LLT Journal, e-ISSN 2579-9533, p-ISSN 1410-7201, Vol. 27, No. 1, April 2024, pp.

434-460

LLT Journal: A Journal on Language and Language Learning

http://e-journal.usd.ac.id/index.php/LLT
Sanata Dharma University, Yogyakarta, Indonesia

INVESTIGATING THE IMPACT OF ONLINE VS. BLENDED

LEARNING ON VOCABULARY LEARNING: EVIDENCE
FROM IRANIAN INTERMEDIATE EFL LEARNERS

Maryam Ramezani Sarajari1 and Abbas Pourhosein Gilakjani2*

1, 2
Department of English Language Translation, Lahijan Branch,
Islamic Azad University, Lahijan, Iran
ramezan94m@gmail.com1 and abbas.pourhossein@yahoo.com2
*correspondence: abbas.pourhossein@yahoo.com
https://doi.org/10.24071/llt.v27i1.7207
received 14 September 2023; accepted 28 April 2024

Abstract
This study aimed to examine the effect of online vs. blended learning on improving
vocabulary learning among Iranian intermediate EFL learners. The current study
followed a quasi-experimental, pretest-posttest control group research design. The
researchers selected a sample of 120 EFL intermediate learners from a private
English Language Institute in Lahijan, Iran for this purpose. The researchers
divided the participants into three groups of 40 students each. The researchers used
three instruments: 1) a Solution Placement Test (SPT), 2) a Vocabulary pre-test 3),
and Vocabulary post-test. The control group only learned vocabulary through
traditional lecture methods and face-to-face teaching. The LMS instructional model
and the blended learning instructional model were used to teach vocabulary to the
online learning group and the blended learning group, respectively. After 10 weeks,
students were tested again using a before and after design. In the L2 vocabulary
test, both the online and blended learning groups performed better than the control
group, in addition, no significant difference was observed between the online and
blended learning groups. That is, both online and blended learning instructions have
been effective in the development of EFL learners’ vocabulary learning and have
had a statistically significant effect on the vocabulary learning of Iranian
intermediate EFL learners. The researchers suggest that EFL students can benefit
from learning L2 vocabulary through online and blended learning. The findings
have practical implications for teacher education programs to promote prospective
teachers’ interest and willingness to implement web-based systems. The findings
also have important implications for web-based application developers. They
should consider a clear model for blended learning and teachers should have the
right to choose a blended learning model that suits their teaching contexts to manage
the classroom and provide a more effective learning environment.

Keywords: blended learning, EFL learner, online learning, vocabulary learning

Introduction
Learning English as a foreign language (EFL) is likely to be challenging for
a wide range of learners. In addition, vocabulary is the main component or the heart
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LLT Journal, e-ISSN 2579-9533, p-ISSN 1410-7201, Vol. 27, No. 1, April 2024, pp. 434-460

of learning another language for them (Coady & Huckin, 1997; Tozcui & Coady,
2004). As a result, without vocabulary knowledge, learning a foreign language is
difficult (Nation, 2013; Yang & Dai, 2011). In addition, vocabulary knowledge
correlates with their language use; that is, the knowledge probably supports the
input and output of their language (Nation, 2001). Likewise, learning vocabulary is
essential because it is the foundation of all language skills (listening, speaking,
reading, and writing) (Aghajanzadeh Kiasi & Pourhosein Gilakjani, 2023; Barcroft,
2004; Hógain, 2012; Namaziandost, Pourhosein Gilakjani, & Hidayatullah, 2020;
Namaziandost, Razmi, Tilwani, & Pourhosein Gilakjani, 2022; Nation, 2001;
Shabani, Parseh, & Gerdabi, 2014; Taati Jeliseh & Pourhosein Gilakjani, 2022).
Communication may fail for those who master grammar but lack vocabulary
knowledge. Many learners feel that they cannot recall the word quickly in a
conversation because of their limited vocabulary. This feeling of insufficiency
prevents further language development. Learners can use vocabulary to form
sentences and communicate in meaningful ways (Harmon et al., 2009; Linse, 2005;
Meredith, 2012; Tosun, 2015).
Even though vocabulary is essential in language learning, a lack of
vocabulary knowledge is already a serious and obvious problem for many students.
Vocabulary knowledge is considered as an essential component of the learner’s
competence and is a contributing factor to the learning process. It is widely accepted
that a lack of vocabulary knowledge limits students’ comprehension of texts and
hinders their ability to engage in listening, reading, writing, and communicative
skills (Noprianto & Purnawarman, 2019). Hunt and Beglar (2005) suggested that
many EFL learners probably have less vocabulary knowledge when using English.
Schuth, Köhne, and Weinert (2017) stated that many EFL learners struggle to
understand spoken language, when there are no visual images. In addition, Khan et
al. (2018) found that a lack of vocabulary knowledge makes it difficult for many
EFL learners to understand passages or sentences they read in English. These
studies showed barriers for EFL learners due to lack of adequate vocabulary
knowledge.
Lack of vocabulary knowledge can lead to stress and anxiety, which
demotivates learners and discourages them from participating in the language
learning process (Al Zahrani & Chaudhary, 2022). Therefore, the importance of
acquiring new words to facilitate the process of learning foreign languages has been
overemphasized (Alharthi, 2020; Masrai, 2020). Adunyarittigun (2002)
investigated Thai students who learned English as a foreign language from the fifth
grade until the end of secondary school. The study revealed that the students could
not predict the meaning of unfamiliar vocabulary in context due to their lack of
vocabulary knowledge and sentence structure.
Online learning and blended learning have become more common since
COVID-19 pandemic started. Many platforms for learning have been created to
support these modes of learning. Online learning means providing learning
programs using digital technologies (Liimatainen, 2021). New technologies can
help students to enhance their learning outcomes, particularly in developing four
language skills (Ahmad et al., 2018). Online learning is an educational environment
where course objects can be delivered using different online strategies. Hybrid
learning, also known as blended learning, is a combination of online and face-to-
face learning. These environments have advantages and disadvantages. Online

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learning has some benefits, such as a cozy environment, a lower cost, access to
materials, and the possibility of staying at home. Lack of interaction between
students and teachers, unsolvable problems, and technical problems can be
mentioned as disadvantages of online learning (Baczek et al., 2021; Mustafa &
Hama Saeed, 2023; Salleh et al., 2020). Blended learning brings advantages like
inspiring students to learn, strengthening classroom relationships, improving
students’ academic writing, and reducing students’ study stress (Albiladi &
Alshareef, 2019). Blended classes take time to prepare, current technology may be
difficult for casual users, and teachers must prepare lectures for online and face-to-
face learning (Albiladi & Alshareef, 2019). Online and blended learning can help
EFL learners to improve their reading culture and overcome the challenges that
students and teachers encounter during the course (Khalid Mustafa et al., 2021;
Mustafa & Hama Saeed, 2023).
Efforts have been made to increase students’ vocabulary knowledge through
different types of instruction, especially using technology (Bozorova & Salixova,
2019). Blended learning is one of the most effective types of technology-assisted
learning. Blended learning aims to facilitate the language learning process both in
online and face-to-face instruction. This type of training is the most suitable
solution for many teachers working in physical classrooms who need to use
technology as an aspect of their practice in the development of educational
technology (Motteram & Sharma, 2009). Among different teaching methods,
blended learning provides an opportunity for teachers and students to interact
through face-to-face and online learning sessions (Singh, Steele, & Singh, 2021)
This research addresses critical variables, as English language teachers are
expected to benefit from its results in creating an effective learning environment
within the classroom at the intermediate level. The results of this study can
contribute to conceptualizing training programs based on the style of blended
learning in teaching for intermediate learners. The study is expected to open a way
to start new research and studies related to the current variables and the extent of
their impact on the psychological, educational, and educational variables. It can
benefit English language curriculum designers at the intermediate level by using
blended learning in building English language lessons.
The positive effects of online and blended learning on learners’ vocabulary
are assumed, based on the potential abilities of technology to enhance language
learning. This research aimed to investigate the impact of online and blended
learning on the vocabulary learning of Iranian intermediate learners, given that
students have different methods of learning vocabulary in EFL contexts and EFL
teachers need to create learning materials that match their students' needs.
Therefore, the following research question was posed: “Do types of vocabulary
instruction (online vs. blended learning) have any statistically significant effect on
Iranian intermediate EFL learners’ vocabulary learning?”

Literature Review
Vocabulary knowledge is essential in second language (L2) learning (Barkat
& Aminafshar, 2015; Reynolds & Shih, 2019). When learning English as a second
language, acquiring vocabulary is more important than mastering other language
skills, such as listening, speaking, reading, and writing (Lukas et al., 2020). This is
because vocabulary acts as the foundation for learners to communicate using the

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language (Lukas et al., 2020). The centrality of vocabulary knowledge has been
well documented in the related literature. The high importance of vocabulary in
language learning is emphasized by Renadya (2002) who stated that vocabulary
plays an important role and grants much of the basis for how well learners listen,
speak, read, and write. Qian and Lin (2020) conceptualized this strong connection
by contending that vocabulary knowledge is a key prerequisite for successful
language learning.
Many authors who have researched general language addressed the
interrelationship of vocabulary knowledge and four basic languages skills – reading
(Laufer, 2013; Schmitt, Jiang, & Grabe 2011; Şen & Kuleli 2015), writing (Karakoç
& Köse, 2017; Yüksel, Mercanoğlu, & Yılmaz, 2020), then listening (Stæhr, 2009;
Teng, 2014a; van Zeeland, 2012) and speaking (Koizumi & In’nami, 2013; Nation,
2015). Harkio and Pietilä (2016) found a positive correlation between vocabulary
knowledge and reading comprehension for intermediate and advanced proficiency
level L2 learners. Kiliç (2019) found that vocabulary knowledge was significantly
related to performance in writing and speaking. Ataş (2018) found moderate and
significant correlation between vocabulary knowledge and listening
comprehension. Uchihara and Clenton’s (2020) research yielded rather confusing
results on the relationship between vocabulary knowledge with respect to its size
and speaking.
Teachers can use blended learning to combine two or more methods or media
for teaching. Blended learning is a teaching method that uses both online and offline
resources and technology to support learning. It also involves different types of
instruction and strategies to help learners achieve the desired learning outcomes
(Sudewi, 2020). Blended learning is an educational program that involves active
learning in two ways: partly online, where the learner can choose the time, place,
and pace of their learning, and partly in a physical location away from home, such
as a school or a workplace (Tucker, 2003). Blended learning is a learning method
that focuses on the student and integrates online and face-to-face learning
experiences (Attard & Holmes, 2020; Kerzˇič et al., 2019). Blended learning uses
online tools for teaching, training, presenting, assessing, and communicating
(Adiguzel et al., 2020; Alammary, 2019). Online learning lets the students join
classroom activities anytime and anywhere (Hadiyanto, Sulistiyo, Mukminin,
Haryanto, & Syaiful, 2022; Nathan & Rajamanoharane, 2016; Pourhosein Gilakjani
& Rahimy, 2020). It enables students to collaborate and share their work or present
to the whole class, which fosters student-to-student interaction. Teachers can also
provide clear guidance and realistic goals for individual and group work, according
to Singh and Singh (2017) and Jamshidi Saleh and Pourhosein Gilakjani (2021).
They can design blended activities for online and face-to-face learning and help
students acquire 21st century skills through academic tasks in and out of the
classroom.
Blended learning has been proven to be effective in improving participants’
learning outcomes, engagement, and motivation (Bhagat, 2020). For instance, an
undergraduate biology course that used BL approach had better performance and
interaction with the instructor than a traditional approach, according to Riffell and
Sibley (2005). A meta-analysis by Vo et al. (2017) compared the effectiveness of
BL and traditional classroom teaching on participants' achievement in higher
education and found a small but significant advantage for blended learning. They

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suggested that BL could improve learning outcomes for participants in higher

education. The blended learning approach helped learners of English improve their
reading skills, according to Kazakoff et al. (2018). Miyazoe and Anderson (2010)
examined how students’ learning outcomes and views of online writing were
influenced by blended courses using three online writing tools for EFL in a blended
learning environment. The students improved their language learning by taking the
blended courses.
Rusanganwa (2013) explored how using computers or not using computers in
college English vocabulary instruction for specific purposes affected the learning
outcomes (ESP). The blend task is increasingly shown to be important for students'
vocabulary learning. Ma and Lee (2021) found that blended learning improved
students' perceptions of attention, confidence, and satisfaction more than online or
offline learning alone. Blended learning improved the students' English
conversation skills, and the students enjoyed the blended course, according to Wang
(2021). A blended approach was effective in improving students' listening and
speaking skills and developing their learner autonomy, according to Cui (2014).
According to Jia et al. (2012), students improved their vocabulary acquisition
performance with an English blended learning class that had individualised
vocabulary acquisition.
Blended learning has been used with learners in EFL/ESL settings in many
studies. Many researchers have found that blended learning approach has many
positive effects on improving vocabulary knowledge. Zhang, Song, and Burston
(2011) compared how well students at a Chinese university learned vocabulary
through mobile phones and paper material. They studied two groups of students
who used either text messages or paper material to learn a chosen list of vocabulary.
One group of students learned a selected list of vocabulary by using text messages,
while the other group of students used paper material for the same list. The results
showed that mobile phones helped students learn vocabulary better in the short term
than paper material. Khazaei and Dastjerdi (2011) also explored how traditional and
blended teaching influenced EFL learners' vocabulary learning. Students took a test
on how well they recognized and remembered vocabulary items. The test results
showed that the students who learned the content with a blended teaching approach
outperformed the students who learned the content in a traditional way.
Some studies found that blended learning improved learners' vocabulary
knowledge. For example, Djiwandono (2013) examined how Indonesian students’
vocabulary learning and their views on the blended learning experience were
affected by blended learning approaches. Krishnan and Yunus (2019) also
investigated how blended learning affected vocabulary learning for low-proficient
learners based on the global CEFR scales. The study used blended learning to help
low-level learners develop their vocabulary. These studies showed that blended
learning improved EFL students’ vocabulary knowledge. Some studies also
recommended using the Seesaw application as a blended learning tool. For
example, Javis and Martin (2018) found that Seesaw could motivate students and
positively affect elementary school students’ learning. Riadil (2020) also conducted
a study to explore the effect of using Seesaw as a literacy medium to enhance
learners' vocabulary. This study indicated that Seesaw could improve learners'
vocabulary knowledge and reading skills. Blended learning with primary level
participants had positive effects on vocabulary learning. Rosetta Stone Computer

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Software’s effect on Iranian students' vocabulary learning was examined by Sharifi

et al. (2015). The results showed that the groups that learned vocabulary with
computer assistance performed better on post-tests than the groups that learned
vocabulary with teacher guidance.
Khodaparast and Ghafournia (2015) examined the effect of online, offline,
and hybrid methods on Iranian EFL learners' achievement in vocabulary. They
selected 100 participants for this research. The traditional method was significantly
different from the other three methods they studied. This means that computer-
assisted teaching methods greatly influenced the vocabulary growth of language
learners. Mahmoudi (2020) investigated how online teaching via smartphone
affected Iranian EFL students' grammatical accuracy. They chose two groups of
upper-intermediate students, one as a control group and one as an experimental
group, for this purpose. The control group received traditional teaching for
grammar, while the experimental group received online teaching. The findings
represented that the experimental and the control group had significant differences,
and the intervention improved the performance of the experimental group more than
the control group.
Rezai Fard et al. (2021) studied how Iranian students learned vocabulary.
They discovered that using the flipped classroom to teach ESP vocabulary helped
Iranian students improve their vocabulary learning. They chose 60 ESP students
based on their scores on the OQPT. The experimental group learned vocabulary in
a flipped classroom, while the control group used a traditional method. The one-
way MANOVA indicated that flipping classes significantly improved Iranian
students’ vocabulary development.
There are contrasting evidences regarding the effect of blended learning on
language development. For example, Chang, Shu, Liang, Tseng, and Hsu (2014)
examined the impacts of blended e-learning on participants’ performance. The
participants were two classes of 11th graders in a vocational high school in Taiwan.
They were randomly selected and assigned to two experimental groups that studied
through blended e-learning or a control group that studied through traditional
classroom learning. The results indicated that blended e-learning did not have a
significant effect on students’ achievement test scores, but it did significantly affect
their self-assessment scores.
Yick, Yip, Au, Lai, and Yu (2019) investigated the impact of blended learning
on undergraduate students and compared the students’ grades in a blended learning
and in a traditional face-to-face classroom. The results did not show a significant
difference in the actual grades of students who used blended learning modules
compared to students in the control group. Similarly, Berga, Vadnais, Nelson,
Johnston, and Olaiya (2021) conducted a study on blended learning versus face-to-
face learning at an undergraduate university in Alberta, Canada. A total of 217
second-year undergraduate nursing students participated in this research. Data were
collected and analyzed using descriptive and inferential statistics. According to the
findings, there were no significant difference in self-efficacy scores between groups
or in the pre-post surveys over time. The results also indicated that there is no
significant difference in knowledge between the blended online and face-to-face
groups.
Blended learning is a complex way of learning that integrates online and
offline learning settings, learning materials, methods, and assessments. These

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elements cooperate to help students acquire essential knowledge and enhance their
language abilities. Despite the importance of blended and online learning, these new
methods of teaching and learning English are not very common in Iranian EFL
contexts. Most English classes are done in person rather than through online
instructions. The effects of these new teaching methods on the vocabulary
knowledge of Iranian EFL learners were investigated in this study, since these
methods have not been extensively examined in the Iranian EFL context.

Method
Research design
This study used a quasi-experimental, pretest-posttest control group research
design. Participants were randomly assigned to two experimental groups of the
same size- an online learning group (OLG) and a blended learning group (BLG)—
and a control group (CG). This research design was quasi-experimental because it
did not use randomization, which is a key feature of the true experimental research
method. Randomization of samples is mostly ideal for fully- experimental designs
in which samples are selected randomly for control and experimental groups
(Shadish et al., 2002). Therefore, we had two classes as our experimental group and
one class as our control group, each with forty participants. The treatment was
carried out in experimental groups –an online learning group through the LMS
instructional model and a blended learning group through the blended learning
instructional model, the control group held their usual classes using the traditional
teaching method (lecture and face-to-face teaching). The Learning Management
System (LMS) is a key web-based advancement for improving e-learning systems
that combine classroom instruction and online instruction in the learning process.
In educational institutions, whether in open-source programming (e.g., MOODLE)
or commercial programming (e.g., Blackboard), learning management system is
launched to encourage learners to schedule courses with a variety of resources, such
as discussion boards, forums, chat, online grade upload, online review, file sharing,
task management, syllabuses, planning, notices and curricula (Cole et al., 2019).

Participants
In the process of choosing the participants for this study, a Solution Placement
Test (SPT) was used on the vocabulary of the participants to homogenize them,
who were a sample of a private English language institution. One hundred and
twenty students participated in this experiment. Participants were randomly divided
into two experimental groups of the same size- an online learning group (OLG) and
a blended learning group (BLG), which received LMS instructional method and
blended learning instructional method respectively—and a control group (CG),
which followed the traditional learning method (each group had 20 male and 20
female intermediate EFL learners). The participants were aged between 18–20
years.

Instruments
Solution placement test (SPT)
SPT helped the researchers to determine the level of their subjects (i.e.
elementary, pre-intermediate, intermediate). A proficiency test was given to 120
EFL learners to check their similarity. This placement test has three parts: 50

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questions with multiple choices about grammar and vocabulary, a reading passage
with 10 questions to check how well students understand it, and an optional writing
task that shows how well students can produce the language.

Vocabulary pre-test
The purpose of the pretest was to check if there was any difference in the
vocabulary knowledge of the experimental and control groups. For this purpose, a
pretest involving 60 multiple choice cloze and vocabulary tests with 30 grades
based on the learners’ textbook (Family and Friends 2) was used to determine the
participants’ vocabulary learning. It was utilized to measure students’ vocabulary
knowledge in all groups before treatment. To make sure the test was valid and
reliable, the researchers chose another group that was similar to the experimental
and control groups to do the experiment. They checked how reliable and consistent
the SPT items and vocabulary tests were by doing a small study with 30 EFL
learners before they did the main statistical analyses.

Vocabulary post-test
The vocabulary post-test was the third tool that this research used. A standard
and reliable test similar to the pretest was used as a posttest after ten training
sessions at the end of the treatment to test the participants’ vocabulary knowledge.
The same test as the pre-test was used for the post-test. The form and number of
items of the post-test were identical to the pre-test. The only difference between the
post-test and the pre-test was that the questions and options were reordered so that
the students could not recall the answers from the pre-test. This helped the
researchers measure the impact of the treatment on students’ vocabulary knowledge

Procedure
120 Iranian EFL learners were divided them into three groups of equal size:
a group that learned online (OLG), a group that learned in a mixed way (BLG), and
a group that did not receive any treatment (CG). All groups took a pre-test to
determine initial differences or similarities in their vocabulary knowledge. Then the
training program started which lasted for 10 weeks. The teacher taught vocabulary
to the control group using a regular curriculum and traditional methods (lecture and
face-to-face teaching). When students came to class, they did not have a proper
understanding of the subject. Students have to do more detailed knowledge at home
which is called homework. In each session, the teacher taught 10 words. She
instructed the students to read the words and learn their meanings and spellings.
Then, she taught an English text that contained the words. Finally, she assigned the
students homework to write the words and meanings again at home.
An instructor taught vocabulary to the first experimental group (online group)
using LMS. Participants chose authentic practice materials. A place was considered
for exchanging opinions and solving the problems of the participants. The teacher
trained the first experimental group on how to use the LMS and overcome its
challenges before the experiment started. The teacher showed the participants how
to access the content online, how to use the LMS, and how to communicate with
the instructor online for specific training sessions. The purpose of this work was to
ensure that the online group participants could handle the LMS teaching format
without any issue in the test and finish the general English tasks and online tasks

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for the rest of the training program. The instructor made a question or problem about
a certain topic and put her students in pairs in the online class. The researchers gave
each pair of learners enough time to find the right answer and asked the students to
say their answers in their own words. This group learned 10 words in each online
session like the control group. The students received all the words and they had to
say their meanings. The students searched for meanings, synonyms, and antonyms
of the words and posted them in the online group. The teacher added images of each
word in the group to make word learning more interesting for the students.
This group was given a text with the target words to help them learn the words
in related sentences. The instructor taught the same English vocabulary to the
second experimental group with blended learning model. The teacher taught 10
words in person for 45 minutes to blended learning group in each session. The
students got the translation of the words; they learned their synonyms and
antonyms; and they studied the text. For the rest of the time, they received a picture
of each word in the group and did exercises online. The teacher was available online
to assist them if they required it. The participants were in a school that used
technology and they could use the computer to communicate with each other and
the teacher. The same teacher taught all three groups with the same goal and content
of the course. Each session lasted for 45 minutes for all students. At the end of the
study, all learners took the vocabulary post-test after 10 weeks of training sessions.
The post-test was identical to the pre-test, which was a valid and reliable test. They
scored the pre-test and post-test objectively and the scores of pretest and posttest
were between 0 and 30.

Data analysis
The researchers analyzed the data based on the research objectives after they
collected enough data. They checked the normality of data in the Skewness analysis
using Shapiro-Wilk test. Then, they used statistical tools such as paired samples t-
test and One-Way ANOVA to see the effect of treatment on improving learners’
receptive skills. They used SPSS version 22, a statistical software program, to
analyze the data.

Results of the reliability analyses

The researchers checked how reliable and consistent the items of the SPT and
the vocabulary tests were by doing a small study with 30 EFL learners before they
did the main statistical analyses. The reliability analyses results are presented in
Table 1.

Table 1. Reliability statistics for the SPT and the vocabulary tests
Instrument Cronbach’s Alpha N of Items N of sample
SPT .88 60 30
vocabulary test (pretest) .77 60 30
vocabulary test (posttest) .79 60 30

The estimated value of Cronbach’s alpha for the SPT (α= .88) was considered
a “very good” value based on the reliability standards suggested by (DeVellis,
1991). The reliability of the vocabulary tests showed that the values were acceptable
(α pretest=.77; α posttest=.79).

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Findings and Discussion

Results of solutions placement test (SPT)
SPT was used to ensure that the participants were similar. They chose 120
intermediate EFL who got 31+ in grammar and vocabulary, 8+ in reading, and 8+
in writing section as the main sample for this study based on the SPT test direction.
The SPT results are displayed in Table 2.

Table 2. Statistics for the solutions placement test

SPT
N Valid 120
Missing 0
Mean 53.1333
Median 54.0000
Mode 54.00
Std. Deviation 3.30503
Variance 10.923
Skewness -.047
Std. Error of Skewness .221
Kurtosis -.877
Std. Error of Kurtosis .438
Range 12.00
Minimum 47.00
Maximum 59.00
Sum 6376.00

Table 3 gives the group statistics for the placement test scores. It shows the
average (53.13), the middle (54.00), and the most frequent (54) scores for the SPT.
It also shows how much the scores differ from the lowest to the highest (12.00),
how much they spread out (10.92), and how much they are away from the average
(3.30). It also shows how much the scores are not symmetrical (-.047) and how flat
or sharp they are (-.877).

Assessing the assumptions of one-way ANOVA

The researchers checked the assumptions before they did one-way ANOVA.
The assumption of independence was checked by examining the research design. It
was found that three groups were independent from each other. The normality
assumption was checked by using the Shapiro-Wilks test, which is a common test
that uses a significance level of alpha (α=.01). From this test, the Sig. (p) values
were compared with the alpha level and it was decided to reject (p <α) or retain (p
> α) the null hypothesis. The normality assumption was also verified by using the
standardized skewness measure of normality along with the Shapiro-Wilk test,
which is a usual test that has an alpha significance level.

Table 3. Tests of normality for pre and posttest scores of the vocabulary
Groups Shapiro-Wilk
Statistic df Sig. skewness kurtosis
pretest Control .961 40 .186 -.078 .171
OLG .930 40 .016 -.211 -.874
BLG .934 40 .021 -.077 -.948

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Groups Shapiro-Wilk
Statistic df Sig. skewness kurtosis
posttest Control .950 40 .077 -.090 .514
OLG .939 40 .033 -.006 -.851
BLG .940 40 .036 .015 .733

The researchers used Shapiro-Wilk test to check if the pretest scores for each
group were normal. The test revealed that pretest scores for "control group" were
not significantly different from normal (p = .186), while pretest scores for both
"OLG" (p = .016) and "BLG" (p = .021) were significantly different from normal.
In addition, the p-value for posttest scores of "control group" came to (p = .077),
for posttest scores of the "OLG" was (p = .033), and for posttest scores of the "BLG"
came to (p= .036). The vocabulary scores followed a normal distribution based on
(p) values from Shapiro-Wilks test and using a significance level of (α = .01). As
seen in Table 4, the skewness and kurtosis measures were between -2 and +2, so
the data met the assumption of normality. The samples satisfied the normality
assumption. The next step was to check the assumption of variances using Levene’s
test, which tests the homogeneity of variances. Table 4 shows the results of this test.

Table 4. Test of homogeneity of variances

Levene Statistic df1 df2 Sig.
pretest .208 2 117 .813
posttest 1.822 2 117 .166

The results of Levene’s test showed that pretest and posttest scores had no
significant difference in variance; F pretest scores (2, 117) = .208, p= .813; F
posttest scores (2, 117) = 1.822, p= .166) with a significance level of .05. Therefore,
the sample satisfied the assumption of equal variance and the Levene statistics
supported the hypothesis of equal variance of the group (Figure 1).

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Figure 1. Error bars for examining the homogeneity of variances assumption

(Pretest and posttest)
As indicated in the figure above, the degree of variation from the mean score
in the participants' vocabulary performance was similar both at the beginning and
at the end of study. The pretest and posttest scores were analyzed with descriptive
statistics after confirming that the variance was homogeneous among the three
groups.

Results of the descriptive statistics

The purpose of conducting pretest at the beginning of study was to create a
basic measurement through which the EFL learners' achievements in the post-test
could be examined and explained. The students took posttest to measure their
vocabulary improvement. The data from the pretest and posttest were summarized
using descriptive statistics. Table 5 presents the summary statistics for vocabulary
scores before and after the intervention.

Table 5. Descriptive statistics for vocabulary test scores

N Mean SD 95% Confidence Min Max
Interval for Mean
Lower Upper
Bound Bound
Pretest Control 40 11.6750 1.45686 11.2091 12.1409 8.00 15.00
OLG 40 11.8000 1.50555 11.3185 12.2815 9.00 14.00
BLG 40 11.5500 1.50128 11.0699 12.0301 9.00 14.00
Total 120 11.6750 1.47906 11.4076 11.9424 8.00 15.00
Posttest Control 40 11.7500 1.42775 11.2934 12.2066 8.00 15.00
OLG 40 13.2000 1.63613 12.6767 13.7233 10.00 16.00
BLG 40 13.9000 1.78023 13.3307 14.4693 11.00 17.00
Total 120 12.9500 1.84186 12.6171 13.2829 8.00 17.00

The means vocabulary scores for the three groups in the homogeneous subsets
are revealed in Table 6. For the pretest of vocabulary, the means of control group,
OLG, and BLG were (M= Control = 11.67, M OLG = 11.80, and M BLG =11.55),
respectively. They differed by some points around their average in the vocabulary
pretest. The control group had a mean that was .125 points higher than the BLG and
.125 points lower than the OLG. The OLG group had a slightly better performance
than the other two groups in pretest. The standard deviation values showed that the
three groups had almost the same variation of the scores. Figure 2 shows the pretest
mean of three groups.

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Figure 2. The comparison of means of the three groups in pretest

The posttest scores had the following means for control group, OLG, and
BLG: (M= Control = 11.75; M OLG = 13.20; and M BLG=13.90). BLG group
performed the best among the three groups. The control group had a mean that was
1.45 points smaller than the OLG and 2.150 points lower than the BLG. The largest
difference in the posttest was between control group and BLG group (mean
difference= 2.15). The smallest difference among the two experimental groups was
observed (mean difference= of .700). Regarding the difference of scores from the
mean scores, the BLG group reflected a relatively higher variation in scores than
the other two groups. The posttest mean of three groups is indicated in Figure 3.

Figure 3. The comparison of means of the three groups in posttest

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The posttest of vocabulary showed that the performance of the three groups
was different. The control group scored the lowest mean in the post-test. On the
other hand, the second experimental group that was exposed to blended learning
had highest mean score among the other groups.

Results of the inferential statistics

Table 6 shows that the mean scores of the three groups in the vocabulary
pretest and posttest were not the same. The post-test had larger mean differences
than the pretest. The vocabulary scores before and after the intervention were
compared using one-way ANOVA to see if the mean differences were significant.
Table 6 depicts the results of the analysis.

Table 6. One-Way ANOVA for the pretest and posttest

Sum of df Mean F Sig.
Squares Square
pretest Between Groups 1.250 2 .625 .282 .755
Within Groups 259.075 117 2.214
Total 260.325 119
posttest Between Groups 96.200 2 48.100 18.301 .000
Within Groups 307.500 117 2.628
Total 403.700 119

Table 7 shows that the vocabulary pre-test scores of the three groups had no
significant difference in their means (F 2, 117= .282, Sig. = .755≥.05; p≥ .05).
Before the specific treatments were applied, three groups had comparable levels of
English vocabulary knowledge. On the other hand, the ANOVA table shows that
the F significance value for post-test scores was lower than (.05). The ANOVA F
ratio for the vocabulary post-test scores was statistically significant (F 2, 117=
18.301, Sig. = .00≤.05). Due to the significance of the overall group, several
comparisons were also conducted.

Table 7. Results of Scheffe test for the purpose of multiple comparisons

Dependent (I) (J) Mean Std. Sig. 95% Confidence
Variable Groups Groups Difference Error Interval
(I-J) Lower Upper
Bound Bound
Pretest Control OLG -.12500 .33274 .932 -.9500 .7000
BLG .12500 .33274 .932 -.7000 .9500
OLG Control .12500 .33274 .932 -.7000 .9500
BLG .25000 .33274 .755 -.5750 1.0750
BLG Control -.12500 .33274 .932 -.9500 .7000
OLG -.25000 .33274 .755 - .5750
1.0750
Posttest Control OLG -1.45000* .36251 .001 - -.5512
2.3488
BLG -2.15000* .36251 .000 - -
3.0488 1.2512
OLG Control 1.45000* .36251 .001 .5512 2.3488
BLG -.70000 .36251 .160 - .1988
1.5988
BLG Control 2.15000* .36251 .000 1.2512 3.0488
OLG .70000 .36251 .160 -.1988 1.5988
*. The mean difference is significant at the 0.05 level.

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The vocabulary scores of the three groups were compared using the Scheffe
test. The test revealed that there was no significant difference (p≥ .05) among the
three groups in their pretest scores. However, the control group scored significantly
lower (p ≤.05) than each of experimental groups in posttest. The post-test scores of
experimental groups did not differ significantly from each other (p≥ .05). The
figures below show the mean graphs of the pretest and post-test vocabulary.

Figure 4. Mean plot for the results of the pretest of vocabulary

As it was indicated in Figure 4, the pretest graph showed that the three groups
had similar scores.

Figure 5. Mean plot for the results of the posttest of vocabulary

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Figures 4 and 5 show the group means and how they are related linearly. The
chart for the posttest had significant differences among three groups. The means of
three groups were significantly different from each other, as shown by the F
statistics in Table 7. Participants who received blended vocabulary learning training
outperformed their peers who only practiced online vocabulary training and the
control group. Second, the group that worked on online vocabulary learning through
LMS performed better than the control group. The difference between the means
was tested with a post-hoc follow-up test. The post-hoc test (Scheffe) showed that
control group and BLG group had the largest difference in their means. The effect
of the two types of vocabulary training on the vocabulary improvement of Iranian
EFL learners was tested using paired-sample t-test. The test also compared the
progress of each group within itself.

Table 8. Paired T-test for the vocabulary tests

Groups Paired Differences
Mean SD 95% Confidence Interval t df Sig. (2-
of the Difference tailed)
Lower Upper
Control Pair pretest - -.075 .41 -.20 .05 -1.13 39 .262
1 posttest
OLG Pair pretest - -1.40 .67 -1.61 -1.18 -13.18 39 .000
1 posttest
BLG Pair pretest - -2.35 1.09 -2.70 -1.99 -13.52 39 .000
1 posttest

The paired t-test showed that the participants’ vocabulary learning improved
in post-test phase for all three groups. However, the experimental groups that
received specific vocabulary instruction had more progress than control group. The
control group had a .075 point increase from the pretest to posttest. The second
experimental group that used blended learning improved their vocabulary more
than the first experimental group that only had online instruction through the LMS.
While OLG group improved by 1.40 points, this progress reached 2.35 points for
BLG group. The paired t-test revealed that the control group had a slight
improvement, but it was not significant (p≥ .05). On the other hand, two
experimental groups had a significant improvement in vocabulary from the pretest
to posttest (p≤ .05).

Discussion
The post-test scores of the three groups for the dependent variable were
significantly different from each other, as indicated by ANOVA test. The three
groups started with the same level of vocabulary learning, but after the experimental
group received specific treatments, they had a significant difference in their
vocabulary improvement compared to the other two groups (p≤ .05). The post-test
scores of control group were lower than the scores of two experimental groups that
received online and blended vocabulary instruction, respectively, according to
statistical analysis. The two experimental groups that had specific vocabulary
training did not differ significantly in vocabulary learning, according to Scheffe
test. Unlike the control group, two experimental groups improved significantly
from the pretest to posttest, as shown by paired t-test results. Therefore, the null

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hypothesis that the three groups had the same mean was rejected (p < .05). The
conclusion was that online and blended learning instructions helped learners
develop their vocabulary learning and had a great impact on Iranian intermediate
learners’ vocabulary learning.
The data analysis showed that the experimental groups that used LMS or a
mix of LMS and face-to-face instruction had better vocabulary learning than the
traditional instruction group. There are several possible reasons for the success of
these experimental groups. First, it can be explained that LMS created an
opportunity to implement useful learning practices in an active environment that
was interesting and motivating for the learners. It was possible for the users to do
online vocabulary activities and thus learning could happen beyond the classroom
and they were prepared for classroom activities. It was easy for teachers to upload
vocabulary lessons into the LMS and develop different types of vocabulary practice
programs to support learners with different learning needs. Teachers could easily
track learners’ vocabulary improvement and provide feedback on learners’
language performance. The control group participants did not get immediate
feedback when they made mistakes. Participants in the two experimental groups
had the opportunity to check their answers immediately and develop their
understanding of the vocabulary exercises. These findings are consistent with
Khodaparast and Ghafournia’s (2015) research and show that online platforms
facilitate the provision of feedback and improve learners’ vocabulary gains.
Another explanation is that there were many opportunities for teachers to
provide authentic and rich input to learners. They can also plan, implement, and
evaluate learners’ vocabulary learning using LMS. The frequency of chances
teachers had to assess learners’ vocabulary promoted learners’ vocabulary
achievements and led to more opportunities for learners to experience target words,
which had a positive effect on their word retrieval in the two experimental groups.
This is line with research by Timmis et al. (2016) who have demonstrated that
technology offers many potential opportunities for assessment practices. This result
correlates well with previous studies such as Bancha (2012) wherein he showed that
the rate of testing makes learners put more effort into vocabulary learning and
enhances vocabulary recall and retention.
The integrated implementation of LMS and classroom teaching enabled
active participation of learners in educational process. The LMS program enabled
the participants of both experimental groups to store information in their memory
through three different ways: seeing, hearing, and understanding. Visual encoding,
vocabulary items presented as stimuli seen in the LMS program can be stored,
remembered, and retrieved with the help of the visual images (Khenissi et al., 2017).
LMS users and those using blended learning had a wide choice of vocabulary
learning strategies to use, including guessing, repeating words for practice, and
encoding. This means that the LMS program and blended learning allow learners
to experience a dynamic vocabulary learning process that includes metacognitive
choices and cognitive implementation of different strategies.
The other issue was the availability of LMS outside the classroom and this
can be useful in helping learners to be autonomous language learners who can their
learning to their own success. When the LMS was combined with face-to-face
learning, it created a blended learning environment where learner autonomy was
developed. They accessed the lessons as many times as they needed. They could

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learn at their own speed and be accountable for their own learning, as well as finish
tasks and extend their learning outside the classroom setting. It is argued that a
personalized learning environment is created in blended learning which helped both
the gifted learners and those less skilled who may not perform well in conventional
classroom learning. Moreover, the availability of LMS exercises allowed learners
to do the exercises as often as needed so that they could practice the vocabulary
exercises more skillfullly. Hajebi et al. (2018) reached a similar result. They found
that access to vocabulary exercises in online platforms such as LMS helped learners
remember words more efficiently.
The previous studies that demonstrate the advantages of blended teaching for
EFL learners’ language learning are supported by this research (Kafes & Caner,
2020; Taysi & Basaran, 2018; Yesilbag & Korkmaz, 2021). This study verified that
online learning through LMS and blended learning in mixed online and face-to-face
learning environments both yielded relatively similar outcomes. The average scores
of blended learning group were higher than the scores of LMS group, but this
difference was not important. The findings of many studies (Krishnan & Yunus,
2019; Mustafa et al., 2019; Novitasari et al., 2018; Shabaneh & Farrah, 2019)
supported the effective role of LMS in improving learners’ vocabulary
development. The reason for the difference between two experimental groups is
that blended learning group saw more words than LMS group and participants
interacted through online and face-to-face learning because of blended learning
(Singh et al., 2021). Consistent with previous studies (Yunita, 2020), it was
observed that the LMS was an effective supplement to classroom instruction. That
is, online teaching vocabulary resources work best when they are accompanied by
teachers’ explanations in a blended environment. Therefore, learners’ vocabulary
learning is improved by the combination of technology and face-to-face instruction,
according to the findings.
However, contrasting evidence exists about the effect of blended learning on
language learning. For instance, a study conducted in China found that while
students believed that blended learning had a positive impact on their achievement,
empirical evidence showed no significant improvement (Chang et al., 2014).
Similarly, research conducted in Hong Kong, China did not show a significant
difference in learning achievements between blended and traditional approaches
(Yick et al., 2019). The findings of this study are in contrast with the study
conducted by Al-Qatawneh et al. (2020), which found no significant difference in
attitudes toward blended or traditional approaches, which could be due to either
internal or external factors.
A study conducted at Point Loma Nazarene University in the USA also found
no significant difference between blended and traditional instruction, and students
also spent less time learning in blended courses (Botts et al., 2018). Finally, students
in a blended learning course at an undergraduate university in Alberta, Canada,
despite positive perceptions of blended learning, had no significant differences in
self-efficacy and knowledge scores compared to those who used non-blended
learning (Berga et al., 2021).

Conclusion
The findings indicated that the combined use of classroom teaching along
with the LMS Web-based technology helped teachers plan, implement, and assess

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students' vocabulary learning more efficiently than using the LMS program in
developing learners’ vocabulary learning. The creation of specific educational
conditions is needed for the successful use of technologies, and teachers should
know the digital skills of learners before using a web-based LMS. Although the
implementation of web-based technologies has its difficulties, a balanced
combination of LMS system with face-to-face teaching can be more effective by
encouraging collaboration and participation between teacher and learners and
providing useful experiences while working in LMS. That is, classroom training
can be supported by integrating the LMS system to solve the problems of traditional
classes like time constraints and instructional facilities. It is also concluded that
technology helps improve vocabulary learning and LMS can facilitate vocabulary
learning experience. In addition, teachers should encourage their learners to use
advanced technology and provide them with accessible learning materials that are
modified based on learners’ preferences and characteristics so that learners can
experience an effective blended learning environment. Most importantly,
implementing effective blended learning requires developing a method to help
learners become motivated to learn vocabulary.
The findings have practical implications for teacher education programs to
promote teachers’ interest and eagerness to implement web-based systems. Future
teachers need to develop a positive attitude towards using LMS system and learn
how to effectively integrate LMS into their classroom teaching through pre-service
and in-service training courses. The study findings have important implications for
web-based application developers. A clear model for blended learning should be
considered and teachers should have the option to select a blended learning model
that fits their teaching situations in order to control the classroom and offer a more
effective learning environment. Educators should arrange workshops for students
to improve their computer skills and help them develop a positive attitude towards
using web-based programs for learning vocabulary, since the attitude and digital
competence of learners towards LMS is important in the development of their
language learning.

Limitations of the study

This study showed how vocabulary learning can be facilitated by online and
blended learning, but it has some limitations. First, the study only focused on
examining the effects of LMS as a web-based program and blended learning on the
vocabulary development of EFL learners in a language institute. Therefore, the
findings may not be generalizable to other educational contexts such as public or
private schools. To get a broader picture of the implementation of blended learning,
extensive research can be conducted in other educational settings like universities
or public schools. Furthermore, the study examined the effects of LMS at the
intermediate level and therefore cannot represent other levels. The sample size was
also limited to 120 EFL learners. The other limitation of this study is that among
various features of word knowledge, this study has focused only on meaning. In
other words, other word features like pronunciation, spelling, word parts, and word
accents were not evaluated when judging learners’ vocabulary development.

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Suggestions for further research

Further studies are suggested to investigate the advantages and disadvantages
of the LMS system and to examine the challenges LMS users face while learning a
foreign language. The problems that prevent learners from successfully using the
system to improve their vocabulary and the benefits that motivate them to work in
the LMS system can be comprehensively studied in future studies. Future research
can be done to investigate the educational opportunities that can be created by
integrated uses of LMS system and classroom teaching regarding teacher-student
collaboration. In addition, future work on online and blended learning could
enhance language skills and sub-skills or other language components like grammar
through the use of web-based programs such as mobile apps or social media
applications as well as online software, which are available in the market. A more
comprehensive methodology such as a mixed method can be used in future
research. For example, triangulation can be achieved by conducting interviews,
administering questionnaire, and conducting observations to obtain more detailed
information about the effects of online vocabulary instruction on language learners'
vocabulary development. Finally, studies can be carried out to examine the possible
effects of using online platforms on learners' word knowledge in more specific areas
such as their understanding of collocations, syntactic associations, and grammatical
functions of words.

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