| Research Papers
JOURNAL OF LANGUAGE & EDUCATION
https://doi.org/10.17323/jle.2023.13187
The Development of a Reflective
Language Learning Model: A Structural
Equation Modeling Approach
Salman Asshabi 1 , Mojgan Rashtchi 2 , Massood Siyyari 2
1
Islamic Azad University, Science and Research Branch, Tehran, Iran
2
Islamic Azad University, North Tehran Branch, Tehran, Iran
ABSTRACT
Background: Several language learning theories exist to explain the language learning process.
Reflective learning is one of the models that has received attention and has been employed to
explain language learning and teaching.
Purpose: The present study aimed to develop and validate a close-ended reflective language
learning instrument to discover EFL learners’ reflective learning strategies while learning a
language.
Method: Based on a comprehensive literature review, 358 concepts were extracted for reflective
language learning. Then, experts’ opinions on reflective language learning were gathered,
leading to the extraction of 50 general themes. After the experts’ approval, the researchers
transformed the concepts into statements and constructed the final version of the questionnaire.
In the next step, the initial version of the questionnaire was piloted with 100 participants,
reducing the number of items to 47. Then, the piloted instrument was administered to a
sample of 398 students. The obtained data were entered into SPSS and LISERL for exploratory
and confirmatory factor analyses. Principle Component Analysis (PCA) was employed to run
an explanatory factor analysis. Varimax rotation was performed on the underlying construct
of the 47-item questionnaire. The result was the removal of four items and forming a 43-item
questionnaire. A six-factor model of second language learning encompassing twelve behavioral
cognitive items, twelve behavioral evaluative items, six behavioral metacognitive items, six
behavioral interactional items, four behavioral reflective journal items, and three behavioral
retrospective items was obtained. Then, the researchers performed confirmatory factor analysis
to verify the six factors. Finally, a reflective language learning model was developed.
Results: The results showed that the newly developed Reflective Language Learning
Questionnaire (RLLQ) was valid and reliable. The model formulated based on the data gathered
from the administration of RLLQ also enjoyed acceptable fitness indices.
Citation: Asshabi S., Rashtchi M., &
Siyyari M. (2023). The Development
of a Reflective Language Learning
Model:
A
Structural
Equation
Modeling
Approach.
Journal
of
Language and Education, 9(4), 11-30.
https://doi.org/10.17323/jle.2023.13187
Correspondence:
Mojgan Rashtchi,
[email protected]
Received: October 09, 2021
Accepted: December 15, 2023
Published: December 30, 2023
JLE | Vol. 9 | No. 4 | 2023
Conclusion: The questionnaire could be used in future studies. Researchers interested in
reflective language learning, language teachers intending to follow reflective practices in their
classes, and syllabus designers believing that reflection promotes learning can employ RLLQ.
KEYWORDS
construct validation, language learning, model development, reflection, Reflective Language
Learning Questionnaire (RLLQ)
INTRODUCTION
Throughout the history of English language teaching, controversies regarding learning a new language have been
conspicuous among pedagogy practitioners and researchers. Such disputes
have been due to perspective changes in
defining language, learning, and teaching. Thus, researchers’ quest to develop
successful language learning models has
been a central issue. One such model is
reflective learning, which has been explored by several researchers (Gadsby,
2022; Kolb, 1984, 1994; Schön, 1987) since
Dewey published his inspiring viewpoints
regarding reflective thought in 1933. The
effect of reflection in language teaching
and learning is undeniable since reflection occurs in everyday activities in the
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Salman Asshabi, Mojgan Rashtchi, Massood Siyyari
human mind. Reflective learning is synonymous with lifelong learning (Tan, 2021); thus, it can be employed in different learning contexts (Griggs et al., 2018).
Reflective learning has its roots in reflective thinking, which
is crucial in fostering individuals’ intellectual processes to
become efficient in problem-solving and decision-making.
Reflective thought embraces “active, persistent and careful
consideration of any belief or supposed form of knowledge
in the light of the grounds that support it and the further
conclusion to which it tends” (Dewey, 1933, p. 6). According
to Dewey, reflective learning consists of two interrelated notions: first, a state of mental doubt in which thinking originates, and second, an act of inquiring to settle hesitation
and perplexity, which could be resolved if explored through
empirical studies. Schön (1983; 1987), who has a decisive
role in expanding the notion of reflective learning, argues
that learners’ reflection on their own learning promotes
learning. He distinguishes between reflection-in-action and
reflection-on-action. Reflection-in-action is the activity that
learners engage in as they encounter a problem in a learning context. Reflection-on-action is a process that occurs after learners’ engagement in a learning context, and finally,
in ‘reflection-for-action,’ individuals start planning materials. Therefore, the communal principle implied in reflective
learning is that reflective thinking integrates “knowledge,
practice, and human experience” (Colomer et al., 2013, p.1).
What is essential is realizing that reflection is generally manifested in learners’ actions when engaged in reflective practice (Alt et al., 2022).
Reflective learning explains reflection’s role in teaching and
learning and helps analyze the experience individuals have
gained as a learning outcome. Kolb’s (1984) experiential
learning, developed based on Dewey’s notions of reflection,
indicates that individuals learn from their daily life experiences as they are engaged in reflection. Kolb and Kolb (2005)
argue that personal experiences are the source of learners’
autonomous learning and critical thinking.
However, using reflective practices is not limited to language learning and teaching. Several studies other than
language teaching and learning have reported their efficacy
(Cicmil & Gaggiotti, 2018; Rogers et al., 2019; Winkel et al.,
2017). Moreover, studies on different aspects of reflective
learning at university levels indicate that it significantly improves various aspects of learning (Aryani et al., 2017; Feng,
2016; Kember et al., 2000). Some studies have supported
the role of reflective journals in improving reflective thinking (Bruno & Dell’Aversana, 2017; Griggs et al., 2018). Still,
some others have shown the effect of reflective practice on
language learning (Fuertes-Camacho et al., 2021; Southcott
& Crawford, 2018).
However, the critical issue that motivated the current study
researchers is understanding the effects of reflective activities on language learning and discovering the types of
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reflective learning strategies learners use while engaged
in reflective practices. Therefore, the researchers aimed to
construct a close-ended questionnaire to measure learners’ learning strategies during reflective language-learning practices. The researchers assumed that developing a
closed-ended reflective language learning scale can help
EFL/ESL teachers understand the extent to which students
get involved in reflective practices. Besides, they can specify
strategies learners use during such procedures, resulting in
cognitive processes responsible for learning. Such a scale
can also help English language learners employ strategies
to promote reflective learning. To achieve the study objectives, the researchers formulated the following research
questions:
RQ1: What are the main components of Iranian EFL learners’ language reflectivity?
RQ2: Is the newly developed reflective language learning
questionnaire a reliable and valid data collection instrument?
LITERATURE REVIEW
Reflective Learning
Experiential learning, as the core concept of reflective learning, is a process by which learners reflect on their experience and obtain more understanding from such a reflection
(Morris, 2020). Dewey asserts that when learners reflect,
they confront emerging doubts, followed by a reflective
process, and end in more understanding. For Schön (1983),
reflection is the ability to think and decide how to act while
doing a task (reflection in action). Thus, reflective learning usually deals with practical problems, accompanied by
doubt and perplexity, before possible solutions (Fullana et
al., 2016). Schön completes his view on reflection in action
by a complementary stage of reflection or reflection on
action, which refers to deep thinking about an experience
and re-evaluating the decisions one made while performing an action. Hierarchical levels of reflection are observed
in reflecting on action. Grossman (2008) believes in at least
four levels of reflection along a continuum, ranging from
descriptive accounts to varying levels of mental processing
to transformative or intensive reflection. Other scholars
suggest an increasing complexity such as reporting, responding, relating, reasoning, and reconstructing to define
it (Marcos et al., 2009). However, most scholars agree that
reflection is deliberate, purposeful, cognitive, and metacognitive thinking, which results in people improving their
professional practice (Sellars, 2013; Yesilbursa, 2011). Kolb
(1984) believes experiential learning is a sequential activity
during which students achieve a broader understanding of
the subject matter and become capable of generalizing new
knowledge and putting it into further action. Thus, reflective
learning is a deliberate process of cycles of inquiry in which
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Relective Language Learning Model
learners move between action and reflection to understand
a concept (Ramsey, 2006), resulting in a deep understanding
of new concepts.
Reflective Learning Models
Several reflective learning models have been proposed
based on Dewey’s viewpoints on reflection. A model that
has a vital role in understanding reflective learning is Kolb’s
(1984) four-stage experiential learning model, consisting of
four stages: (a) experience (Concrete Experiences), meaning
that all individuals have the opportunity to start the learning
cycle in any situation or place, (b) reflect (Reflective Observation) which involves thinking about what a person has done
and experienced, (c) conceptualize (Abstract Conceptualization) which is making a hypothesis about one’s experiences,
and (d) plan (Active Experimentation), that is, testing the hypothesis that a person has adopted. Kolb’s learning model
is cyclical, and the end of one cycle is related to initiating a
new one. For Kolb, learning is a cognitive process, and individuals build knowledge based on their experiences with the
environment rather than instruction. The challenges they
encounter shape their learning process, and they pass the
stages of action, reflection, feeling, and thinking. The advantage of Kolb’s model over other models is that it considers
learning styles and individual preferences in learning (Kolb
& Kolb, 2009).
Other reflective models that have played a vital role in constructing associations between experience, learning, and
reflection are Boud et al.’s triangular representation (1985),
Gibbs’ reflective cycle (1988), and Atkins and Murphy’s
(1993) cyclical model. Another example of a reflective model is Moon’s (2004) five-stage reflective learning model. For
Moon, noticing, making meaning, making sense, working with
meaning, and transformative learning are significant in reflective learning. He asserts that without noticing, learning
cannot happen; in making meaning, contextualization is vital, and making sense is equal to comprehension. Students
gradually understand meaning and probably change their
overall understanding by analysis.
However, some other models have developed reflective
models with different dimensions. For instance, Black and
Plowright (2010) constructed a multi-dimensional model of
reflection consisting of “the source, target, and purpose of
reflection” (p. 256). They argue that the reflective process
could occur through written and internal dialogue with
“self.” Davys and Beddoe’s (2009) reflective learning model
of supervision rests on “the premise that supervision is a forum for learning and that the main vehicle for learning is reflection” (p. 920). Ideas and understanding are synthesized
in the transformative learning stage, resulting in students’
ability to evaluate the processes that lead to new knowledge.
In a more recent model, Jasper (2013), inspired by Kolb, proposes three stages of experience, reflection, and action for
reflective learning and argues that individuals’ experiences
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(positive or negative) provoke reflection and lead them to
take action.
Reviewing the models indicates that although they may portray different stages for reflective learning, all share three
vital stages: experiencing a challenging situation, reflecting
on the situation to solve a problem, and learning from the
experience by evaluating it. All models suggest that reflection contributes to learning and boosts the impact of teaching on learning. Thus, examining students’ reflection levels
by developing a scale can illuminate the processes they follow in reflective learning.
Measuring Reflective Learning
To measure reflective learning, some researchers have employed journal writing in different fields, such as medicine
(Pena-Silva et al., 2022; Rogers et al., 2019), engineering (Aryani et al., 2017), management (Gray, 2007; Loo & Thorpe,
2002), and teaching (Sabah & Rashtchi, 2016; Wallin & Adawi,
2018). Some others have focused on developing validated
tools to contribute to understanding the “multi-dimensional nature” of reflective learning (Black & Plowright, 2010, p.
246). One such study was Kember et al.’s (2000), through
which they developed a valid questionnaire using confirmatory factor analysis. Kember et al. extracted four factors
for reflective learning: habitual action, understanding, reflection, and critical reflection, examining the extent to
which students engage in reflective thinking in professional
preparation courses. In another study, Peltier et al. (2005)
developed a standard scale to measure four identified levels
of reflection hierarchy (habitual action, understanding, reflection, and intensive reflection) of MBA program students.
However, the authors suggested further studies using
structural equation modeling to discover the relationships
between several variables in reflective learning.
Colomer et al. (2013) also developed a Self-Reported Reflective Learning Questionnaire to examine students’ views on
teaching methods. The researchers were interested in finding the relationship between the participants’ responses to
the questionnaire and their experience, knowledge, self-reflection, and self-regulation. Besides, they intended to discover the students’ difficulties in integrating reflective learning methodologies and learning processes.
Similarly, Min and Park (2019) intended to measure upper-secondary learners’ reflective attitudes toward conversation. To this end, they constructed a 12-item questionnaire under the three constructs: thoughtful action, content
and process reflection, and premise reflection. The study’s
results showed that the instrument measured participants’
reflective attitude toward conversation; however, answering the questionnaire during or after conversation affected
the level of reflective thinking.
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Salman Asshabi, Mojgan Rashtchi, Massood Siyyari
Another way to explore the nature of reflective learning is
by using open-ended questionnaires. For example, Bell
et al. (2014) analyzed 150 participants’ responses to four
open-ended questions to examine whether they could
change their viewpoints in favor of reflective thinking. Feng
(2016) also developed an open-ended scale for measuring
learners’ intercultural competence, employing Kolb’s fourstage learning cycle. The researcher provided a detailed
description of the participants’ answers to the open-ended
questions (qualitative) and compared respondents’ pre and
post-performances on a survey.
However, none of the scales discussed so far was intended
to explore different aspects of reflective learning techniques,
such as cognitive, meta-cognitive, evaluative, and the like, to
understand what occurs in the learners’ minds and behavior while attempting to learn a new concept. Besides, the instruments were not designed and employed among EFL/ESL
learners.
Thus, the current researchers found it logical to construct a
Reflective Language Learning Model comprising all learning
strategies involved in the process of language learning activities. The objectives of the present study were twofold: Firstly,
constructing a reflective language learning instrument, and
secondly, extracting a model of reflective language learning
that can be used by language learners, teachers, and researchers in future studies.
METHOD
Constructing the Item
The researchers followed the stages proposed in the literature to develop a reflective language learning questionnaire model in the Iranian EFL context (Dörnyei, 2003, 2007;
Coombe & Davidson, 2015). In the first step, the researchers
reviewed the related literature (Dewey, 1993; Schön,1983,
1987; Kolb, 1984; 1994; 2005) to collect definitions, explanations, and concepts on the nature of reflection and reflective
learning. Then, they reviewed several models (Atkins &Murphy,1993; Boud et al.,1985; Gibbs, 1988; Kolb, 1984, 1994;
Moon, 2004) to understand reflective learning processes
conceptualized by researchers. At this stage, the components of reflective learning were discovered. Kember et al.’s
(2000) study provided a picture of different reflective and
adult learning concepts. Peltier (2005) and Colomer (2013)
helped discover the reflection/non-reflection dichotomy and
the different views on reflection. The researchers detected
some general themes at each stage and then attempted to
break them into smaller components. The result was to identify 358 concepts, definitions, and activities for reflective language learning.
The researchers explored experts’ opinions regarding reflective learning in the next step. They extracted seven interview
14
questions and asked a panel of five male and female applied
linguists with over twenty years of experience teaching at the
university level (two professors and three associate professors) to rate them as “essential,” “useful but not essential,”
and “not necessary” (Ayre & Scally, 2014). All experts agreed
that four questions would be essential, and three were unnecessary. Content Validity Ratio (CVR) was calculated for the
questions, indicating that the questions were crucial. Then,
interviews were conducted with the same five experts on
four validated questions (see Appendix A). Each interview
session took about 45 minutes. The interviews were recorded, and the themes were extracted following a deductive
approach (Bingham & Witkowsky. 2022). First, broad themes
related to reflective learning were extricated and then categorized to obtain a body of experts’ viewpoints. In the next
step, the themes that overlapped with the concepts in the
literature (at the first stage) were located, classified, and
reduced in number. Repeating the procedure several times
decreased the number of items to 50. After transforming the
concepts into statements and revising them, the panel of experts re-examined them to construct the questionnaire draft
for the pilot study.
Participants
In the first phase, 100 EFL learners (34 males and 66 females),
selected based on convenience sampling, participated in piloting the newly developed questionnaire. Their age ranged
between 20 and 45. All participants studied TEFL at the university in different semesters (from the 1st to the 8th). The participants’ characteristics in the piloting phase were similar to
the target group for whom the questionnaire was designed.
In the second stage, 398 participants were selected based
on convenience sampling. They signed an informed consent
and agreed to take an Oxford Placement test two weeks before answering the questionnaire to let the researchers know
their English proficiency level. Then, for construct validation
of the questionnaire, they answered the newly developed
questionnaire. Table 1 shows their demographic information.
Piloting the Questionnaire
A primary step in developing a questionnaire is field testing,
which refers to piloting with a group of respondents similar
to the target population (Dörnyei, 2007). Thus, the researchers administered the 50-item reflective language learning
questionnaire to the 100 participants (as explained above).
Then, they entered the data into SPSS to compute its reliability via Cronbach’s α, which appeared to be .943 (Table 2).
However, after examination, items 36, 43, and 46 were removed due to the low values (<.3) of corrected item-total correlations (Table 2). The analysis of the remaining
47 items, with corrected item-total correlation values
over .3, showed that Cronbach’s α value was .946 (Table 3), indicating an acceptable internal consistency.
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Table 1.
Participants’ Characteristics in the Second Phase
Proficiency Level
Gender
Age Range
Male
257
A2
90
20-24
184
Female
128
B1
89
25-29
56
B2
93
30-34
16
C1
65
35-39
20
C2
61
40-44
16
45-49
14
50 or more
10
Not mentioned
69
Learning Context
University Students
322
Language Institutes Learners
63
Table 2
Item Analysis for the 50-item Questionnaire
Corrected Item-Total Correlation
Cronbach’s Alpha if
Item Deleted
Corrected Item-Total Correlation
Cronbach’s Alpha if
Item Deleted
Item 1
.516
.942
Item 26
.412
.942
Item 2
.574
.941
Item 27
.627
.941
Item 3
.429
.942
Item 28
.555
.941
Item 4
.459
.942
Item 29
.575
.941
Item 5
.370
.943
Item 30
.473
.942
Item 6
.460
.942
Item 31
.522
.942
Item 7
.486
.942
Item 32
.470
.942
Item 8
.470
.942
Item 33
.566
.941
Item 9
.474
942
Item 34
.613
.941
Item 10
.573
.941
Item 35
.447
.942
Item 11
.405
.942
Item 36
.107
.945
Item 12
.551
.942
Item 37
.618
.941
Item 13
.443
.942
Item 38
.529
.942
Item 14
.553
.942
Item 39
.505
.942
Item 15
.412
.942
Item 40
.478
.942
Item 16
.628
.941
Item 41
.481
.942
Item 17
.547
.942
Item 42
.483
.942
Item 18
.477
.942
Item 43
.205
.944
Item 19
.511
.942
Item 44
.610
.941
Item 20
.523
.942
Item 45
.613
.941
Item 21
.484
.942
Item 46
.260
.943
Item 22
.527
.942
Item 47
.594
.941
Item 23
.585
.941
Item 48
.501
.942
Item 24
.449
.942
Item 49
.574
.941
Item 25
.492
.942
Item 50
.423
.942
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Table 3
Item Analysis for 47-Item Questionnaire
Corrected Item-Total
Correlation
Cronbach’s Alpha
if Item Deleted
Corrected Item-Total
Correlation
Cronbach’s Alpha
if Item Deleted
Item 1
.526
.945
Item 26
.409
.946
Item 2
.572
.945
Item 27
.623
.945
Item 3
.437
.946
Item 28
.572
.945
Item 4
.453
.946
Item 29
.589
.945
Item 5
.357
.946
Item 30
.462
.946
Item 6
.468
.946
Item 31
.517
.945
Item 7
.486
.946
Item 32
.473
.946
Item 8
.476
.946
Item 33
.570
.945
Item 9
.476
.946
Item 34
.607
.945
Item 10
.575
.945
Item 35
.438
.946
Item 11
.411
.946
Item 36
.618
.945
Item 12
.551
.945
Item 37
.526
.945
Item 13
.463
.946
Item 38
.493
.945
Item 14
.577
.945
Item 39
.468
.946
Item 15
.426
.946
Item 40
.482
.945
Item 16
.630
.945
Item 41
.493
.945
Item 17
.544
.945
Item 42
.618
.945
Item 18
.462
.946
Item 43
.620
.945
Item 19
.524
.945
Item 44
.585
.945
Item 20
.528
.945
Item 45
480
.946
Item 21
.489
.945
Item 46
.574
.945
Item 22
.533
.945
Item 47
.429
.946
Item 23
.587
.945
Item 24
.458
.946
Item 25
.498
.945
Validating the Questionnaire
After ensuring its face validity, computing the reliability
indices, and removing redundant items, the 47-item scale
was administered to 398 participants to gather data for exploratory and confirmatory factor analyses. Exploratory Factor Analysis (EFA) draws on various techniques to uncover
the underlying structure and extract latent factors (Pallant,
2007). Confirmatory Factor Analysis (CFA) tests whether the
data fit a hypothetically constructed model. After performing EFA, the number of items was reduced to 43. Afterward,
the researchers ran a CFA to confirm the extracted factors.
Linear Structural Relations Software (LISREL) was used to
perform Structural Equation Modeling (SEM). The developed model was verified in the CFA. The following sections
present the different steps in detail.
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RESULTS
Exploratory Factor Analysis (EFA)
EFA started with data cleaning by discarding 13 questionnaires due to incomplete answers and running data analysis with 385 questionnaires. The Kaiser-Meyer-Olkin (KMO)
measure of sampling adequacy value (.948, beyond .60 ) and
Bartlett’s Test (p<.001) verified the appropriacy of the data
for factor analysis (Table 4).
Principal Component Analysis (PCA) was used to run EFA as
the most commonly adopted approach. A factor analysis
through varimax rotation was conducted on the underlying
construct of the 47-item questionnaire. As Table 5 shows,
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Table 4
KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy
Bartlett’s Test of Sphericity
Approx. Chi-Square
.948
9470.951
df
1081
Sig.
.000
Table 5
PCA on 47-Item Questionnaire
Initial
Eigenvalues
Component
Extraction Sums of Squared
Loadings
Rotation Sums of Squared
Loadings
Total
% of
Variance
Cumulative
%
Total
% of
Variance
Cumulative
%
Total
% of
Variance
Cumulative
%
1
17.231
36.662
36.662
17.231
36.662
36.662
5.648
12.017
12.017
2
2.335
4.969
41.631
2.335
4.969
41.631
5.221
11.108
23.124
3
1.698
3.612
45.243
1.698
3.612
45.243
4.498
9.570
32.695
4
1.558
3.315
48.558
1.558
3.315
48.558
3.963
8.431
41.125
5
1.250
2.660
51.217
1.250
2.660
51.217
3.313
7.048
48.174
6
1.188
2.528
53.745
1.188
2.528
53.745
2.494
5.307
53.480
7
1.139
2.424
56.171
1.139
2.424
56.169
1.264
2.689
56.169
Note: Extraction Method: Principal Component Analysis
SPSS extracted seven factors, with an Eigenvalue of more
than 1, that explained 56.17% of the variance. Six-point Likert scales were used for each item, ranging from 1 (false), 2
(mostly false), 3 (more false than true), 4 (more true than
false), 5 (mostly true), to 6 (True).
Table 6 contains the initial commonalities before rotation.
The initial communalities indicate the relation between the
variable and all other variables (the squared multiple correlations between the item and all other items). As evident
from Table 6, all commonalities are high (>.40) and thus acceptable. Communality values for this questionnaire ranged
from 0.40 to 0.70.
As Table 7 shows, seven factors load after rotating the factors in PCA. Subsequent to checking the factor loadings,
items that do not load highly on any of the factors should
be excluded. Items loading above .40 are acceptable. In this
phase, 44 items were acceptably loaded on the seven factors, and three (6, 12, & 35) were deleted due to item loading
below .40. Table 7 lists the 12 items that have the highest
and lowest item loadings: factor 1 twelve items (the highest:
item 29 to the lowest: item 34); factor 2, twelve items (the
highest: item 42, the lowest: item 41), factor 3 six items (the
highest: item 3, the lowest: item 5), factor 4 six items (the
highest: item7, the lowest: item 18), factor 5 four items (the
highest: item 20, the lowest: item 19), factor 6 three items
(the highest: item 47, the lowest: item 14), and finally factor
7, 1 item (the highest and lowest: item 45).
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The Scree plot in Figure 1 shows a clear break between the
first and second components. The Scree plot also indicates
another little break after the seventh component, recommending retaining (extracting) seven components. The results suggest that the seven factors are confirmed, and the
developed items are approved. Thus, the 43-item Reflective
Language Learning Questionnaire (RLLQ) is a valid and reliable data-gathering instrument.
Table 8 shows the categorization of the RLLQ for the six factors and the reliability indices for each factor. The researchers excluded factor 7 since it possessed only 1 item loading
(Item 45) and was problematic for reliability and confirmatory features. The items clustering under the same factor
were checked for commonality among them. The result was
extracting six factors: “Cognitive,” “Evaluative,” “Metacognitive,” “Interactional,” “Reflective Journaling,” and “Retrospective,” the details of which are explained in the discussion section. As illustrated in Table 8, the reliability of the
43-item RLLQ is .963.
Confirmatory Factor Analysis (CFA)
After gaining the six main factors by EFA (with 43 items), the
researchers ran CFA to confirm the six factors. SEM was performed employing CFA-LISREL 8.0 to examine the factors
underlying reflective language learning and checking item
quality. Figure 2 displays the measurement model for the
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Table 6
Initial Communality Values in PCA in the 47-Item Questionnaire
Initial
Extraction
Initial
Extraction
item1
1.000
0.503
item25
1.000
0.625
item2
1.000
0.662
item26
1.000
0.481
item3
1.000
0.635
item27
1.000
0.571
item4
1.000
0.563
item28
1.000
0.514
item5
1.000
0.404
item29
1.000
0.608
item6
1.000
0.435
item30
1.000
0.535
item7
1.000
0.638
item31
1.000
0.567
item8
1.000
0.627
item32
1.000
0.662
item9
1.000
0.563
item33
1.000
0.532
item10
1.000
0.566
item34
1.000
0.551
item11
1.000
0.562
item35
1.000
0.485
item12
1.000
0.584
item36
1.000
0.559
item13
1.000
0.502
item37
1.000
0.541
item14
1.000
0.671
item38
1.000
0.541
item15
1.000
0.490
item39
1.000
0.414
item16
1.000
0.515
item40
1.000
0.535
item17
1.000
0.536
item41
1.000
0.442
item18
1.000
0.524
item42
1.000
0.619
item19
1.000
0.668
item43
1.000
0.583
item20
1.000
0.689
item44
1.000
0.540
item21
1.000
0.551
item45
1.000
0.559
item22
1.000
0.700
item46
1.000
0.590
item23
1.000
0.692
item47
1.000
0.611
item24
1.000
0.512
RLLQ with standardized estimates (see Appendix B for the
final version of RLLQ).
Inspecting the initial normed chi-square (CMIN/DF), PGFI,
NFL, and RMEAS (Table 9) showed a relatively fit structured
model falling within the acceptable range of 1 and 3. A few
modifications (suggestions) were observed; however, they
were ineffective and made no significant improvement in
the model. The soundness of the factor structure for the Reflective Language Learning Model was examined using CFA
comprising the six factors (Table 9). The CFA measurement
model indicated an acceptable overall model fit: df=1.62,
PGFI=0.73, NFI=0.98, and RMSEA=.054.
DISCUSSION
The researchers constructed and validated a questionnaire
to answer the first research question, which addressed the
18
main components of Iranian EFL learners’ language reflectivity. Running EFA and CFA resulted in the development of
a six-factor model that showed the elements of Iranian EFL
learners’ language reflectivity, as follows:
Cognitive Process: Items Loading on Factor 1 Capture
Cognitive Strategy in Learning a Concept
Cognitive strategies include different mental processes in
language learning, such as inferencing, generalization, deductive learning, monitoring, and memorization (Oxford,
2017; Richards & Schmidt, 2002). Similarly, in the items clustered around this factor, learners are involved in some mental activity, such as conceptualizing learning experiences
by thinking and questioning about learning processes and
procedures used in learning (items 9, 10, 32), thinking about
learning materials to improve learning (items 13, 14, 15, 19,
22, 23, 27), internal self-dialog to retain information (item
31), thinking about learning processes and moving between
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Table 7
Rotated Factor Matrixa in PCA in the 47-Item Questionnaire
Component
47-items
43-items
Item29
Item27
.670
item27
item25
.654
Item25
Item23
.647
Item33
Item31
.567
Item24
Item22
.560
Item21
Item19
.532
Item10
Item9
.507
Item17
Item15
.479
Item11
Item10
.476
Item15
Item13
.474
Item16
Item14
.463
Item34
Item32
.455
Item42
Item39
.663
Item40
Item37
.623
Item43
Item40
.622
Item44
Item41
.586
Item38
Item35
.476
Item28
Item26
.474
Item37
Item34
.459
Item30
Item28
.452
Item39
Item36
.447
Item36
Item33
.435
Item13
Item11
.425
Item41
Item38
.400
1
2
3
4
5
6
7
Item35
Item3
Item3
.704
Item2
Item2
.701
Item1
Item1
.654
Item4
Item4
.611
Item9
Item8
.557
Item5
Item5
.450
Item12
Item7
Item6
.746
Item32
Item30
.706
Item8
Item7
.661
Item31
Item29
.644
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Salman Asshabi, Mojgan Rashtchi, Massood Siyyari
Component
47-items
43-items
Item26
Item24
.558
Item18
Item16
.533
1
2
3
4
5
6
7
Item6
Item20
Item18
.765
Item23
Item21
.726
Item22
Item20
.726
Item19
Item17
.711
Item47
Item43
.716
item 46
item 42
.592
Item14
Item12
.407
Item45
Note:
.542
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalizationa
a
Rotation converged in 8 iterations.
Figure 1
Scree plot for RLLQ in PCA
Table 8
Six Factors of 43-Item RLLQ with the Related Reliability Indices
Factors
No. of Items
Cronbach’s Alpha
Reliability Value
1) Cognitive (Items 9, 10, 13, 14, 15, 19, 22, 23, 25, 27, 31, 32)
12
0.906
2) Evaluative (Items 11, 26, 28, 33, 34, 35, 36, 37, 38, 39, 40, 41)
12
0.896
3) Metacognitive (Items 1, 2, 3, 4, 5, 8)
6
0.815
4) Interactional (Items 6, 7, 16, 24, 29, 30)
6
0.748
5) Reflective (Items 17, 18, 20, 21)
4
0.839
6) Retrospective (Items 12, 42, 43)
3
0.687
Total Questionnaire
43
0.963
20
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Relective Language Learning Model
Figure 2
Reflective Language Learning Model with Standardized Estimates in RLLQ
Table 9
Model Fit Analysis Summary
CMIN/DF (1 ≥, ≤ 3)
PGFI (≥ .60)
NFI (≥ .90)
RMSEA (≤ .06)
1.62
.73
.98
.054
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Salman Asshabi, Mojgan Rashtchi, Massood Siyyari
actions repeatedly to gain new understanding (item 25).
Therefore, it was named “Cognitive Factor.”
Evaluative Activity: Items Loading on Factor 2 Deal with
Evaluation
Richards and Schmidt (2002) consider self-evaluation as
“checking one’s own performance on a language learning
task after it has been completed or checking one’s success
in using a language” (p.475). All items loaded under this factor deal with issues, including evaluating English learning
experiences and making learners self-aware and thoughtful
to understand and deepen their learning (items 11, 26, 28,
36, 37, 38, 40). Likewise, learners’ reflecting on learning activities has improved learning (item 33), reflecting on learning materials during and after using them has facilitated
learning (items 34, 35), thinking over the materials has empowered learners to become an agent of change in learning (item 41), and reflecting on learning experiences has
eliminated the problems in the process of learning (item 39).
Thus, it was labeled “Evaluative Factor.”
Metacognitive Process: Items Loading on Factor 3 Tap into
Metacognitive Strategies
Metacognitive strategies involve planning, monitoring,
thinking, and evaluating a learning task during or after it
occurs (Khellab et al., 2022; Richards & Schmidt, 2002). In the
items loaded around this factor, learners think about learning experiences to do them better for the second time (item
1), reflect on the thinking process to improve learning procedures (item 3), reflect on learning beliefs and values to understand better to enhance their learning (items 4, 5), analyze learning experiences to get a new understanding (item
2), think over learning experiences to evaluate the outcome
of learning (item 8). Therefore, it was named “Metacognitive
Factor.”
Interactional Activity: Items Loading on Factor 4 Deal
with the Interaction Occurring Between a Learner and
Themselves, Context, or any Other Person
Interaction is inevitable in any successful language-learning activity and can be used differently. Therefore, learners
must have opportunities to be engaged in interactional activities in various ways, such as group discussions, collaboration, and participation (Loewen & Sato, 2018). Thus, in
the items loaded under this factor, learners seek help from
classmates and instructors to check their understanding
(items 6 &7), raise questions to understand what has happened in the process of language learning (item 16), reflect
on classmates’ views to improve learning (item 24), interact with instructors, and participate in group discussions to
share meaning (items 29, 30). Therefore, it was labeled “Interactional Factor.”
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Reflective Journal: Items Loading on Factor 5 are
Concerned With Reflective Journaling
A journal is “a notebook or book in which students write
about experiences both in and out of school or record responses and reactions to learning and learning activities”
(Richards & Schmidt, 2002, p. 300). In this study, the effect
of reflective journaling on language learning was significant,
as evidenced by the four items answered by language learners. In the items clustered under this factor, learners assert
that journal writing contributes to their success in language
learning (item 17), stimulates new thoughts and questions
for discussion (item18), gives them more significant insights
into the habit of learning (item 20), and stimulates learners’
reflection (item 21). Therefore, it was called “Reflective Journal Factor.”
Retrospective Activity: items loading on Factor 6 deal with
retrospection
ELT experts have frequently discussed the relationship of
retrospection with reflective learning to reinforce professional development (Pietrzak, 2019; Van der Sluis et al., 2017).
Wedell (2022) asserts, “English language teaching practices in many countries and contexts are subject to frequent
change as innovation is introduced to reform teaching and
learning practices (p. 1)”. In this type of activity, learners
refer to previous activity and scrutinize it to categorize the
concepts, relate them, and find the differences or similarities to develop a new understanding and innovative idea.
Thus, in the items loaded under this factor, learners think
about an experience and relate new information to the previous one to improve their learning (item 12), contrast two
things to find differences they have made in their learning
(item 42), refer to their previous notes in different intervals
to improve their learning (item 43). Therefore, it was labeled
“Retrospective Factor.”
The second research question focused on the validity and
reliability of the newly developed instrument. The results of
EFA and CFA obtained from LISREL urged the researchers
to verify that the 43-item RLLQ was valid and reliable. This
finding implies that future studies can employ the questionnaire and the extracted model to measure learners’ degree
of reflectivity.
As this study is the first attempt to construct and validate
a closed-ended reflective learning scale in the Iranian context, the researchers cannot compare it with similar ones.
However, compared to open-ended scales (Bell et al., 2014;
Feng, 2016), RLLQ seems more beneficial to language learners since it provides a comprehensive range of activities under each factor. Besides being a closed-ended instrument,
RLLQ shares the priority of such tools: it is objective and can
be answered, analyzed, and quantified with fewer problems
than open-ended questionnaires to provide straightforward
results (Dörnyei, 2003).
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Relective Language Learning Model
Moreover, RLLQ shows how to prepare learners to engage
in reflective learning, an advantage that is not addressed
in previous instruments like Colomer et al.’s (2013) Self-reported Reflective Learning Questionnaire. Besides, RLLQ explores various reflective learning strategies proposed in the
literature, such as cognitive (Yesilbursa, 2011), metacognitive (Sellars,2013), and individual and cooperative activities
(Cooke, 2013; Erdogan, 2019).
Most previous studies have employed journal writing to
explore reflective learning (Bruno & Dell’Aversana, 2017;
Hussein, 2018; Ogbuanya & Owodunni, 2015). However,
the limitation of journal writing is that it lacks a “pre- and
post-design” to examine the change in reflective thinking
level (Kember et al., 2000, p. 382). Additionally, the approach
cannot provide information about learners’ strategy use,
which are factors that indicate the advantage of RLLQ.
Likewise, RLLQ has advantages over most of the previous
closed-ended questionnaires (Kember et al., 2000; Min &
Park, 2019; Peltier et al., 2005) since none of the tools prepare students for reflective practice. What is significant in
reflective learning is not determining the relationship of a
variable with another or assessing the impact of a variable
on another but helping learners engage in reflective activities. Thus, the result of the present study in extracting a
model of reflective language learning and giving a complete
picture of the various activities under each factor can be employed by language learners and practitioners in learning
and teaching a concept.
Besides, language teachers and educators can use RLLQ as
a diagnostic measure to examine learners’ engagement in
reflective practice.
CONCLUSION
The researchers developed a reflective language learning
questionnaire to be implemented in the Iranian EFL context.
The study first showed the importance of reflective learning
and discussed the role of different models in shaping such
learning. Then, following several procedures, the researchers developed the RLLQ to cultivate reflective learning practices and make reflective learning measurable. However,
the findings might not be generalizable to contexts other
than Iran. Furthermore, since the context of the study was
Kurdistan, Iran, a nationwide research study can verify its
applicability to other settings inside and outside the country.
The researchers suggest replicating the study with students
majoring in different fields, such as ESP courses. Additionally, studying learners with diverse learning abilities and
considering personality characteristics can be the subject of
further studies to verify the reliability and validity of RLLQ.
Future studies can examine whether incorporating RLLQ
can contribute to personalized learning.
DECLARATION OF COMPETITING
INTEREST
IMPLICATIONS OF THE STUDY
None declared.
Different groups can benefit from the substantial implications of the present study. The RLLQ developed in this study
presents a detailed picture of the six components of reflective language learning and the activities related to each factor. Thus, on a theoretical basis, it can help educators and
SLA researchers understand the dimensions of reflective
learning and teaching in an EFL context. Additionally, the
activities proposed in the RLLQ allow language learners to
use the activities to practice reflective learning and engage
in experiential learning to improve their English language
proficiency. The activities can also guide students’ learning
and help them follow a more organized procedure in language learning. Accordingly, L2 learners can use the RLLQ
to examine the amount of their engagement in reflective
language learning activities to become skillful and self-regulated learners. Teachers can also use RLLQ to explore learners’ reflective strategies while engaged in a learning activity.
Teachers can adjust their instruction to students’ language
levels by pinpointing learners’ weaknesses and strengths.
AUTHORS’ CONTRIBUTION
JLE | Vol. 9 | No. 4 | 2023
Salman Asshabi: Conceptualization; Data curation; Formal
analysis; Funding acquisition; Investigation; Methodology;
Project administration; Resources; Software; Supervision;
Validation; Visualization; Writing – original draft; Writing –
review & editing; Other contribution.
Mojgan Rashtchi: Conceptualization; Data curation; Formal
analysis; Funding acquisition; Investigation; Methodology;
Project administration; Resources; Software; Supervision;
Validation; Visualization; Writing – original draft; Writing –
review & editing; Other contribution.
Massood Siyyari: Conceptualization; Data curation; Formal
analysis; Funding acquisition; Investigation; Methodology;
Project administration; Resources; Software; Supervision;
Validation; Visualization; Writing – original draft; Writing –
review & editing; Other contribution.
23
Salman Asshabi, Mojgan Rashtchi, Massood Siyyari
| Research Papers
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Wedell, M. (2022). Innovation in ELT revisited. ELT Journal, 76(2), 272-275. https://doi.org/10.1093/elt/ccac003
Winkel, A.F., Yingling, S., Jones, A.A., & Nicholson, J. (2017). Reflection as a learning tool in graduate medical education: A systematic review. Journal of Graduate Medical Education, 9(4), 430-439. https://doi.org/10.4300/JGME-D-16-00500.1
Yesilbursa, A. (2011). Reflection at the interface of theory and practice: An analysis of pre-service English language teachers’
written reflections. Australian Journal of Teacher Education, 36(3), 50-62. https://doi.org/10.14221/ajte.2011v36n3.5
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APPENDIX A
Experts’ Interview Questions
1.
How do you define, explain, and perceive reflective learning?
2.
How do you think reflective learning occurs?
3.
What are the different stages of reflective learning?
4.
What strategies, techniques, and procedures do you suggest for reflective learning?
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Salman Asshabi, Mojgan Rashtchi, Massood Siyyari
APPENDIX B
This questionnaire aims to understand what shapes the reflectivity components of language learners in the Iranian context.
There are no wrong or right answers. You are free on whether to write your name or not. The questionnaire focuses on your
personal opinions.
Please mark the number from 1 to 6, which best describes your behavior.
True
6. True
Mostly true
5. Mostly true
More true than false
4. More true than false
More false than true
3. More false than true
Mostly false
2. Mostly false
False
1. False
1.
I deliberately step back and think about my previous English learning experience to do it better
for the second time.
1
2
3
4
5
6
2.
I regularly analyze my English learning experiences to get a new understanding.
1
2
3
4
5
6
3.
I reflect on my thinking processes to improve my English learning procedures.
1
2
3
4
5
6
4.
I reflect on my learning beliefs to improve my English learning behaviors.
1
2
3
4
5
6
5.
I reflect on my life values to see whether they influence my English learning
1
2
3
4
5
6
6.
I reflect on my English learning experiences and seek help from my classmates to check my
understanding.
1
2
3
4
5
6
7.
I reflect on my English learning experiences and seek help from my instructor to check my understanding.
1
2
3
4
5
6
8.
I review my English learning experiences to evaluate the outcome of my learning activities.
1
2
3
4
5
6
9.
I conceptualize my English learning experiences by thinking about the learning processes.
1
2
3
4
5
6
10. I conceptualize my English learning experiences by questioning the learning materials.
1
2
3
4
5
6
12. I review my English learning experiences and relate the new information to what I already knew
to improve my learning.
1
2
3
4
5
6
13. I think about my English learning experiences to meaningfully transfer them to real-life contexts.
1
2
3
4
5
6
14. I reflect on English learning activities to help me draw on my previous experiences to understand
new ideas.
1
2
3
4
5
6
15. I reflect on English learning activities and relate the new ideas to my previous ones to support
my learning.
1
2
3
4
5
6
16. I ask thoughtful questions about the language learning process in the classroom to understand
what has happened.
1
2
3
4
5
6
17. Reflective journaling contributes to my success by providing insights into academic subjects to
increase my responsibility for learning
1
2
3
4
5
6
18. Reflective journaling has stimulated new thoughts and questions in me for discussion.
1
2
3
4
5
6
19. I reflect on the English learning materials to identify my strengths and weaknesses to improve
my learning.
1
2
3
4
5
6
20. Reflective journaling has given me greater insights into my learning habits.
1
2
3
4
5
6
21. I have realized that reflective journaling has stimulated my reflection.
1
2
3
4
5
6
22. I think about my English learning process to shape future learning activities.
1
2
3
4
5
6
Items
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False
Mostly false
More false than true
More true than false
Mostly true
True
Relective Language Learning Model
23. I reflect upon the relations of the English learning materials to improve my learning.
1
2
3
4
5
6
24. I reflect on my classmates’ views concerning learning materials to improve my learning.
1
2
3
4
5
6
25. I think over the language learning process and repeatedly move between action and the learning
process to gain a new understanding.
1
2
3
4
5
6
26. I critically evaluate my English learning practice to deepen my learning.
1
2
3
4
5
6
27. I converse with myself about the English learning materials to rearrange and classify them to
learn better.
1
2
3
4
5
6
28. I reflect on the English learning materials by referring to my written notes to improve my learning.
1
2
3
4
5
6
29. I actively interact in group discussions to analyze the English learning materials and share meaning.
1
2
3
4
5
6
30. I interact with my instructor to analyze the English learning materials and share meaning.
1
2
3
4
5
6
31. I interact with myself and retain information concerning the English learning materials through
internal dialogue.
1
2
3
4
5
6
32. I conceptualize the English learning materials by thinking about the procedures I used in learning.
1
2
3
4
5
6
33. I reflect on my English learning experiences to recollect as much information as possible to understand the materials.
1
2
3
4
5
6
34. I reflect on the different aspects of English learning materials during the learning activities to
facilitate my learning.
1
2
3
4
5
6
35. After the learning activities, I reflect on different aspects of English learning materials to facilitate
my learning.
1
2
3
4
5
6
36. I generally think of finding another way to work on English materials.
1
2
3
4
5
6
37. I usually reflect on the errors in my English learning materials to improve learning.
1
2
3
4
5
6
38. I usually think about how I should attempt to learn English materials better.
1
2
3
4
5
6
39. Reflecting on my past experiences helps me eliminate the problems I encountered while learning
English materials.
1
2
3
4
5
6
40. Reflecting on language learning activities helps me become more thoughtful and less impulsive
in my following learning activities.
1
2
3
4
5
6
41. Reflection has empowered me to become an agent of change in the English learning environment.
1
2
3
4
5
6
42. I reflect on my English learning experience and think about what difference it might make in
improving my learning.
1
2
3
4
5
6
43. Referring to my written notes on the previous sessions at later times improves my learning.
1
2
3
4
5
6
Items
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Please provide the following information by ticking (√) in the box or writing your response in the space.
Gender: Male □ Female □
Learning context: University □ Institute □
Age: Month, day, year
Name of the University ……………………
Years of studying experience …………
Term: …………….
Marital status: Single □ Married □
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Mojgan Rashtchi
