.
Swanson, H. L., & Hoskyn, M. (1998). Experimental
intervention research on students with learning
disabilities: A meta-analysis of treatment outcomes.
Review of Educational Research, 68, 277-321.
Swanson, H. L., & McMahon, C. M. (1996). Synthesis of
intervention research for students with learning
disabilities. Unpublished paper, University of
California-Riverside.
Torgesen, J. K. (1977). Memorization processes in reading
disabled children. Journal of Educational Psychology,
69, 571-578.
Torgesen, J. K. (1982). The learning-disabled child as an
inactive learner: Educational implications. Topics in
Learning and Learning Disabilities, 2, 45-52.
Weinstein, C. E., & Mayer, C. (1986). The teaching of
learning strategies. In M. C. Wittrock (Ed.), Handbook
of research on teaching. American Education Research
Association.

Dongil Kim, Boong-nyun Kim, Kijyung Lee, Joong-kyu Park, Sungdoo Hong, Hyoungsoo Kim
G
420
Appendix. The list of the articles in the present study
Bae, J., & Park, H. (2001). The effect of schema based
cognitive-metacognitive strategy instruction on solving
instruction on solving mathematical word problems for
students with mathematical learning disabilities. The
Journal of Special Education, 36(3), 1-20.
Byun, H., & Ryu, H. (1995). The effects of elaborative-
interrogation and prior-knowledge on learning of facts.
Educational Review in Chonbuk University, 40, 1-13.
Choi, B. (1999). Effects of teacher-directed strategies
instruction and interactive strategies instruction on
reading comprehension, metacognition, and self-
efficacy of students with learning disabilities. The
Journal of the Research Institute of Korean Education,
12, 51-73.
Choi, C (1996). The effects of the semantic networking
learning strategies on the structural knowledge in the
hypertext learning environment. Research in
Educational Psychology, 10(2). 261-285.
Choi, S. (2002). The effects of strategy training on the
mathematical word problem solving and self-efficacy of
middle and high school students with learning
disabilities. The Journal of Special Education, 9(1).
221-239.
Choi, S. (2001). Effects of attributional training using
cognitive and metacognitive strategies on attribution,
emotion and mathematical word problem solving. The
Journal of Special Education, 8(2). 195-220.
Han, O., & Park, H. (1997). The effects of problem-solving
learning applied strategic problem-posing on the
achievement in mathematics. Proceedings of
Mathematical Education, 6, 337-356.
Han, S. (1997), The effect of reading strategy, metacognition,
motivation on text comprehension. The Journal of
Educational Research, 35(1), 83-104.
Hwang, B. (1998). The effects of the concept mapping as an
instructional strategy in geography education- An
experiment for the instructional unit of urban
geography. The Journal of Geography Education. 39,
1-15.
Hwang, H. (1994). The effect of metacognitive learning
strategy on its application and reading comprehension.
The Journal of Educational Research in Pusan, 7(12),
127-157.
Hwang, H. (1999). Developing learning strategy program
and its' effect on academic achievement for college
students. Journal of Student Guidance Research, 10(1),
7-24.
Hwang, H. (2001). The effects of embedding approach for
the improvement of critical thinking ability. The
Journal of Educational Research, 39(3), 187-214.
Jeon, S., & Kim, Y (2001). Effects of instruction of volition
strategies on academic achievement, self-efficacy of
social studies. Research in Educational Psychology,
15(4), 463-480.
Jung, K., & Park, H. (2001). The effects of student-initiated
cognitive mapping on reading comprehension and
reading strategy skills of elementary students with
reading disability. Journal of Speech & Hearing
Disorders, 6(2), 406-427.
Jung, Y., & Lee, Y. (2001). The effects of meaningful
learning on students` learning orientation in middle
school biology class: Utilizing concept maps. Journal
of the Korean Association for Research in Science
Education, 21(3), 580-589.
Kang, B. (2001). The effects of the cognitive level based
constructive instruction - learning strategies on the
problem - solving abilities in the hypermedia learning
environment. The Journal of Educational Research,
19(3), 285-312.
Kang, B. (2003). The effects of situation-based instruction
strategies on children's academic attitude and
achievement of natural science. The Journal of the
Research Institute of Korean Education, 18, 101-114.
Kang, H., Ha, J., & Kim, N. (1996). The effects of learning
through concept mapping on elementary school science
achievement and creativity. Elementary Science
Education, 15(2), 191-206.
Kang, K., & Lee, J. (1999). The Effects of Elaboration on
Memory. Educational Psychology Research, 3(1), 1-20.
Kil, H., & Baek, S. (1997). The effects of metacognition
strategy on the conceptual change of mass conservation.
Chemical Education, 24(4), 187-201.
Kim, A. (1996). The effects of metacognition training on
children's attributional style and ability of solving
problem. The Journal of Educational Research.10(2),
25-52.

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421
Kim, J. (1997). The effects of the training for generative
process of reading comprehension on reading skills.
The Journal of Educational Research, 35(5), 87-113.
Kim, J. (2004). The impact of cognitive strategy-based
instruction on student achievement. Journal of
KAHPERD, 43(3), 229-243.
Kim, Y. (1996). The effects of self-regulating strategy
instruction and metacognition on children's writing
performance. The Journal of Educational Research,
34(5), 97-119.
Kim, Y. (1998). The effects of mind mapping note method
on the memory and understanding of children. The
Journal of Educational Research, 36(4), 281-308.
Kim, Y., Shin, S., & Lee, S (2003). The study on the effect
of concept maps teaching strategy on the elementary
school children. Journal of research in Science
Teaching, 27, 115-127.
Kwak, N., Park, H., & Kang, B. (2000). The effects of
constructivist instruction strategies on children
academic attitude and self-efficacy of natural science.
The Journal of Korea elementary education, 42, 339-
362.
Lee, E. (1997). The effect of graphic organizer strategy map
on reading. The Society of Chongnan Language &
Literature, 19, 123-149.
Lee, J. (1995). Effects of learning strategies training on
mathematics achievement, self-regulation, impulsivity,
and self-efficacy of the learning disabled. The Journal
of Educational Research, 33(3), 179-205.
Lee, J. (1996). The effects of self-instruction and
attributional training on mathematics achievement and
self-efficacy of middle school students with learning
disabilities. The Journal of Educational Research, 34(5),
233-254.
Lee, J. (2000). The effects of transactional comprehension
strategies instruction on children's reading comprehension
metacognition. The Journal of Educational Research in
Pusan, 13(1), 21-48.
Lee, J., & Heo, M. (1995). The effect of concept map on the
attitude of science class and academic achievement.
Journal of the Korean Association for Research in
Science Education, 15, 223-232.
Lee, M. (2000). The effect of learning strategy on the
strategy application and self- efficacy of underachiever.
Student Guidance Center in Chongju National University
of Education, 8, 80-90.
Lee, S. (2002). The achievement level effects of
constructivism instructional design on mathematics
achievement and learning attitude. Research in
Educational Psychology, 16(1), 123-139.
Moon, B. (2000). The effects of self regulated learning
strategy training on children`s academic performance.
The Journal of Education Research, 20(2), 61-76.
Moon, B. (2000). The effects of self-regulated learning
strategy training on mathematical word problem
performance in relation to level of self-efficacy. The
Journal of Korea Elementary Education, 13(2), 101-
116.
Moon, S., & Bae, H. (1995). Effects of Text Structure/
Summarization Training on Expository Text Processing.
The Journal of Education Research, 33(5), 21-43.
Moon, S., & Cho, H. (1993). Effects of Keyword Strategy on
English Word Learning. Journal of Secondary
Education Research, 5, 87-116.
Moon, S., & Lee, H. (1998). Effects of Question-generation
Training on Comprehension of Expository Text.
Journal of Secondary Education Research, 10, 204-231.
Moon, S., & Park, J. (1999). Effects of Headings/Outlines
Training on Text Learning. Journal of Secondary
Education Research, 11, 382-412.
Na, D., Lee, J., & Jang, T. (1994). The effects of keeping a
daily learning log on learning strategies use,
motivational beliefs, and achievement of learning
disabled learners. Educational Review in Chonbuk
University, 14, 17-32.
No, T., Jang, S., & Lim, H. (1998). The instructional
influences of metacognitive learning strategies in
elementary school science course. Journal of the
Korean Association for Research in Science Education,
18(2), 173-182.
No, T., Kim, C., & Kwon, H. (1999). The effect of clarified
mapping strategy and placement of analog on middle
school students' conceptual understanding in science.
Journal of the Korean Association for Research in
Science Education, 19(1), 107-116.
Park, B (1996). The effects of structured strategy and reward
of cooperative learning in literal comprehension
learning and inferential comprehension learning.
Research in Educational Psychology, 10(3), 39-66.
Park, C., & Park, H. (2003). The effect of the ARCS model
Meta-analysis on Cognitive Learning StrategiesG

422
of Keller for students' achievement and self-concepts in
elementary school. The Journal of Korea Elementary
Education, 16(2), 237-252.
Park, J., & Jang, N. (1998). The effect of 'Cognitive
Restructuring Strategy' for the enhancement of self-
esteem. Environmental Education, 12, 237-249.
Park, Y., & Choi, B. (2003). Effect of reading strategy
instructions on metacognition and reading
comprehension. Research in Educational Psychology,
17(1), 167-186.
Shim, H., & Jung, J. (2003). The effects of self-regulated
learning strategy training for reading underachievers in
elementary school. Educational Development Review,
24(1), 105-134.
Shin, D., Park, J., & Joo, H. (1998). The effectiveness of
concept mapping on elementary science education. The
Journal of Curriculum Studies, 16(1), 399-416.
Shin, M., Ko, Y., & Choi, Y. (2000). The effectiveness of
metacognitive instruction model on the changes of
molecular concepts. Elementary Science Education,
18(2), 61-73.
Received June 5, 2007
Revision received February 22, 2008
Accepted October 30, 2008
Dongil Kim, Boong-nyun Kim, Kijyung Lee, Joong-kyu Park, Sungdoo Hong, Hyoungsoo Kim