Recibido: 12-07-20=
19/
Revisado: 20-07-2019/Aceptado: 15-08-2019/ Publicado: 06-09-2019
The effects of cooperative
learning on reading comprehension
The Effects of
Cooperative Learning on Reading Comprehension
Noemi Mercedes
Remache Carrillo. [1],
Mariela Germania Pilco Labre. [2],
Viviana Vanessa Yanez Valle. [3]
This study aimed to determine the influence of cooperative learning in
reading comprehension of high school students at Unidad Educativa
“Riobamba” during 2017-2018 school period. For the assessment of the validi=
ty
and effectiveness of this research, a pre-test and a post-test were applied
based on the Cambridge PET (Preliminary English Test) exam, reading section.
That exam was composed of two parts: the first was carried out through a
cooperative work in pairs and the second part, taking into consideration the
cooperative work in groups of four students. A didactic guide for the teach=
er
was designed and applied in the classroom. After that, the analysis of data=
was
made before and after applying the intervention. The teacher's guide was
designed to put cooperative learning strategies such as jig-saw, think-pair=
-share,
and reciprocal questioning into action. Three stages of reading were used
namely before reading, during reading, and after reading. After the impleme=
ntation
of the proposal, the data analysis was performed using the T-student
mathematical test. It is concluded that the students improved their reading
comprehension through cooperative work in pairs and in groups as well. It w=
as
recommended that teachers practice cooperative learning in the classroom to
improve students' reading comprehension in order to optimize their developm=
ent
in English language learning.
Keywords: Cooperative learning, effects, reading comprehension, strategies
Introduction.
Reading comprehension is an important issue in English classes. However, it is not seemed as completely
developed for students. Therefore, it is important to analyze what happens =
in
the world, in Ecuador, and at Unidad Educativa =
“Riobamba”.
Marzbana
At Unidad Educativa “Riobamba”, there is =
an
important report which states that levels of reading comprehension are under
the 50% of performance. It is alarming because 378 students of third of
Reading comprehension is a fundamental aspect of language development.
However, a number of English teachers are interested in helping students to
complete worksheets rather than providing reading strategies to improve
comprehension (Adnyana, 2014). Fitria
(2015) states that “English teachers do not use appropriate techniques or
methods; therefore, it gives impact to the students and the class condition
during teaching and learning process”. Consequently, the teachers' role is =
to
help students to understand what they read (Fitria,
2015). That is the reason why the present research is interesting, importan=
t,
newfangled, helpful, and feasible.
This research is interesting for teachers and students because teache=
rs
want to improve their teaching strategies and be prepared for helping stude=
nts.
Felder and Brent (2013) argue that cooperative learning helps to minimize
unpleasant situations when students cooperatively work and maximize learning
and satisfaction when they are working in groups; consequently, students and
teachers have higher performance when working in teams. Therefore, the pres=
ent
research is interesting because teachers have valuable information to
understand the use of cooperative learning in the development of reading
comprehension. Hence, the current
research looks for effective activities and resources which help for enhanc=
ing
reading comprehension development.
Furthermore, the present work is relevant. Although the terms, reading
comprehension and cooperative learning are well known in the educational fi=
eld,
the fusion of these two terms can be used to foster Ecuadorian teaching
practices. It will help teachers because comprehension is showed by students
when they can remember important aspects of the reading material, and the
number of questions they can answer correctly. On the other hand, quality of
comprehension is understood based on the rank to which students answer
comprehension questions at inference making levels
Besides, the current study is feasible. This research is focused on
students from Unidad Educativa “Riobamba” since=
they
struggle with reading comprehension. Therefore, it is extremely necessary to
help them to solve these problems for improving their English knowledge.
It is fundamental to describe
literature review related to cooperative learning on reading comprehension =
in
order to understand the research problem.
Johnson, Johnson, and Stanne (2000) claim
cooperative learning is one of the most helpful, extended and fruitful area=
s of
theory, research, and practice in the educational field. The methodology
adopted for this research is a meta-analysis which consists of a literature
review and the calculation of effect sizes in a statistical combination of
results that test the same hypothesis. It also uses inferential statistics =
to
draw conclusions about the general result of the research. This meta-analys=
is
is centered on answering four main questions such as 1) how much investigat=
ion
has been addressed on cooperative learning methods, 2) how many different
cooperative learning methods can be assessed, 3) how effective each method
assessed is in the best student achievement, and 4) what the features of the
most effective cooperative learning methods are. According to the authors, =
164
studies have been found which are investigating eight cooperative learning
methods. Those studies showed the same number of independent effect sizes w=
hich
represent significant and positive academic achievements. They compared
cooperative learning with competitive learning. The results of the research
show that cooperative learning promoted the greatest effect rather than
competitive learning. They used academic controversy,
student-team-academic-divisions, team-games tournaments, group investigatio=
n,
jigsaw, and teams-assisted methods of cooperative learning, cooperative
integrated reading, and composition. They conclude that cooperative learning
has a greater impact than individualistic learning.
Millis (2002) states that enhancing critical thinking, promoting deep
learning, encouraging self-esteem and acceptance of others, and improving
interpersonal skills are the most challenging educational goals. This paper
main objective is describing cooperative learning which is an instructional
approach developed to enhance the challenging educational goals such as
critical thinking skills, deep learning, encourage self-esteem and acceptan=
ce
of others, and improve interpersonal effectiveness. The author argues that =
cooperative
learning involves working with small groups on particular tasks which are
painstakingly structured. She has developed a guide based on cooperative
learning premises which discusses issues about cooperative learning classro=
om,
activities, groups, and teams. The author concludes that teachers who
understand the investigation and theory of cooperative learning and classro=
om
management can apply them in their classes and in any curriculum. For that
reason, learning is better for students who enjoy attending classes and
contribute with their classmates.
Learning techniques are used to teach according to different learning
conditions like students’ abilities, material, and assessment. They can be
practice testing which refers to practice answering quizzes about the topic=
of
lessons. Other learning techniques can be self- explanation, interrogation,=
and
summarizing, identifying and marking significant content in determined text,
determine new vocabulary, create mind maps, reading material various times =
(Henetz, 2013).
It is an instructional issue based on groups: formal and informal gro=
ups;
where interpersonal skills build up social interaction through elements lik=
e face
to face interaction, interdependence, accountability (Johnson & Johnson,
1987); and collaborative skills, with techniques like jigsaw, and reciprocal
questioning, and think-pair-share approach, for decision making, communicat=
ion,
and conflict management.
Cooperative learning promotes cooperative and collaborative work in
groups. There is not just an only one form of using groups. Grouping can be
distributed by the teacher to be either homogeneous or heterogeneous on the=
ir
characteristics. Or students can also self- select their group forming. Tho=
se
groups can be formal or informal (Garfield, 1993).
Jacobs and Hall (2002) state that even two people can be considered a=
s a
group. Groups of three or maximum four members are the best because the gro=
up
is large enough to allow students to come up with their own opinions,
experiences, and even learning styles. The members of the group tend to help
each other in solving problems. Additionally, even if one student is absent,
the rest of the group can continue working (Millis, 2002). Groups of four are also considered as
appropriated for developing big tasks. For these groups, pair work is devel=
oped
first and then the two pairs interact with one another.
Slish (2005) remarks th=
at
jigsaw helps in the classroom for developing active learning. Students are
engaged with the provided material. Students cooperate in groups for
accomplishing the same goal. Classes are dedicated to active learning
exercises. These help students to read, understand, and learn the material =
in a
better way. In jigsaw; every single student who is member of a team is assi=
gned
a unique part of the reading material (Meng, 2010). The student reads his or
her part and forms another group of students who have the same reading
material. They form the group of “experts” to discuss, share and clear idea=
s,
and master information. After that, students return to their original group=
in
order to teach the rest of the group about what they have read. Finally, the
whole group is assessed based on the reading material. Jigsaw is suitable f=
or
reading comprehension because it develops students’ meta-cognitive awareness
and let them learn the content when they are teaching to their peers in the=
ir
groups.
Causes are reasons why something happens; on the contrary, an effect =
is
what happens because of that cause. To recognize if the reading material ha=
s a
“cause and effect” pattern, it is necessary to pay attention to the signal
words and phrases that the reading material provides to the reader. Those
signal words and phrases can be: ‘for this reason’, ‘thus’, ‘since’, ‘in or=
der
to’, ‘as a result’, ‘therefore’, ‘consequently’, ‘because’, ‘due to’, ‘for =
this
reason’, and ‘on account of’. It is also necessary to design graphic organi=
zers
in order to understand the ‘cause and effect’ p=
attern
(Perles, 2018).
Methodology
This research is focused on the social educational model. In fact,
students are motivated to learn English by working with their pairs. Hence,
cooperative learning for enhancing reading comprehension is part of the
students’ daily life. According to the Ministry of Education students have =
to
reach a B1.2 level in Ecuador. Therefore, it is imperative the necessity to
improve reading skills. A quali-quantitative ap=
proach
has been used in this research
It is essential to have direct contact with students, teachers, and
authorities where the problem occurs
Synchronic research was carried out during the second term of 2017-20=
18
academic year with first year of bachillerato of
Riobamba High School in Riobamba city, Chimborazo province
This research has contributed to the solution of a social- educational
problem which is affecting students
The independent variable (Cooperative Learning) affects the dependent
variable (Reading comprehension). There is a close relationship between them
because they support each other
For this study, the researcher has worked with ten English teachers w=
ho
assist students at Unidad Educativa “Riobamba”.
Besides, the population includes students from first year of bachillerato in the second term of 2017-2018 academic=
year.
Furthermore, the present work has a population of 211 students; therefore, =
the
researcher has worked with the total of the population which is detailed in
Table 1.
Table =
1. =
Popul=
ation
and sampling
|
CLASSROOM |
MEN |
WOMEN |
TOTAL |
GROUP |
|
A |
4 |
26 |
30 |
EXPERIMENTAL
GROUP |
|
B |
6 |
31 |
37 |
|
|
C |
7 |
28 |
35 |
|
|
D |
8 |
28 |
36 |
CONTROL
GROUP |
|
E |
10 |
26 |
36 |
|
|
F |
9 |
28 |
37 |
|
|
TOTAL |
44 |
167 |
211 |
|
Source:
Unidad Educativa “Riobamba” (2018)
Created by: Pilco, M. (2018)
The data of the present research was gathered through organizing and
explaining information about cooperative learning on reading comprehension =
(Adnyana, 2014). The data has been directed to answer =
the
stated problem through a quasi-experimental research. For this purpose, a p=
re
and a post-test, PET exam from Cambridge, reading section, were used. The
researcher assisted 211 students in total that were divided into the
experimental group which had 102 students and the control group which had 1=
09
students who come from Unidad Educativa “Riobam=
ba”.
After giving the pre-test, the researcher developed a class intervention
through the use of cooperative learning for reading comprehension methodolo=
gical
guide for one month. After the intervention, data was collected in order to
accept or reject the corresponding hypotheses. Additionally, a survey was
applied to both English teachers and students. It was validated by two
professionals in teaching English as a foreign language.
Results
Pre-
Test and Post- Test Results
This study assisted to both control and experimental group; the former
was composed by 109 learners and the latter was composed of 102 students wh=
ich
belonged to first year of bachillerato at Unida=
d Educativa “Riobamba” in the second term of 2017-2018
academic period.
Both the control group and the experimental one took the same pre-tes=
t,
PET exam from Cambridge, in order to assess their reading comprehension ski=
lls.
The first part of the exam aimed to evaluate their work in pairs and the se=
cond
part of it was designed in order to evaluate their group work. The exam was
divided into two sets. The first part had a duration of 30 minutes and the
classes were divided into pairs to read a 3 short pieces of reading which h=
ad
one multiple choice question each one. Additionally, the second part of the
test had duration of other 30 minutes and the classes were divided into gro=
ups
of 4 students to read and answer a longer piece of reading that contained 5
questions. The same structure but different readings and questions were
selected for the post-test, PET exam from Cambridge. For this reason, the d=
ata
analysis of the pre and post-tests were divided into two parts: the first o=
ne
is the analysis of the students reading comprehension development when they
worked in pairs and the second part of the analysis aimed to study the
students’ results when working in groups of four.
Table 2. Pre a=
nd
post-tests results: pair work
|
Pre and post test results – Experime=
ntal
and Control groups: pair work |
||
|
Category |
Pre - test |
Post – test |
|
Experimental group: pair work |
2,04 |
4,44 |
|
Control group: pair
work |
1,74 |
2,93 |
Source: Pre
and post-tests results. Experimental and control groups: pair work
Author: Pilco,
M. (2018)
=
Figure 1. Pre a=
nd
post-tests results: pair work
Source: Pre
and post-tests results. Experimental and control groups: pair work
Author: Pilco,
M. (2018)
This study aimed to prove whether the effects of cooperative learning influence on reading comprehension or not. Therefore, the alternative hypothesis aimed to prove that the effects of cooperative learning do influ= ence on reading comprehension; on the contrary, the null hypothesis stated the effects of cooperative learning do not influence on reading comprehension.<= o:p>
For the hypothesis verification, SPSS statistical software was used in
order to apply the T- student.
Normal
distribution test
Table 3. Normal distribution test:
experimental work
|
EXPERIMENTAL GROUP |
||
|
Kolmogorov-=
Smirnov
test for one dataa |
||
|
|
PRE-TEST |
|
|
N |
50 |
|
|
Normal parametersb,c |
Mean=
|
2,040 |
|
Std. Deviat=
ion |
1,5903 |
|
|
Most extreme
differences |
Absolute |
0,230 |
|
Positive |
0,230 |
|
|
Negative |
-0,210 |
|
|
Test statis=
tic |
0,230 |
|
|
Asip.Sig. (2 tailed) |
0,000d=
|
Source: Pre-test
experimental group
Author: Pilco,
M. (2018)
Table 4. Normal distribution pre-test
control group
|
CONTROL GROUP |
||
|
Kolmogorov-=
Smirnov
test for one dataa |
||
|
|
PRE-TEST |
|
|
N |
54 |
|
|
Normal parametersb,c |
Mean=
|
1,741 |
|
Std. Deviat=
ion |
1,5070 |
|
|
Most extreme
differences |
Absolute |
0,228 |
|
Positive |
0,228 |
|
|
Negative |
-0,216 |
|
|
Test statis=
tic |
0,228 |
|
|
Fsip. Sig. (2 tailed) |
0,000d=
|
Source: Pre-Test
Control group
Author: Pilco,
M. (2018)
P.sig < 0.05
For the normal distribution of data as the experimental group as for =
the
control group the Kolmogorov-Smirnov test for one data was applied.
Hence, p.sig that corresponds for these
results, is 0.000 and it is less =
than
0.05; therefore, the data that comes from the experimental group and the
control group are normal like as the tables above show.
These results mean that the researcher can continue with the next test
which is T student for comparing population means.
T –
Student test for comparing population means
Ta=
ble 5.
Student test. Comparing population means, pre-test
|
Group statistics |
|||||
|
=
|
GROUP=
|
N |
Mean=
|
Standard
deviation |
Standard error mean |
|
PRE-TEST |
EXPERIMENTAL |
50 |
2,040 |
1,5903 |
,2249 |
|
CONTROL |
54 |
1,741 |
1,5070 |
,2051 |
Source: T-Test.
Comparing population means. Pre-test
Author: Pilco,
M. (2018)
Ta=
ble 6.
Leven=
e test for equality. Pre-test<=
/span>
|
Independent samples T-test |
||||||||||
|
|
Levene test for
equality |
T- test for equality of means<=
/b>=
|
||||||||
|
F |
Sig.=
|
T |
gl |
Sig.(two ta=
iled) |
Mean differ=
ence |
Standard er=
ror
difference |
95% Confide=
nce
interval of the difference=
|
|||
|
Inferior |
Superior |
|||||||||
|
PRE-TEST |
Equal variances assumed |
0,063 |
0,802 |
0,985 |
102<=
span
lang=3DEN-US style=3D'font-size:10.0pt;line-height:150%;font-family:"Aria=
l",sans-serif;
mso-ansi-language:EN-US'> |
0,327 |
0,2993 |
0,3037 |
-0,3032 |
0,9017 |
|
Equal variances not assummed |
|
|
0,983 |
100,271 |
0,328 |
0,2993 |
0,3044 |
-0,3046 |
0,9031 |
Source: T-test. Comparing population means. Pre-test
Author: Pilco,
M. (2018)
In the Levene test for equality of varian=
ces,
it is clearly assumed that the Sig. is > 0.05; in this case, it is 0.802.
Therefore, it is needed to say that equal variances are assumed because the=
re
are high differences between the two populations’ variances.
Furthermore, the T-test
table shows that the Sig. is 0,327 which is > 0.05; therefore, there is a
difference between the mean in the control group and the mean in the
experimental group. In other words, the mean of experimental group is higher
than the mean of the control group in the pre-test.
T-
Test
The final T- test aimed to verify whether there is a significant
difference between the means of the control group and the experimental one =
in
the post-test. This hypothesis is planted because the alternative hypothesi=
s in
this study refers that the effects of cooperative learning influence on rea=
ding
comprehension development. Since the researcher has implemented a class
intervention based on cooperative learning for improving reading comprehens=
ion,
it is needed to see if the intervention has had good results or not.
The
hypothesis is:
µ1 ≠ µ2
The formula signifies that the mean in the exper=
imental
group, G1, is not the same as the mean in the control group, G2.
Table 7. T-test. Group statistics.
Post-test
|
Group statistics |
|||||
|
|
GROUP |
N |
Mean=
|
Standard
deviation |
Standard er=
ror
mean |
|
POST-TEST |
EXPERIMENTA=
L |
50 |
4,440 |
1,3577 |
,1920 |
|
CONTROL |
54 |
2,926 |
1,4902 |
,2028 |
Source=
: T-Test. Group statistics. Post-test
Author: Pilco, M. (2018)
Table 8. Compa=
ring
population means. Post-test
|
Independent samples T-test |
||||||||||
|
|
Levene test for
equality |
T- test for equality of means |
||||||||
|
F |
sig<=
span
lang=3DEN-US style=3D'font-size:10.0pt;line-height:150%;font-family:"Aria=
l",sans-serif;
mso-ansi-language:EN-US'> |
t |
Gl |
Sig.(two
tailed) |
Mean differ=
ence |
Standard er=
ror
difference |
95% Confide=
nce
interval of the difference=
|
|||
|
Inferior |
Superior |
|||||||||
|
POST-TEST |
Equal variances assumed |
2,407 |
0,124 |
5,402 |
102<=
span
lang=3DEN-US style=3D'font-size:10.0pt;line-height:150%;font-family:"Aria=
l",sans-serif;
mso-ansi-language:EN-US'> |
0,000 |
1,5141 |
0,2803 |
0,9581 |
2,0700 |
|
Equal variances not assummed |
|
|
5,422 |
101,976 |
0,000 |
1,5141 |
0,2793 |
0,9601 |
2,0680 |
Source: Independent samples T- test. Post-test
Author: Pilco,
M. (2018)
Final decision=
In the Levene
test for equality, it is shown that sig.
is > 0.05 that is 0.124. It imp=
lies
that the variances are statistically equal.
On the other hand
with a standard of error mean of 0, 1920 it is concluded that there is a high differ=
ence
between the means of the µ1 with respect to µ2. G1 or experimental group=
had a
final mean of 4.440 which is higher than the result of the G2 or control gr=
oup
that obtained a final mean of 2.926.
In
conclusion, the alternative hypothesis is accepted and the null hypothesis is
rejected. Furthermore, the researcher’s intervention with the proposal “A
methodological guide with cooperative learning activities for improving rea=
ding
comprehension development” had a good impact in the students of first of
As
it was detailed in the previous numeral, the pre- and post-tests had two
sections. The first section was developed by students in pairs and the other
part was performed in groups of four students. This second section had one =
long
piece of reading with 5 multiple choice questions. The students had to 30
minutes to read, analyze, and answer the questions.
For the analysis of data, =
the
researcher has used the same scheme that in the first part. It means that S=
PSS
statistical software was used for obtaining the normality T- test, equality=
of
variances, contrast and compare of the pre-and post-test results through T –
student, and final decision.
Data obtained for the group work
Ta=
ble 9.
Group work. General results
|
GROUP WORK |
||||
|
|
EXPERIMENTAL
GROUP |
CONTROL
GROUP |
||
|
PRE-TEST |
POST-TEST |
PRE-TEST |
POST-TEST |
|
|
GROUP 1 |
2 |
6 |
2 |
4 |
|
GROUP 2 |
4 |
6 |
4 |
2 |
|
GROUP 3 |
4 |
2 |
0 |
4 |
|
GROUP 4 |
6 |
10 |
2 |
0 |
|
GROUP 5 |
2 |
8 |
2 |
2 |
|
GROUP 6 |
0 |
8 |
6 |
6 |
|
GROUP 7 |
0 |
8 |
0 |
0 |
|
GROUP 8 |
2 |
4 |
0 |
2 |
|
GROUP 9 |
2 |
10 |
4 |
2 |
|
GROUP 10 |
2 |
6 |
2 |
4 |
|
GROUP 11 |
4 |
6 |
2 |
2 |
|
GROUP 12 |
2 |
10 |
4 |
4 |
|
GROUP 13 |
2 |
10 |
2 |
2 |
|
GROUP 14 |
4 |
8 |
0 |
2 |
|
GROUP 15 |
0 |
6 |
0 |
4 |
|
GROUP 16 |
4 |
8 |
0 |
4 |
|
GROUP 17 |
4 |
10 |
4 |
0 |
|
GROUP 18 |
0 |
8 |
6 |
4 |
|
GROUP 19 |
0 |
6 |
0 |
2 |
|
GROUP 20 |
2 |
6 |
6 |
2 |
|
GROUP 21 |
4 |
6 |
0 |
0 |
|
GROUP 22 |
4 |
2 |
0 |
2 |
|
GROUP 23 |
2 |
10 |
0 |
6 |
|
GROUP 24 |
4 |
6 |
4 |
4 |
|
GROUP 25 |
2 |
8 |
4 |
0 |
|
Average |
2.48 |
7.12 |
2.16 |
2.56 |
Source: General results. Group work=
Author: Pilco, M. (2018)
Normality
distribution test
To prove the hypothesis of
data normality, the Kolmogorov-Smirnov test was used because this test help=
s to
prove that the sample data come from a normal distribution.
In SPSS statistical softwa= re the following steps were followed: First, the researcher had to segment dat= a, then she had to apply KS T-test for one sample, and finally the analysis of= F.sip. Significant. As the table above shows, the F. significant is < 0.05; therefore, data of the experimental group come from a normal distribution.<= o:p>
Table 10. Norma=
lity
T-test. Experimental group work
|
EXPERIMENTAL GROUP |
||
|
Kolmogorov-=
Smirnov
test for one dataa |
||
|
|
Pre-test |
|
|
N |
25 |
|
|
Normal parametersb,c |
Mean=
|
2,48=
|
|
Std. Deviat=
ion |
1,661 |
|
|
Most extreme
difference |
Absolute |
0,220 |
|
Positive |
0,214 |
|
|
Negative |
-0,220 |
|
|
Test statis=
tic |
0,220 |
|
|
Fsip. Sig. (2 tailed) |
0,003d=
|
Source: Pre
-test results. Experimental group: group work
Author: Pilco,
M. (2018)
Ta=
ble 11.
Normality test group work. Control group<=
/i>
|
CONTROL
GROUP |
||
|
Kolmogorov-=
Smirnov
test for one dataa |
||
|
|
PRE-TEST |
|
|
N |
25 |
|
|
Normal parametersb,c |
Mean=
|
2,16=
|
|
Std. Deviat=
ion |
2,154 |
|
|
Most extreme
differences |
Absolute |
0,242 |
|
Positive |
0,242 |
|
|
Negative |
-0,164 |
|
|
Test statis=
tic |
0,242 |
|
|
Fsip=
. Sig. (2
tailed) |
0,001d=
|
Source: Pre
-Test results. Experimental group: group work normality test
Author: Pilco,
M. (2018)
In the same way, =
the Kolmogorov-Smi=
rnov
test for one data was applied for the control group, and the res=
ult
is that data come from a normal distribution because the F.sip.sig
is < 0.05.<=
/span>
The next step is =
to
apply the T-student in order to compare the population means.=
T- =
Student
This test is used for comparing the assumption of equality of varian=
ce.
For doing it, the Levene<=
/span> test for equa=
lity
was applied.
Table 12. Group work: assumption =
of
equality of variances test
|
Group Statistics |
|||||
|
|
Group |
N |
Mean=
|
Standard
deviation |
Standard er=
ror
difference |
|
Pre-test |
Experimental |
25 |
2,48=
|
1,661 |
,332=
|
|
Control |
25 |
2,16=
|
2,154 |
,431=
|
Source: Pre -test results. Experimental and control group:
Group work: assumption of equality of variances test
Author: Pilco,
M. (2018)
Ta=
ble 13.
=
Levene test for equality of variances. Group work Independent samples T-test =
Levene test for
equality T- test for equality of means<=
/b> F sig=
t gl Sig.(two ta=
iled) Mean differ=
ence Standard er=
ror
difference 95% Confide=
nce interval
of the difference Inferior Superior PRE-TEST Equal variances assumed 2,259 0,139 0,588 48 0,559 320<=
span
lang=3DEN-US style=3D'font-size:10.0pt;line-height:115%;font-family:"Aria=
l",sans-serif;
mso-ansi-language:EN-US'> 0,544 -0,774 1,414 Equal variances not assumme=
d =
=
,588=
45,090 ,559=
320<=
span
lang=3DEN-US style=3D'font-size:10.0pt;line-height:115%;font-family:"Aria=
l",sans-serif;
mso-ansi-language:EN-US'> ,544=
-,776 1,416 Source:
T-Test. Group statistics. Levene test for equal=
ity of
variances. Pre-test; group work Author: Pilco,
M. (2018) As
the table above shows, in the pre-test the sig. is > 0.05; being 0.139 > 0,05; therefore it is conclud=
ed
that the Levene test of equality shows that the=
re is
equality of variances. Besides, the researcher has compared the mea=
ns
in the two groups. It is noticed that Sig. in the table above is 0,559 whic=
h is
> 0.05; therefore it is needed to say there are differences between the
pre-test of the experimental group and the pre-test in the control group.
However, this difference is not too significant. T- TEST: group work. Post-
test Similarly
to the pair group work analysis, the researcher has verified whether there =
is a
significant difference between the means of the control group and the
experimental one in the post-test. This hypothesis is showed because the H1=
in
this study makes the assumption that the effects of cooperative learning
influence on reading comprehension development. The
hypothesis is: µ1
≠ µ2 G1
≠ G2 This formula implies that the mean in the experimental group, G1, is=
not
the same as the mean in the control group, G2.
Therefore, it is clearly showed that the mean in the experimental gr=
oup
for the post-test is highly different from the mean in the post-test of the
control group. Table 14. T-tes=
t. <=
/span>Group
statistics. Post-test group work Group statistics GROUP N Mean=
Standard
deviation Standard er=
ror
mean POST-TEST EXPERIMENTAL 25 7,12=
2,315 0,463 CONTROL 25 2,56=
1,781 0,356 Source=
: T-Test. Group statistics. Post-test; group work Author: Pilco,
M. (2018) Table 15. Compa=
ring
population means. Post-test- Group work Independent samples T-test Levene test for
equality T- test for equality of means F sig<=
span
lang=3DEN-US style=3D'font-size:10.0pt;line-height:150%;font-family:"Aria=
l",sans-serif;
mso-ansi-language:EN-US'> t gl Sig.(two
tailed) Mean differ=
ence Standard er=
ror
difference 95% Confide=
nce
interval of the difference=
Inferior Superior POST-TEST Equal variances assumed 1,555 0,218 7,805 48 0,000 4,560 0,584 3,385 5,735 Equal variances not assummed 7,805 45,042 0,000 4,560 0,584 3,383 5,737 Source: Independent samples T- test. Post-test – Group work Author: Pilco,
M. (2018) In the table above, the si=
g.
is < 0,05; therefore,
there are significant differences between the post- test in the G1 and G2 b=
eing
the results in the experimental group higher than the results of the post-t=
est
of the control group. Furthermore,
it is needed to analyze if the results of the pre-test and the post-test in=
the
experimental group are different. Therefore, the T- t=
est
is applied: Table 16. Paired sample T-test.
Experimental group Paired sample statistics experimental group Mean=
N Standard
deviation Standard er=
ror
difference Par 1 Pre- test 2,48=
25 1,661 0,332 Post-test 7,12=
25 2,315 0,463 Source: Independent
samples T- test. Post-test – Group=
work Author: Pilco,
M. (2018)
In the table below, it is showed that the sig. is =
> 0.005; hence, ther=
e is
big difference between the pre-test and the post test results.
Table 17. Correlation of paired
samples. Pre and post-tests. Experimental group
|
Correlation of paired samples Pre- and
Post-tests – Experimental group |
||||
|
|
N |
Correlation=
|
Sig.=
|
|
|
Par 1 |
Pre-Test &a=
mp;
Post-Test |
25 |
-0,102 |
0,627 |
Source: paired
samples T- test. Post-test – G=
roup
work
Author: Pilco,
M. (2018)
Ta=
ble 18.
Pair
sample test
|
Paired sample test - Experimental group |
|||||||||
|
|
Mean |
Standard deviation |
Standard error difference |
95% confidence interval of the difference |
T |
gl |
Sig. |
||
|
Inferior |
Superior |
||||||||
|
=
Par
1 |
=
Pre-
test =
Post
- test |
-4,640 |
2,984 |
0,597 |
-5,872 |
-3,408 |
-7,774 |
24 |
0,000 |
Source: Paired
Sample T- test. Post-Test – Group =
work
Author: Pilco,
M. (2018)
In the table above, there is evidenced that the Si=
g.
is < 0,05; therefore, the=
re is
a high difference between the pre-test and the post test of the Experimental
group.
Final decision
After performing the teach=
er’s
intervention, the results indicate that there is a significant difference
between the pre and post-test in the experimental group. Therefore, the
application of cooperative learning for reading comprehension gave good res=
ults
in the experimental group as the figure below shows:
Fi=
gure
Source: Final
results
Author: Pilco,
M. (2018)
Besides, it is also evident that students’ performance is higher in the group work than the pair work.<= o:p>
Conclusions
·
In accordance with T-stu=
dent
test, it has summed up that cooperative learning had contributed to improve
reading comprehension development to students of first year of bachillerato at Unidad Educativa=
“Riobamba” in the 2017-2018 academic year. In other words, the impact of
cooperative learning on reading comprehension was high with positive effect=
s on
students’ development.
·
Most helpful cooperative
learning strategies were identified in order to enhance the students’ readi=
ng
comprehension. Those cooperative learning strategies were identified and us=
ed
in the proposal for better development of the students such as jig-saw,
reciprocal questioning, cooperative reading role cards, think-pair share,
number heads together, and PMI which let both students and teacher develop
positive attitudes towards group cooperation. Students showed lots of inter=
est
for learning and improving their reading comprehension skills; therefore, t=
heir
interest encourages for keep going this research project. Students showed t=
heir
positive attitude while working in pairs and in groups as well. This motiva=
ting
attitude elicited the results in the pre and post-tests results. Students’
cooperation was crucial for the successful accomplishment of goals.
·
There were positive effe=
cts
on reading comprehension of students who attend to classes with the use of
cooperative learning compared with students who attend regular English clas=
ses.
After different reading strategies were identified which are related to
cooperative learning, students have worked in both pairs and small groups w=
ith
strategies such as identifying the main idea and supporting details,
summarizing, cause and effect, sequence, making predictions, drawing
conclusions, making inferences, compare and contrast, fact or opinion, and =
identifying
authors’ purpose. And the intervention was developed in the experimental gr=
oup.
The teacher has developed her intervention in steps: before, during, and af=
ter
reading. Those steps were managed with cooperative learning approach with g=
ood
results because in the pre-test students of the experimental group had a me=
dia
of 1,66 and in the post-test they obtained 7,12 with 95% of confidence. On =
the
other hand, the control group obtained 1, 74 in the pre-test and 2.93 in the
post-test. These results clearly show that the impact of cooperative learni=
ng
is high with respect to students’ reading comprehension.
Boyd, N. (2018). Study.com. Retrieved May 24, 2018, from How
Observational & Field Research Are Used to Collect Data: https://study.com/academy/lesson/how-observational-fie=
ld-research-are-used-to-collect-data.html
L., Manion, L., & Morriso=
n,
K. (2007). Research Methods in Education. New York: Routledge Tay=
lor
& Francis Group. Retrieved from
https://www.researchgate.net/publication/44824604_Research_Methods_in_Ed=
ucation
Felder, R., & Brent, R. (2013). Cooperative Learning. Cary: Education Designs, Inc. Retri=
eved
from http://www4.ncsu.edu/unity/lockers/users/f/felder/public/Papers/CLC=
hapter.pdf
Garfield, J. (1993). Teaching Statistics Using Small-Group Cooperat=
ive
Learning. Journal of Statistics Education , 1-4. Retrieved from
https://www.tandfonline.com/doi/full/10.1080/10691898.1993.11910455
Henetz, T. (2013, May 15). Stanford
Teaching commons. Retrieved April 20, 2018, from Teaching techniq=
ues:
https://teachingcommons.stanford.edu/teaching-talk/learning-techniques-r=
esearch-reveals-dos-and-don%E2%80%99ts
INEVAL. (2017). Instituto
Nacional de Evaluación Educativa. Retrieved October 7, 2017, from
http://www.evaluacion.gob.ec/
Jacobs, G., & Hall, S. (2002). Implementing Cooperative Learnin=
g.
In J. Richards, & W. Renardya, Methodology in Language Teaching
(pp. 52-59). Cambridge: Cambridge University Press.
Johnson, D., Johnson, R., & Stanne, M. (2000). Cooperative Learning Methods: A
Meta-Analysis. Mineapolis: University of Minesota.Retrieved from
https://www.researchgate.net/profile/David_Johnson50/publication/2200403=
24_Cooperative_learning_methods_A_meta-analysis/links/00b4952b39d258145c000=
000/Cooperative-learning-methods-A-meta-analysis.pdf
Kamalova, L., & Koletvinova, N. (2016). T=
he
Problem of Reading and Reading Culture Improvement of Students Bachelors=
of Elementary
Education in Modern High Institution. Retrieved from International
Journal of Environmental & Science Education,:
https://www.google.com.ec/search?q=3Dreading+problems+around+the+world&a=
mp;oq=3Dreading+problems+around+the+world&aqs=3Dchrome..69i57.7736j0j7&=
amp;sourceid=3Dchrome&ie=3DUTF-8
Kowalczyk, D. (2003). Study.com. Retrieved February 2, 2018,
from Quasi-Experimental Designs: Definition, Characteristics, Types &
Examples:
https://study.com/academy/lesson/quasi-experimental-designs-definition-c=
haracteristics-types-examples.html
Marzano, A.,
Vegliante, R., & De Angelis, M. (2015). Qua=
li-Quantitative
Approach In Educational Research. Madrid: University of Salermo. Retrieved from
https://www.researchgate.net/publication/280521706_QUALI-QUANTITATIVE_AP=
PROACH_IN_EDUCATIONAL_RESEARCH
Marzbana, A., & Alinejadb, F. (2014). The Effect of Cooperative Learning on Reading Comprehension.
Iran: ScienceDirect. Retrieved from
https://www.sciencedirect.com/science/article/pii/S1877042814008519
McNamara, D. (2007). Rea= ding Comprehension Strategies. New York: Lawrence Erlbaum Associates.<= o:p>
Meng, J. (2010). Jigsaw Cooperative Learning =
in
English Reading. Retrieved from Journal of Language Teaching and
Research: http://www.academypublication.com/issues/past/jltr/vol01/04/29=
.pdf
Millis, B. (2002). Idea =
Paper
#38. Retrieved October 11, 2017, from Enhancing Learning and More!
Through Cooperative Learning:
http://www.ideaedu.org/Portals/0/Uploads/Documents/IDEA%20Papers/IDEA%20=
Papers/IDEA_Paper_38.pdf
Perles, K. (2018). Bright Hub Education. Retrieved October 2=
4,
2017, from http://www.brighthubeducation.com/lesson-plans-grades-3-5/434=
63-teaching-cause-and-effect/
Slish, D. (2005). Assessment of the use of the Jigsaw Method and
Active Learning in Non-majors, Introductory Biology. Ney York: Milli=
kin
University. Retrieved from https://eric.ed.gov/?id=3DEJ876525
Stevens, R., Savin, R., & Famish, A. (1991). The Effects of Cooperative Learning=
and
Direct Instruction in Reading Comprehension Strategies on Main Idea
Identification . Maryland: Jou=
rnal
of Educational Psychology.
Para citar el
artículo indexado.
emache Carrillo, N., Pilco Labre, M., & Yanez
Valle, V. (2019). The effects of cooperative learning on reading comprehension. Explorador Digital,
3(3.1), 143-163. https://doi.org/10.33262/exploradordigital.v3i3.1.8=
75
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responsabilidad de los autores y no necesariamente reflejan el pensamiento =
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la Revista Explorador Digital.
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y/o total en otro medio tiene que ser autorizado por el director o editor d=
e la
Revista Explorador Digital.
[1]Escuela Superior Politécnica =
de
Chimborazo, Centro de Idiomas, Riobamba, Ecuador, noemi.carrillo@espoch.edu=
.ec
2 Unidad Educativa
Riobamba, Riobamba, Ecuador, marielapilco@yahoo.com.
[3]Escuela Superior Politécnica =
de
Chimborazo, Centro de Idiomas, Riobamba, Ecuador, viviana.yanez@espoch.edu.ec;