Palavras-chave: Opinião
dos pares; produção oral; pesquisa-ação; design retrógrado.
Introduction
Developing
speaking skills in a second language is influenced by many factors (Santos et
al, 2020). As Brown (2000) mentioned, one of these factors that can negatively
impact this skill is the affective factor. Most students feel anxious whenever
they have to speak because they fear blurting out something wrong or
incomprehensible (Santos et al., 2022). It is one of the difficulties
identified in eighth-grade students aged twelve; it is difficult for them to
maintain a conversation and express and support their ideas in spoken English.
These
eighth-grade students have gone through two years of online education where
they have not had the chance to practice their speaking skills with peers and
have focused on content. Therefore, they cannot maintain a conversation or
share their opinions using English. They are now back in their physical
classrooms. After a month of review, the school system has focused on
evaluations through lessons, homework, individual activities, and group
activities without any feedback to help them improve.
Consequently,
this research proposes introducing peer feedback into educational practice to
improve students’ oral production. Peer feedback is when “learners work
together and comment on one another’s work or performance and provide feedback
on strengths, weaknesses and suggestions for improvement” (Yu & Hu, 2017,
as cited in Banister, 2020, p. 2). In the hope that it can help engage students
in their learning and positively impact their speaking skills, which is one of
the most challenging skills for most students learning a foreign language
because of the factors mentioned at the beginning. Therefore, this paper aims
to answer whether peer feedback impacts students’ oral production. For that
reason, the research question that guides this study is: 1) To what extent does
peer feedback improve eighth-grade students’ oral production?
Literature
Review
Peer
Feedback
Feedback
is a form of formative assessment that can help students compare their
performance against their learning goals (Nicol & Macfarlane-Dick, D, 2006;
Theal & Franklin, 2010). Liu and Carless (2006, p. 280) postulate that peer
feedback is defined as “a communication process through which learners enter
into dialogues related to performance and standards.” It can be given by a
teacher or by a peer. Peer feedback is “a set of activities through which
individuals make judgments about the work of others” (Reinholz, 2015, as cited
in Ndoye, 2017, p. 255).
There
have been many studies on peer feedback (Au & Bardakçi, 2020; McGarrell,
2010; Ndoye, 2017; Van Popta et al., 2017), but not many on its influence on
oral production (McGarrell, 2010; Ndoye, 2017) especially in Ecuador. However,
studies focusing on how peer feedback impacts oral production have had some
positive results (Au & Bardakçi, 2020; Joo, 2016; Ratih et al., 2020).
One
research that has studied the impact of peer feedback on oral performance is
that of Au and Bardakçi (2020). Their study was conducted among A1 students
throughout three academic modules (A1 Elementary, A2 Pre-Intermediate, and B1
Intermediate modules). Students were divided into two groups, Group A and Group
B; Group A received peer feedback and Group B immediate teacher feedback, both
feedbacks done with TOEFL independent rubric. The results showed that both
groups’ oral performances displayed significant improvement.
Furthermore,
this study examined the correlation between students’ oral performance and
self-efficacy. The results showed that there was no significant correlation
between the two. Alternatively, Ratih et al. (2020) research focused on online
students’ self-efficacy in using oral peer feedback for speaking activities.
They found that participants had different results affected by their
self-efficacy, goals, experiences, and strategies; the students with higher
self-efficacy had better results than those without self-efficacy.
According
to Ndoye (2017), peer feedback promotes students’ learning through effective
feedback, a supportive learning environment, and cooperation among learners. It
was supported by the results of his research, where most of the students
reported that they preferred to discuss their feedback orally because this
helped them act on it while still on the task. In addition, peer feedback
helped them identify their learning gaps and locate appropriate tools to
improve. They also reported that peer feedback helped them clarify a task’s
expectations and requirements, which allowed them to feel like they had a
supportive learning environment. Likewise, they felt a stronger sense of
responsibility towards their peers as they needed to prepare themselves to
offer the same assistance they received. A study done with 40 major English
students from a Taiwanese university showed that most students agreed that
“peer-assessment had learning benefits such as enhanced awareness of their
strengths and weaknesses, development of critical thinking ability, and the
acquisition of oral skills” (Cheng & Warren, 1997, as cited in Joo, 2016,
p. 9).
Challenges
There
are some challenges when conducting peer feedback (Ashenafi, 2017, Jordan,
2012; Lam & Habil, 202; Liu & Carless, 2006). The most common is that
many students feel that their English-speaking ability is not good enough to
assess their peers’ performance or feel unprepared to give feedback (McGarrell,
2010; Ndoye, 2017; Ratih et al., 2020). Other challenges include time
constraints to discuss feedback thoroughly, learners not seeing assessment as
their responsibility, and students’ disposition to work in groups (Ndoye,
2017).
For
learners to successfully give feedback to their peers, teachers must make sure
to meet some conditions (Yu, 2021). “These conditions include the clear
provision of task-related criteria, sufficient training, considerations of the
learner traits and their perception, as well as the strong integration with the
curriculum” (Joo, 2016, p. 13). For example, one-way students can be trained is
by familiarizing them with a rubric and asking them to give feedback on
multiple spoken performances the teacher has previously revised, then comparing
their feedback with the grading report of these performances (Bachman &
Palmer, 1989). This type of training was done in Au and Bardakçi’s (2020)
research, where students trained for a week by giving feedback to five
responses to the same TOEFL independent speaking task they undertook.
Oral
Production
It is
hard to define speaking because many scholars have different definitions
(Howarth, 2001; Luoma, 2004). Abugohar et al. (2019) defined speaking as a
“communicating process of interaction which is the foundation of all
relationships between humans” (p. 2). On the other hand, Kürüm (2016) stated
that we could say someone speaks a language when the person can produce
meaningful sentences in that language. This author also pointed out that
learners of a foreign language evaluate their progress in the target language
based on their ability to speak fluently (Kürüm, 2016).
Even
though English is a language studied profusely worldwide (Fregonese, 2017),
many students of this language have difficulty speaking it (Juhana, 2012;
Paakki, 2020). Both Brown (2000) and Paakki (2020) addressed the factors which
hinder students’ oral production skills. Brown (2000) called it the “language
ego,” which is students’ idea that they are what they speak. They do not want
to be judged by their performance.
On
the other hand, Paakki (2020) called it “normativity,” which is defined as the
“idealization of standard target language (TL) accents, and standard TL models
that are free from dialect features, learner errors, spoken-language-like
colloquialisms or imperfectness…” (p. 24). Another factor mentioned by Paakki
(2020) is the instruction and input factors; this study showed that both
Finnish and Japanese students were taught based on accuracy rather than
fluency, where language test-taking activities prevailed over oral production
tasks. These factors hindered their performance and their self-confidence in
their speaking ability. Consequently, it is essential to focus on both accuracy
and fluency of language and to find the right balance, so students feel encouraged
to speak (Brown, 2000, Santos & Barcelos, 2018).
Innovation
This
innovation was carried out with 15 eighth-grade students, ages 12 to 13, at a
private bilingual school; their English level varies from A2 to B1. The classes
were taught face-to-face, and the process lasted two weeks.
The
unit was planned to use a backward design planning framework, where the
transfer goal was decided first. Then, the summative (final task) and formative
(peer feedback checklist) assessments were planned to see how students were
doing against the transfer goal. Finally, the instructional part of the lessons
was designed to determine the types of activities students must complete to
reach the transfer goal. These activities were classified into acquisition, meaning
making, and transfer.
In
addition, the Gradual Release of Responsibility (GRR) method (Pearson &
Gallagher, 1983) was used to ensure students were more proactive in class. This
method consisted of first showing students a model of the task. Then, through
guided instructions, students practiced the activities collaboratively and
finally showed they could transfer the new knowledge independently.
The
unit plan consisted of four lessons, including the summative assessment. In
addition, each class provided functional language and vocabulary to talk about
past experiences. Also, students practiced using the past simple and continuous
tenses in context through tasks that encouraged students to talk about
different situations they experienced in the past. Students also had controlled
practice of the structures of both tenses.
Students
were trained on how to give peer feedback using a checklist. This training
happened throughout the unit after they had already listened to a model of the
desired outcome. Students practiced giving peer feedback three times to
recordings of different people describing an experience using the checklist.
Then, they would compare their feedback to their teacher’s and reflect on how
well they did.
Students
were presented with different models of the desired outcome during the unit. At
the end of each lesson, they would have production activities like role-plays,
creating a recording talking about an experience, or retelling a story.
Students also practiced giving feedback on their peers’ recordings. The teacher
would monitor the class collecting useful language and any mistakes to give
feedback at the end of the activities. At the end of the unit, students were
given thirty minutes to plan and record their final oral task on the class’s
i-Pads. Then, they were set in pairs to give feedback to each other using the
checklist. Finally, students were given twenty minutes to make any changes to
their recordings based on their peer’s feedback before uploading them to
Flipgrid.
Methodology
The
present study is action research, defined as “empowering and professional
research done by teachers to inform and improve their practices” (Milton-Brkich
et al., 2010). According to Land (2000), action research has the following
steps: “identify a problem, collect relevant information about the problem,
take action, measure it using various methods, and interpret the results” (p.
3).
This
action research was carried out using quantitative instruments to analyze to
what extent peer feedback (independent variable) improves 8th-grade students’
oral production (dependent variable).
Participants
Participants
were recruited from a single eighth-grade class at a private school in
Samborondon, Ecuador. The school is in an affluent area near the city of
Guayaquil. Students were between the ages of twelve and thirteen years old. The
class was made up of 23 students who were invited to participate in the study.
Parental consent was received from 15 students. More than half of the students
were female (9) and less than half were male (6). Their English level ranged
from A2 (13 students) to B1 (2 students), according to the CEFR.
Instruments
Pretest
and posttest
Students
were asked to record two audios as a speaking test, one at the beginning of the
innovation (pretest) and one at the end (posttest). A rubric was used to grade
students' pretest and posttest. Ulker (2017) mentioned that the status and form
of an assessment conducted vary depending on the purpose. Based on the purpose,
there are eight criteria teachers can choose to assess speaking; the rubric
uses four criteria: grammar, vocabulary, pronunciation, and content.
The
rubric employed a two-and-a-half-point analytical scale. The scores were
derived from the evaluator’s holistic considerations of a general description
based on the four dimensions mentioned previously. For each category, score
bands and student performance descriptors were listed and used to
systematically assign scores to students’ oral production. This study assigned
two and a half points within each category, totaling ten points. An expert in
the field at Universidad Casa Grande vetted it in order to enhance reliability.
Peer
feedback checklist. The students’ peer feedback checklist had four items, each
linked to one rubric descriptor. In addition, it had the following qualitative
scale: “not yet,” “sometimes,” and “yes.” The checklist was designed to follow
the principles of backward design. An expert in the field at Universidad Casa
Grande vetted it.
Data
Analysis
Microsoft
Excel’s data analysis add-in was used to calculate the mean, standard
deviation, minimum, and maximum of the results of each of the rubric
descriptors for the pretest and posttest. Additionally, a paired sample t-test
was used to identify if there was statistical value in the mean difference between
students’ performance, in grammar, vocabulary, pronunciation, and content,
before and after the innovation.
Ethical
Considerations
This
action research followed the procedure of ethical considerations (Gajjar, 2013;
Kaewkungwal & Adams, 2019). First, the author obtained the authorization of
the school’s principal to administer the innovation. Then, it was explained to
students the goal of the innovation, and then proceeded to send a letter to
their parents asking for their consent for students to participate in the
innovation. Parents’ consent was received from 15 students out of 23 who were
invited to participate.
Results
To
answer the research question: to what extent does peer feedback improve
8th-grade students’ oral production? First, the author took the approach of
doing a general analysis of the total scores of the pretest and posttest and
then a more detailed analysis of the different aspects of the rubric.
General
Results from the Oral Production Rubric
Students’
pretest minimum score was three, and the maximum score was eight, with a mean
of 6.2 and a standard deviation of 1.32. The posttest minimum score was five,
and the maximum score was 10, with a mean of 8.86 and a standard deviation of
1.68. The null hypothesis in a paired sample t-test is that there is no
difference between dependent groups. The paired sample t-test showed no
significant difference between the pretest and posttest scores with a p-value
(t= -8 p= 1.369) which is above the alpha value of 0.05 and therefore indicated
support for the null hypothesis.
Table 1
Paired Sample t-test Results from Experimental Group
|
N (15)
|
|
Test
|
Mean
|
SD
|
Min
|
Max
|
Sig.
(P)
|
|
Pre
|
6.2
|
1.32
|
3
|
8
|
1.369
|
|
Post
|
8.7
|
1.68
|
5
|
10
|
|
Note:
N= sample M= mean Sd= standard deviation Min= Minimum Max =
Maximum Sig (P): Significance
|
Source
(Alcivar and Santos, 2023)
Detailed
Results from each Descriptor of the Fluency Rubric
Another
paired sample t-test was conducted to compare each aspect of the rubric to look
for considerable changes in the experimental group. The results exhibited in
table 2 identified a statistically significant difference between pretest and
posttest scores in the grammar (t= -4.03, p= .001) and vocabulary (t= -5.12, p
< .001) descriptors of the rubric. The test indicated support for the
alternative hypothesis in these two descriptors.
Table 2
Experimental Group Rubric Results
|
N (15)
|
|
Pretest
|
|
|
Grammar
|
Vocabulary
|
Pronunciation
|
Content
|
|
Mean
|
1.36
|
1.1
|
2.3
|
1.43
|
|
SD
|
.743
|
.632
|
.414
|
.258
|
|
Min
|
0.5
|
0.5
|
1.5
|
0.5
|
|
Max
|
2.5
|
2.5
|
2.5
|
1.5
|
|
Posttest
|
|
Mean
|
2.1
|
2.1
|
2.43
|
2.23
|
|
SD
|
.632
|
.736
|
.258
|
.457
|
|
Min
|
0.5
|
0.5
|
1.5
|
1.5
|
|
Max
|
2.5
|
2.5
|
2.5
|
2.5
|
|
tStat
|
-4.03
|
-5.12
|
-1.46
|
-7.48
|
|
Sig.
(P)
|
0.001
|
0.000
|
0.164
|
2.952
|
|
Note:
N= sample M= mean Sd= standard deviation Min = Minimum Max = Maximum tStat =
test statistics Sig (P)= Significance
|
Source
(Alcivar and Santos, 2023)
Discussion
This
study demonstrated that 8th-grade students of A2 to B1 levels could improve their
overall oral production through repeated practice and peer feedback. This study
was echoed by Au and Bardakçi (2020), who observed that repeated oral practices
and treatment provided opportunities for learners to glimpse at their
performances and enhance their speaking ability. In this study, students
successfully gave peer feedback to their classmates due to the previous process
of familiarization with the rubric and repeated practice. They used the
checklist to give feedback on some recordings and compared it to the teacher’s
feedback before using the checklist to give feedback to their classmates. This
kind of preparation is mentioned in the study of Joo (2016), who stated that
sufficient training must be met for students to assess their peers’ oral
performance. This kind of training was also put into practice in the study of
Au and Bardakçi (2020) with positive results.
This
research was significant because it revealed that most students already had
good pronunciation. Furthermore, unlike other studies, this study revealed that
after treatment, students’ grammar and vocabulary significantly improved. On
the other hand, there was no statistically significant difference between
overall scores of students’ oral production before and after treatment.
Conclusions
The
primary purpose of this study was to determine to what extent peer feedback
would affect eighth-grade students’ oral production. These students had gone
through two years of online education because of the pandemic. The effects of
these two years of online education showed their difficulty in expressing
themselves using the language.
Subsequently,
to help students express themselves in the target language, the lesson plan was
created using a backward-design planning framework where the transfer goal and
assessment criteria were chosen first. Then the activities were planned to
reach that goal. Finally, the activities provided repeated oral practice and
training for effective peer feedback.
This
research has proved that peer feedback can help improve students’ oral
production. Nonetheless, the results of this study go beyond previous reports,
showing a significant improvement in students’ grammar and vocabulary aspects
of their oral production.
Limitations
and Recommendations
One
limitation of the present study was that students were just getting used to the
rigorous schedule of face-to-face classes in a bilingual school, with some
English classes lasting longer than an hour. It is essential to highlight that
these students had previously been used to online classes of forty minutes.
Another limitation of this study was the timing of the posttest. The posttest
was carried out during a week of evaluations during the last hours of the
school day.
It
affected some students’ commitment to the task. Finally, it was estimated that
twenty-three students would participate in this study, but only fifteen were
allowed to participate. Therefore, the generalizability of the results is
limited by the number of participants.
Future
studies should strategically examine which aspects of students’ oral production
improve with peer feedback. It should also aim to replicate the results with a
larger sample to generalize the positive effect peer feedback can have on
students’ oral production.
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https://orcid.org/0000-0002-6948-4803 
