Kamalvand and Khany ﻿Language Testing in Asia
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https://doi.org/10.1186/s40468-024-00307-y

Language Testing in Asia

Open Access

RESEARCH

Development and validation of an English
teachers’ visual literacy scale for smartphone
photography grounded in social semiotic
theoryAyad Kamalvand1   and Reza Khany1*   *Correspondence:r.khany@ilam.ac.ir
1
Department of English
Language and Literature, Ilam
University, Pajoohesh Street Ilam,
Ilam, Iran

Abstract
Smartphones and the literacy to harness the educational affordances of photographs
currently rest on the bedrock of second language (L2) education. Building on social
semiotic theory, this study developed and validated a visual literacy scale for smartphone photography (VLS4SP). Despite the importance of visuals and smartphones,
no valid scale is available in the domain of English language teaching (ELT) to measure L2 teachers’ VL. In developing and validating the new VLS4SP, initially, some items
were generated and tested for validity. Second, the scale was tested through rigorous
psychometric analyses. The results of structural equation modeling (SEM) suggested
the existence of 28 items that represent the established conceptualization of VL
in the literature and the three areas of meaning metafunctions in the social semiotic
theory: representational, interactive, and compositional. Overall, the study tapped
upon two crucial technological and literacy factors in ELT which paves the way for further research and the applications of the scale in ELT.
Keywords: VLS4SP, Visual literacy, Social semiotics theory, Smartphone photography,
ELT

BackgroundL2 instructors and learners while relying on sensory organs — eyes for visual reception, ears for auditory perception, and tongue for verbal expression — which are
instrumental in linguistic interactions use photographs as semiotic resources formeaning making. Besides, they extensively use smartphones either for regular communication or visualization of their daily and educational activities. Today, among
many other uses, instructors and learners leverage their social media accounts as
bloggers or Instagram influencers for teaching and learning purposes. Content thatteachers and learners produce and consume is mainly facilitated by smartphone cameras. The affordances inherent to smartphone camera systems have broadened thescope of semiotic resources accessible to individuals, facilitating the visualization of
their existence through the production of photographic still images, the subsequent© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you
give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified
the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The
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sharing of these visual artifacts within online environments, the acquisition of external feedback, and the opportunity for reflective engagement with these representations at later junctures.
Digital photography as the common practice of visually oriented learners (Brumberger, 2011) plays a canonical role in actualizing VL in ELT. Gnach et al., (2022) assertthat visuals are the privileged mode of communication in ELT and indispensable partsof teaching and learning (Newman & Ogle, 2019). Visuals contribute to L2 pedagogy
by aiding learners to employ a broader language repertoire in their oral narratives (Lee,2024). Additionally, they generate interest and motivation, provide context, and enhancecomprehension when combined with verbal instruction. Research has underscored thevalue of visuals in language teaching and learning, with learners exhibiting more meaningful learning when exposed to a combination of visual and verbal instructional modalities (Mayer, 2002), in contrast to scenarios devoid of such visual aids, which may impair
learners’ comprehension of the subject matter. In light of the aforementioned transformations, VL has emerged as a field of inquiry dedicated to equipping contemporary
students, often referred to as “viewer learners,” with the skills necessary to engage meaningfully with their surroundings (Romero & Bobkina, 2017). Despite the well-establishededucational value of visual resources, research indicates that educational systems havenot fully acknowledged the importance of VL (Avgerinou & Ericson, 1997), and teachers have yet to fully exploit their potential Donaghy and Xerri (2017). Specifically, L2
instructors have not adequately harnessed the power of images to inspire discussion,
creativity, and new ideas. Moreover, disposition in ELT still reckon written and spoken
modes sufficient to communicate and teach; however, this dogma has been questioned(Katsampoxaki-Hodgetts, 2024), and it has been emphasized that “it is time to unsettle this commonsense notion” (Kress, 2000). Although VL is the most essential literacy
for the twenty-first century (Matusiak, 2020) and for ELT practice, little is written about
how to evaluate L2 instructors’ VL smartphone photography. With a visual social semiotic frame of reference and established principles of scale development, the present
study attempts to develop and validate a scale for evaluating L2 teachers’ VL for smartphone photography. The development of this scale facilitates the advancement of ELT
pedagogy by enabling the diagnosis of instructors’ VL and guiding their efforts to takeinformed steps toward supporting learners in acquiring knowledge in novel and more
efficacious ways through engagement with photographic media (Ng, 2006). Once measured, such a tool may help understand how L2 instructors interact with visual content
and the multimodality of teaching and learning materials.
Smartphone photography adds another meaning-making resource to the L2 instructors’ communicative repertoire (Hall, 2018). The affordance of smartphones is particularly significant in the context of L2 acquisition, which has evolved in tandem with rapid
technological advancements. Language learning entails mastery of semantics and syntax but mastery of other semiotic resources (Hall, 2018; Kárpáti & Schönau, 2022). To
be a successful instructor in this digitally/visually mediated context requires literacy
which enables educators to interact effectively with visual resources. Recognizing this,
UNESCO (2023) and the European Network for Visual Literacy (ENViL) have emphasized the role of VL in education. Common European Framework of References for Visual Literacy (CEFR-VL) has been one of ENViL’s initiatives to break down VL into its

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constitutes (Schönau et al., 2020). Through these efforts, ENViL underscores the importance of visual literacy in our contemporary society.
A key argument developed in this study is the necessity for VL to work with smartphone photography for L2 instructors. VL not only augments the instructors’ understanding and working with photographs but also changes the understanding of theactivity of L2 teaching (Hall, 2018). Given that teaching is a multimodal endeavor (Hall,
2018; Lim et al., 2022), teaching L2 learners within a pedagogical context marked bywidespread smartphone photography necessitates a focus on VL and a reevaluation of
L2 instructors’ instructional approaches (Miller, 2014; Thomson & Uddin, 2023). To
address the expanded notion of literacy, this study developed and validated a VLS4SP
grounded in social semiotic theory (Kress & Van Leeuwen, 2021). The impetus for thecurrent study arose from the long-standing need within ELT to establish robust, theoretically grounded, and empirically validated instruments for the multimodal assessmentof instructional practices (Lim & Kessler, 2024). The significance of this research lies
in its capacity to enhance the field’s evaluation methods, enabling assessors to develop
more sophisticated insights into instructors’ diverse pedagogical practices and, subsequently, to offer more tailored and effective feedback that fosters professional growthand development.
Theoretical grounding: social semiotics

According to social semiotics, visual resources function as semiotic signs that convey a
range of meanings. The theory sees the relationship between the signifier and the signified motivated. Sign makers intentionally select available resources to construct theirmessages, rather than being constrained by any particular system of communication.
The defining characteristic that distinguishes social semiotic theory from other forms
of semiotics is its emphasis on sign-making rather than sign use (Kress, 2009). This fieldof study believes that semiotic resources serve as choice options within systems to makemeaning (Dressen-Hammouda & Wigham, 2022; Kress & Van Leeuwen, 2021). Signs arecontinually newly made and arise from the interests of the sign-makers (Kress, 2009; Van
Leeuwen, 2005). From a methodological standpoint, social semiotics provides a set ofanalytical tools to deconstruct visual significations according to three types of metafunctions: representational, interactive, and compositional (Kress & Van Leeuwen, 2021).
The theory can significantly contribute to VL by equipping L2 instructors with tripartite-metafunctional systems of meaning to effectuate the five generic sub-competencies in the sub-domain of “producing” which are the competency to present one’s own
images and the competency to evaluate one’s own images and image-making processes,
as well as some principles for reading photographs (Barrett, 2010) such as “all images
require interpretation,” “photographs carry more credibility and require interpretation,”and “feelings are guides to interpretations.” Social semiotics recognizes that all communication, including visual communication, involves interpretation. Photographs are
not self-explanatory; they require active the ability the deconstruct them into their elements. The theory views photographs as tools used by sign-makers to serve social needs.
It extends L2 instructors’ act of photography beyond mere observation, equipping themto discern credibility, intent, and underlying messages in photographs. Social semiotics recognizes photographs as a key mode of communication. It encourages sign-makers

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to express their interpretations through language, enhancing L2 instructors’ interactions
with visuals. In social semiotics, realizations of meaning occur through three systems ofrepresentational, interactive, and compositional metafunctions. Each of these overarching metafunctions is composed of constituent subsystems, which serve as the semiotic
resources upon which sign-makers draw to visualize and communicate their intended
meanings with specific effects.
Representational metafunction refers to a system of visual choices that sign-makers
deploy to depict participants (depicted people, places, and things), process (the represented actions of the visualized participants), and circumstances (the place wherethese actions occur). It focuses on what: what represented participants are represented
through different visual resources (Höglund, 2022). Representational metafunction isrealized through narrative and conceptual structures. Narrative structures depict participants in action-reaction processes. The main element of representational meaning
is vectors which connect the represented participants. On the other hand, the conceptual structure lacks vectors; thus, no dynamicity is seen in a visual layout. Conceptual
representations represent participants through classification, analytical, and symbolic
structures.
Interactive meanings concern the interpersonal relations among represented participants and the viewers and how the relations are constructed (Höglund, 2022). It isrealized through systems of contact, social distance, power relations, involvement, andattitude. Contact is constructed by the direct and indirect gazes; social distance by shot
distance (close, medium, and long shots); power relation by vertical camera angle (highor low angles); involvement by horizontal camera angle (frontal or oblique angles); andattitude by the choice of perspective. Another aspect of interactive meaning is the validity or credibility of visual layouts. Credibility can be judged by validity markers, including color, details, contextualization, illumination, brightness, and depth.
The compositional meaning of an image integrates the representational and interactive meanings of an image to construct a meaningful whole. Composition exploits threeinterrelated systems to relate representational and interactive meanings: (a) information
value, (b) framing, and (c) salience. Information value concerns the place of participantsin a visual configuration. The placement of resources on the left and right creates thesense of new and given information and on top and at the bottom creates the information value of ideal and real. Framing isolates or connects represented participants
through using white space between applying color contrast. Salience is a measure of thedegree to which an element draws attention to itself. It is realized through size, sharpness of focus, tonal and color contrast, perspective, and placement in the visual field.
Defining VL

VL is an essential component of multiliteracy in the twenty-first century (The New
London Group, 2000). VL is often described as an overarching term that encompasses
the knowledge and skills needed to effectively use and understand visual information (Avgerinou & Pettersson, 2011; Brumberger, 2019; Elkins, 2009). This knowledge
includes both an interpretative and a productive component. Although the ability toanalyze and interpret visuals is critical, it is not by itself sufficient for full VL; it mustbe accompanied by some ability to create visual material (Brumberger, 2011). For

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Felten (2008), living in a visual world, however, does not mean instructors and students naturally possess sophisticated VL skills. Rather, it involves the ability to understand, produce, and use culturally significant images, objects, and visible actions. For
some, VL is defined as the ability to comprehend, generate, and utilize images to communicate, think, and learn through visual means (Stokes, 2002). The construct forother researchers is coupled with heightened conscious awareness, that is VL is theability to analyze visuals in terms of their historical context, how they are produced,
their impact on society, and the moral responsibilities of their producers (Curtis,
1987; Messaris & Moriarty, 2005). Contemporary scholars view VL as a set of abilities that are largely acquired, namely, the ability to understand (read) and use (write)
images, as well as the ability to reason and learn in terms of images (Avgerinou, 2007).
Yenawine (1997) associates meaning finding with VL. For him, VL involves a set ofskills ranging from identification of the image to more sophisticated interpretationthat acts upon contextual, metaphoric, and philosophical levels.
Within the educational context, Ausburn and Ausburn (1978) state that VL can be
defined as a body of enabling skills that help individuals perceive and use visuals forpurposeful interpersonal communications. Further, they point out that visuals are alanguage with its syntax, grammar, and vocabulary by which a person can interpretand compose visual messages. Likewise, Gates (2004) speaks of VL as a language witha syntax to create educationally functioning pictures, and their meanings need to benegotiated by learners and instructors. Goin (2001) asserts that learners require theunderstanding that visual language employs syntactic rules. Moline (2023) argues
that VL is more than just symbol recognition. It is the skill to interpret and sharethe meanings of images, leading to the development of “intelligent vision” (p. 7). The
Association of College and Research Libraries (ACRL) has defined VL as “a set of abilities that enables an individual to effectively find, interpret, evaluate, use, and create
images and visual media” (Hattwig et al., 2013).
Social semiotics suggests that images are constructed in a way comparable to language and can also be deconstructed into the choices sign-makers make to configure meaning. Hence, the ability to read and write visuals is a crucial prerequisite
for social participation in an era loaded with visuals (Hermans & Schönau, 2022).
VL concerns the ability of a sign-maker to manipulate signs to create new meanings(Bopry, 1994). This ability lets the sign-maker be open to novel discoveries (Bopry,1994). Kress and Van Leeuwen (2021) classify VL into old and new (p. 21) where theold VL refers to the era when visuals played a subservient role in communication andthe new is the modern era in which visuals have gained an important role. Generally,in Kress and Van Leeuwen’s grammar of visuals, the ability to produce photographs
would fall under the category of design, and the ability to interpret photos would fallunder the category of interpretation. Design includes the choices made in creating aphotograph, such as representational, interactive, and compositional meanings. Interpretation refers to the understanding and analysis of the visual, including the decoding of its meaning and the context in which it was created.
Overall, VL is an important skill for L2 educators. This skill requires the educators’ proficiency to create, interpret, and evaluate visuals to participate fully in a bain

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d’images (Avgerinou, 2009), or image bath, and it is increasingly recognized as a key
component of education.
Research questions◦ RQ 1: What are the key dimensions that constitute the construct of VLS4SP?
◦ RQ 2: What are the psychometric properties of the scale developed to measure
English teachers’ VL for smartphone photography?

Methodology
Study design

The study adopted the established psychometric principles suggested by Hinkin (2005)
and DeVellis and Thorpe (2021) to develop the scale. The process involved scale development and scale validation. The scale development phase included the defining VL, a pilot
study, and the content validity of the developed. The scale validation phase included
exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and model fit
using multiple fit indices, including χ 2 test, Tucker-Lewis index (TLI), Bentler’s Comparative Fit Index (CFI), Hoelter’s “critical N,” root-mean-square error of approximation(RMSEA), and goodness-of-fit index (GFI).
Phase 1

Initially, based on the conceptualization of the VL informed by social semiotic theory,
an initial pool of items was generated. Since the literature on VL has already provided
a theoretical definition of VL and since social semiotics has delineated the components of VL, the study adopted a deductive approach to generate the items (Hinkin,2005). Hence, to ensure that the items on the scale were representative of the construct and grounded in the theory, the relevant literature was extensively reviewed,
and then a theoretical definition of the construct was formulated. Secondly, item
wording was conducted. This step covered issues related to the simplicity and consistency of the items (Hinkin, 2005). The scale also was checked for ambiguity anddouble-barreled items that could lead to the respondents’ confusion. Thirdly, thenumber of items was determined. This step was guided by the principle of retaining
a pool of items that exceeds the target length of the final scale by approximately 50%(DeVellis & Thorpe, 2021) to achieve a higher internal. For item scaling, the participants were asked to answer the items using a 5-point Likert-style rating system. Typically, 5 to 7 points are used to increase the reliability of the Likert scales, according
to common practices (DeVellis & Thorpe, 2021; Hinkin, 2005). Hence, the items were
evaluated on 5-point Likert-type scales ranging from strongly disagree to strongly
agree. After the participants have provided their responses using the 5-point Likertstyle rating system, each response is assigned a score from 1 (strongly disagree) to 5
(strongly agree). The total score for each participant is then calculated by summing
the scores of all the items. In the case of missing responses, the total score is calculated based on the items that were answered. This scoring protocol ensures that the
responses are interpreted consistently across all participants, enhancing the reliabilityof the scale. The concluding stage of the “Phase 1” entailed the assessment of face andPage 6 of 22

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content validity to ascertain the alignment of the items with its purported measurement objectives. At this stage, the questionnaire was administered to the first groupof participants (n = 30). The participants were asked to review the items and provide
feedback on whether they understood the statements questions and if any statements
were unclear. Then, a panelist of experts in social semiotics and applied linguistics
checked the items. The experts were chosen based on their extensive knowledge andexperience in the fields of social semiotics and applied linguistics. This included thefounder of the theory used in this study, who brought invaluable insights and depth tothe process. This stage aimed to solicit feedback as well as to check for domain definition, domain representation, and domain relevance (Sireci, 1998).

Phase 2In this step, the study utilized SEM using the software package AMOS to assess thereliability and validity of the VLS4SP. First, the internal consistency reliability of thescale by calculating Cronbach’s alpha coefficient was done. Then, EFA was performed
initially to explore the underlying factor structure of the scale. After identifying thefactor structure through EFA, a CFA was performed to confirm the factor structureof the scale. Model fit was evaluated using multiple fit indices, including χ 2 test, TLI,
Bentler’s CFI, Hoelter’s “critical N,” RMSEA, and GFI.

Results
Demographic features
Pilot phase

The total number of Iranian English instructors is kept confidential by Iranian general
education and not publicly available. However, efforts were made to ensure that the sample is diverse and representative of various regions and teaching contexts within Iran. To
be eligible for this study, participants needed to have 5 years of experience teaching English. The pilot testing sample for this study consisted of 30 Iranian English instructors.
The educational qualifications of the participants were as follows: 4 participants had
PhD degrees, 15 participants had MA degrees, and 11 participants had BA degrees. The
gender breakdown of the pilot sample was 45% male (13 participants) and 55% female(17 participants). The age range of the pilot phase participants was 25 to 55 years old. All
participants in the pilot phase had a minimum of 5 years of English teaching experience.
The pilot phase participants were recruited from various regions within Iran to ensure adiverse and representative sample. The gender ratio was 45% male and 55% female. The
pilot testing evaluated the scale’s clarity, specificity of directions, and preliminary psychometric properties. Further, the test–retest reliability of the scale was assessed using
the pilot group of participants. The same test was administered to these participants at
two different points in time. The correlation between the two sets of scores was calculated to assess the reliability of the test over time. The results showed a high correlation
between the scores from the two administrations (r = 0.85, p < 0.01), indicating strong
test–retest reliability. This suggests that the scale provides consistent results over time
when the construct being measured remains stable.

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Main phase

The main study’s sample consisted of 274 English instructors with 30 holding PhDs,
106 holding BAs, and 138 holding MAs. The gender ratio was 42.7% male and 57.3%
female. The main phase participants were individuals between the ages of 25 and 55.
The main phase sample was also drawn from different regions across Iran to maintaina diverse representation. The scale’s format was organized into two discrete parts: ademographic data section and a 5-point Likert scale section for assessing participant
responses. Participants were informed of the confidentiality and research purposes of
their responses. The scale was distributed through two methods: in-person or electronically using Google Forms.
Reliability assessment

A reliability assessment was conducted to evaluate the internal consistency of thescale. Cronbach’s alpha coefficient was computed for the remaining 65 questions,which measures the extent to which all items in the questionnaire measure the same
construct or dimension. The obtained coefficient of 0.974 indicated good internal reliability and consistency of the items, surpassing the recommended threshold of 0.65
(DeVellis & Thorpe, 2021).
Content validity assessment

Initially, 71 items were generated according to reviewing the literature. The items
then were presented to the expert panel of the study to assess the content and establish its validity. After gathering feedback and rating data from the experts, the content
validity index for each item was calculated. Upon analyzing the expert ratings, it was
found that six items were deemed unsuitable for the study and were eliminated fromthe initial pool. Furthermore, based on the experts’ recommendations, some of theitems were modified and rephrased to enhance their clarity and specificity.
EFA

Prior to performing EFA, the Kaiser–Meyer–Olkin (KMO) for measuring the adequacy of the sampling and Bartlett’s test of sphericity for factorability of the correlation matrix were assessed. The KMO measure was found to be 0.89 which indicatesthe sampling was adequate (Shrestha, 2021). Bartlett’s test of sphericity was statistically significant (χ 2 = 18339.799, df = 2485, p < 0.000) indicating highly acceptablefactorability of the data and correlation matrix (Shrestha, 2021).
The study used both the scree plot and the Kaiser-Guttman method to determine
the optimal number of factors to retain. The scree plot (Fig. 1) shows a distinct breakafter the third factor, indicating the retention of three factors. Then, the Kaiser-Guttman criterion, which suggested retaining factors with eigenvalues greater than 2.5,
was used as the corresponding criterion value. Based on this criterion, the first threefactors had eigenvalues greater than 2.5, while the fourth factor had an eigenvalue of
2.189, which is less than 2.5. Therefore, the first three factors were retained. As shownin Table 1, the three factors accounted for a total of 48.48% of the variance in the data.
Factor 1 explained 38.54% of the variance, factor 2 explained 5.68% of the variance,

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Fig. 1 Scree plot

Table 1 Total variance explained
Component

Initialeigenvalues

Extraction sums ofsquared loadings

Rotation sums ofsquared loadings% of variance Cumulative %explained

1

25.04

25.04

13.00

38.53

38.53

2

3.69

3.69

11.13

5.67

44.21

3

2.77

2.77

7.37

4.26

48.48

and factor 3 explained 4.27% of the variance. The study also conducted a rotation of
the factor structure, which resulted in the extraction of the same three factors. The
rotated solution accounted for a total of 48.48% of the variance in the data. Factor
1 explained 20.01% of the variance, factor 2 explained 17.13% of the variance, andfactor 3 explained 11.34% of the variance. After factor rotation, items loaded on thethree factors with loadings less than 0.5 were deleted.
A matrix of factor loadings (Table 2) was generated from the initial factor analysis
before rotation. The matrix shows the factor loadings of the items in the questionnaire
across the three components extracted. The items with higher factor loadings were considered to be more strongly related to the underlying factor.
Next, to improve the interpretability of the factor structure after the initial factor
extraction, factor analysis was performed using principal component analysis withvarimax rotation and Kaiser normalization. The rotation was conducted with eight
iterations until convergence was achieved. The rotated component matrix was generated to improve the interpretability of the factor structure. Table 3 shows the rotatedcomponent matrix, which displays the factor loadings for each variable on each component after rotation. Variables with loadings greater than 0.5 were considered tohave high associations with a particular component. The first component had highloadings from items 12, 14, 19, 22, 26, 27, 32, 42, 51, and 63, which were interpreted
as representing events and concepts. The second component had high loadings from

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Table 2 Component matrix
Item

Component
1

2

3

2

0.66

0.16

0.07

3

0.48

0.24

0.26

4

0.34

0.49

0.18

5

0.45

0.40

0.09

6

0.47

0.44
− 0.29− 0.18− 0.01− 0.06

7

0.54

8

0.47

9

0.32

0.58

10

0.36

0.34

11

0.48

0.34

12

0.74

13

0.68

− 0.18

14

0.70

15

0.62

16

0.62

17

0.74

0.14

18

0.71

19

0.62

− 0.03− 0.25

20

0.69

0.22

21

0.62

− 0.04

22

0.60

23

0.68

24

0.58

0.16

25

0.65

0.26

0.02

26

0.51

0.49

27

0.72

− 0.115
0.02

0.00

28

0.67

0.07

32

0.64

− 0.0934

0.66− 0.23− 0.30

35

0.64

36

0.64

37

0.71

38

0.62

39

0.46

40

0.14

− 0.01− 0.270.20

0.12− 0.320.27− 0.38
0.25

0.31

0.25

0.05

− 0.09− 0.14− 0.11− 0.020.05− 0.08− 0.09

0.039

0.34

0.12

0.38
− 0.030.24

0.31− 0.03− 0.28− 0.05− 0.26− 0.17

0.62

0.00

41

0.65

0.00

− 0.27

42

0.67

43

0.73

− 0.203

44

0.67

45

0.69

46

0.71

49

0.63

47

0.69

48

0.64

50

0.71

51

0.65

52

0.50

54

0.16

− 0.010.42− 0.22− 0.140.22− 0.16− 0.240.08− 0.340.11

0.23− 0.18− 0.38− 0.270.06− 0.33− 0.09− 0.07− 0.05− 0.13− 0.33− 0.15− 0.00− 0.10
0.62

0.19

0.02

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Table 2 (continued)
Item

Component
1

2

55

0.68

56

0.54

− 0.06

57

0.68

0.08

58

0.65

0.02

59

0.58

− 0.13

60

0.64

61

0.73

62

3

0.51

0.13
− 0.07− 0.280.21− 0.24− 0.25− 0.24

0.59

0.11

63

0.61

64

0.50

− 0.04− 0.15

65

0.64

66

0.64

67

0.58

68

0.68

69

0.62

70
71

0.10

− 0.11− 0.150.00

0.19− 0.08
0.17

0.11

0.20

− 0.22− 0.15− 0.20− 0.02

0.64

0.26

0.59

− 0.29− 0.050.04

0.19− 0.04

items 13, 18, 34, 40, 44, 46, 49, 50, 57, 62, and 67, which were interpreted as representing relation with the viewer. The third component had moderate loadings fromitems 15, 17, 20, 24, 37, 39, and 56 representing syntax of space. The rotated component matrix was used to identify and interpret the underlying constructs or dimensions represented by the factors. The 28 items that construct the VLS4SP are given in
Appendix Table 11.
With the data in Table 3, the name of each factor was assigned (Table 4).
A factor correlation test was conducted to assess the relationships between the factors identified in the factor analysis. Table 5 displays the correlation matrix for thethree factors. The results indicate that factor 1 was significantly positively correlatedwith factor 2 (r = 0.733, p < 0.01) and factor 3 (r = 0.757, p < 0.01). Factor 2 was alsosignificantly positively correlated with factor 3 (r = 0.727, p < 0.01). These findings
suggest that there are meaningful relationships between the factors and support ourinterpretation of the underlying constructs represented by the factors.
Indices of the first factor Table 6 shows the results of a one-sample t-test conducted on
Factor 1. The test was conducted to determine whether the mean scores of the items in
Factor 1 significantly differ from the hypothetical value of 3, responses indicating positive strength of agreement. The results show that the mean scores for all items in Factor
1 were significantly higher than the hypothetical value of 3, with p-values less than 0.001
and mean differences ranging from 0.547 to 0.785. These findings suggest that respondents on average had higher scores on Factor 1 compared to the hypothetical value. The
confidence intervals for the mean differences ranged from 0.43 to 0.89, indicating thatthe differences are likely to be statistically significant.

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Table 3 Rotated component matrix
Item

Component
1

2

3

12

0.69

14

0.66

19

0.66

22

0.67

26

0.71

27

0.43

32

0.65

42

0.62

51

0.43

63

0.53

15

0.49

17

0.43

20

0.49

24

0.35

37

0.26

39

0.62

56

0.69

13

0.69

18

0.64

34

0.73

40

0.58

44

0.74

46

0.50

49

0.72

50

0.58

57

0.59

62

0.43

68

0.56

Table 4 Name of each factor and the related items
Name of the factor

FactorNumber of the
items

Items

Relation with the viewer

1

1113, 18, 34, 40, 44, 46, 49, 50, 57, 62, 67

Events and concepts

2

10

12, 14, 19, 22, 26, 27, 32, 42, 51, 63

Syntax of space

3

7

15, 17, 20, 24, 37, 39, 56

Table 5 Factor correlation test
Factor 1
Factor 1

Pearson correlation

Factor 2

Factor 3

1

Sig. (2-tailed)
Factor 2
Factor 3aPearson correlation

0.733aSig. (2-tailed)

0.000

Pearson correlation

0.757a0.727aSig. (2-tailed)

0.000

0.000

Correlation is significant at the 0.01 level (2-tailed)11Kamalvand and Khany ﻿Language Testing in Asia

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Table 6 The descriptive statistics for factor 1
Item

Mean

Test value = 3
T

df

Sig. (2-tailed)

Mean difference

95% confidence
interval of thedifference
Lower

Upper

13

3.63

11.199

273

0.000

0.631

0.52

0.74

18

3.78

17.277

273

0.000

0.785

0.70

0.87

34

3.56

10.622

273

0.000

0.562

0.46

0.67

40

3.55

9.397

273

0.000

0.547

0.43

0.66

44

3.65

13.029

273

0.000

0.653

0.55

0.75

46

3.78

15.089

273

0.000

0.785

0.68

0.89

49

3.64

12.566

273

0.000

0.639

0.54

0.74

50

3.61

10.559

273

0.000

0.609

0.50

0.72

57

3.65

12.795

273

0.000

0.646

0.55

0.75

62

3.66

12.347

273

0.000

0.657

0.55

0.76

67

3.76

14.170

273

0.000

0.755

0.65

0.86

Mean difference

95% confidence
interval of thedifference

Table 7 The descriptive statistics for factor 2
Item

Mean

Test value = 3
T

df

Sig. (2-tailed)

Lower

Upper

12

3.70

12.283

273

0.000

0.701

0.59

0.81

14

3.81

14.935

273

0.000

0.810

0.70

0.92

19

3.86

16.545

273

.0000

0.861

0.76

0.96

22

3.67

11.444

273

0.000

0.668

0.55

0.78

26

3.69

11.171

273

0.000

0.693

0.57

0.82

27

3.73

14.407

273

0.000

0.730

0.63

0.83

32

3.76

15.819

273

0.000

0.755

0.66

0.85

42

3.83

15.751

273

0.000

0.828

0.72

0.93

51

3.75

14.572

273

0.000

0.752

0.65

0.85

63

3.78

14.266

273

0.000

0.785

0.68

0.89

63

3.78

14.266

273

0.000

0.785

0.68

0.89

Indices of the second factor Table 7 presents the results of a one-sample t-test for Factor 2. The mean score for each item is shown, along with the test value (set at 3), thet-value, degrees of freedom (df), and the significance level. The mean difference and 95%
confidence interval for the difference are also provided. All items had significantly higher
mean scores than the test value of 3, with mean differences ranging from 0.668 to 0.861.
These results suggest that participants rated Factor 2 items positively, with mean scores
ranging from 3.67 to 3.86.

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Table 8 The descriptive statistics for factor 3
Item

Mean

Test value = 3
T

df

Sig. (2-tailed)

Mean difference

95% confidence
interval of thedifference
Lower

Upper

15

3.80

16.377

273

0.000

0.796

0.70

0.89

17

3.64

13.349

273

0.000

0.639

0.54

0.73

20

3.71

14.263

273

0.000

0.712

0.61

0.81

24

3.85

16.093

273

0.000

0.850

0.75

0.95

37

3.65

11.936

273

0.000

0.653

0.55

0.76

39

4.13

26.605

273

0.000

1.131

1.05

1.22

56

3.76

14.966

273

0.000

0.755

0.66

0.85

Indices of the third factor Table 8 presents the results of the one sample t-test for Factor
3. The mean, t-value, df, significance level, mean difference, and 95% confidence intervalof the difference are reported for each item. The test value was set at 3. All items showeda significant mean difference from the test value of 3 (p < 0.05). The mean differences
ranged from 0.639 to 1.131. The 95% confidence intervals of the difference ranged from0.54 to 1.22.
CFA

To validate the factor structure identified through EFA, a CFA was conducted using AMOS
The structural model posited three latent constructs as factors and items as observed variables depicted in Fig. 2. The fit of the model was evaluated using a suite of indices: the χ^2test, NFI, CFI, Hoelter’s critical N, RMSEA, and GFI. The χ^2 test yielded a value of 0.314,
indicating a good fit at the significance level of α = 0.05. This value suggests that the model’s predictions are consistent with the observed data. The NFI and CFI values were bothabove 0.90, reflecting a satisfactory fit of the model. Hoelter’s critical N was calculated to
be 200, confirming that the sample size is adequate for the model. The RMSEA was 0.049,
which is within the acceptable range, indicating a good fit. Lastly, the GFI stood at 0.950,
demonstrating the model’s ability to reproduce the observed covariance matrix effectively.
The model demonstrated a good fit to the data, as indicated by the fit indices meeting or
exceeding their respective acceptance thresholds (Table 9). This supports the factor structure identified through EFA, suggesting that the model is an appropriate representation of
the data.
In general, it was found that the path (Table 10) from VL to relation with the viewer at the
5% level was positive and significant, and the path from VL to events and concepts at the
5% level was also positive and significant, and the path from VL to the syntax of space at the
5% level was positive and significant. Additionally, the factors of relation with the viewer,
events and concepts, and syntax of space had a significant and mutual effect on each other.
Overall, the proposed model, which is the result of factor analysis, was confirmed.

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Page 15 of 22

Fig. 2 Structural model of VLS4SP

Table 9 Evaluation of model fit
CriteriaLevelχ 2 test

0.314

NFI

0.930

Interpretation
Excellent fit at a significance level of α = 0.001

Excellent fit (criteria greater than 0.90)

CFI

0.910

Excellent fit (criteria greater than 0.90)

Hoelter’s “critical N”

0.840

Excellent fit (criteria greater than 0.70)

RMSEA

0.049

Excellent fit (criteria less than or equal to 0.05)

GFI

0.950

Excellent fit (criteria greater than 0.90)

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Table 10 Indices for the pathPath
VL → relation with the viewer

VL → visualizing events and concepts

VL → syntax of space

Relation with the viewer ↔ visualizing events and concepts

Syntax of space ↔ visualizing events and concepts

Syntax of space ↔ relation with the viewer

Estimate

p-value

Result0.77***

Significant

0.70

***

Significant

0.63

***

Significant

0.73

***

Significant

0.72

***

Significant

0.69

***

Significant***indicates a p-value less than 0.05, signifying a statistically significant result for the path estimates

Discussion
The present study attempted to develop and validate an English instructors’ VL scale forsmartphone photography by implying the tenets of social semiotic theory. The results ofthe study demonstrate that the developed scale has satisfactory validity and reliability,
indicating that it is an effective tool for assessing English instructors’ VLS4SP. By drawing on this theory, the study was able to develop a scale that reflects the key elements ofthe production and interpretation of photographs and provides a standardized framework for assessing instructors’ VLS4SP. Consistent with the levels of meanings in thesocial semiotic theory, the results of the EFA provided support for the proposed threefactor model, which was further tested through a CFA using AMOS. The results of the
CFA demonstrated an excellent fit of the proposed model to the data, as evidenced by
the high values obtained for each of the fit indices. The scale comprises three factors: (a)relation with the viewer, (b) visualizing events and concepts, and (c) syntax of space with
28 items (Appendix Table 11). The first factor, in relation with the viewer, corresponds
to interactive metafunction. It entails the knowledge of engaging viewers with the represented participants through the motivated use of the camera lenses to enact systems
of contact, social distance, and attitude (Kress & Van Leeuwen, 2021). This factor servesto assess educators’ familiarity with encoding demand or offer images. Further, it aids indeducing from taken photographs the educators’ understanding of systems of the size ofthe frame to visualize intimacy, individuality, and personal and impersonal relationships(Jewitt & Oyama, 2001). Furthermore, the discernment of subjectivity or objectivity, as
reflected in participants’ detachment, power, equality, action, and knowledge orientations through camera angle, constitutes additional aspects assessable by this element.
The second factor, events and concepts, aligns with the representational meaning insocial semiotic theory and indicates the knowledge to use smartphone cameras to visually construct narrative and conceptual representations. It evaluates the sign-makers’
ability to capture the essence of events, participants, and environment in the image. Thisfactor taps the educators’ awareness to illustrate the subject or object doing/receiving
activities in a particular setting. It also serves to evaluate instructors’ ability to visualize the participant as a “more or less stable and timeless essence” within the systems ofclassification, analytic, or symbolic structures (Kress & Van Leeuwen, 2021). The third

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factor, the syntax of space which correlates with compositional meaning, refers to theknowledge of compositional principles or placing the represented participants in different spaces of a photograph. This factor facilitates evaluating educators’ cognizance of
information value, salience, and framing. The positioning of participants within the visual frame (information value), the extent to which they dominate the composition (salience), and the degree of their integration with additional components within the visual
space (framing) collectively constitute the compositional metafunction.
Developments in technology suggest that the new VL represents a departure fromthe old VL and has implications for how instructors understand visual communication(Kress & Van Leeuwen, 2021). In the new VL, visuals are no longer the unstructured replication of reality, secondary to the construction of meaning (Kress, 2009). VL calls foreducators who are aware of the affordances of visuals and are able to take and interpret
photographs carrying intended meanings. In education, this requires a shift in teaching practices and pedagogy, as educators need to help students navigate the complex
and evolving landscape of visual communication (Winstanley et al., 2024). In this way,
instructors can help students develop critical thinking and analytical skills, as well as anappreciation for the power and potential of visual language. Today, English in the digitally mediated world is learned and taught through a multiplicity of modes that extend
beyond modes of speech and writing (Tudini & Liddicoat, 2024). Language instructors
work in a time when in 1 h more photographs are produced than were produced in theentire nineteenth century (Cubitt & Cartwright, 2018). Further, smartphones have diversified L2 learning materials and promoted learners to the producers of learning content (Huynh et al., 2022). Consequently, a tectonic shift (Kress, 1999) has happened in
educational content from the medium of book to the medium of screen (Kress, 2003),
demanding instructors to recognize VL as essential literacy and education to revise pedagogy (Domínguez Romero & Bobkina, 2021).
Integrating mobile devices into education has sparked heated debates among researchers. While some argue that mobile devices can enhance language skills (Xueting Ye &Shi, 2023; Yeşilel, 2022), others contend that their use can disturb the “fragile ecology”(Merchant, 2012) of classrooms. Similarly, despite the surfeit of visuals, integration of
VL into ELT can be challenging. However, incorporating VLS4SP into language teachingpresents both challenges and opportunities for educators. VL has been largely ignored in
ELT (Donaghy & Xerri, 2017). However, the presented VLS4SP offers a promising tool
for assessing instructors’ abilities and raising their conscience about using photographs
in ELT. The scale can aid instructors in mindfully integrating photographs into L2 education. Moreover, it helps instructors to have the needed theoretically driven vision (Ng,2006) by which they prioritize the use of theoretically captured photographs that facilitate and intensify language learning (Wasilewska, 2017). Social semiotics theory canenrich instructors’ vision for using the lenses of smartphones for pedagogical purposes.
It promotes instructors’ understanding that photographs are not passive reflectionsof reality but, rather, constructed artifacts that reflect the cultural and social practicesof sign-makers. As such, instructors can use smartphone photography to encourage

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students to critically examine and interpret visual images in order to understand thesocial and cultural meanings they convey.
The three factors of the VLS4SP can serve as a framework for guiding instructors inselecting and creating photographs that align with their instructional objectives and thelearners’ cultural backgrounds. The interplay between language learning and culture has
been widely addressed in second-language acquisition (SLA). Culture is a reservoir ofsemiotic resources of a particular group of people. Individuals use the resources according to their own interests to settle on the intended meaning (Kress & Van Leeuwen,
2021). The three factors of the VLS4SP provide ELT with a systematic approach to turning photographs into semiotic modes (Danielsson & Selander, 2021). The scale raises
instructors’ awareness of their own culturally bound resources which in turn mightlead to cultivating cross-cultural competence in L2 learners (Stefanenko & Kupavskaya,2012). This, in turn, can lead to a more inclusive and culturally responsive approach tolanguage teaching and learning. L2 instructors’ and learners’ culture has marginal status
in SLA research. The VLS4SP can set the stage for future inquiries into the impact of
semiotic resources.

Conclusion
In conclusion, this study has developed and validated a scale for evaluating English
language instructors’ VL for smartphone photography utilizing a social semiotic
theoretical framework. The findings of this investigation attest to the reliability andvalidity of the scale as a measure of VL for smartphone photography. The instrument
may serve as a benchmark for gauging VL for smartphone photography among English educators across diverse geographic and cultural contexts. The outcomes of thisresearch may be employed as a point of reference for future inquiries seeking to assess
VL among disparate populations of instructors and learners. Given the ubiquity andpotency of visual media, facilitated by the proliferation of mobile devices and hosting platforms, ELT educators are compelled to cultivate their VL to effectively adapt
and integrate photographic perspectives into a range of language learning tasks. The
attainment of VL represents an imperative for instructors striving to remain current
with and effectively engage learners’ burgeoning interest and expertise in utilizing visual resources.
Limitations of the study

The VLS4SP in this study was developed within a single context. Other researchers
could repeat this study in other contexts. New studies in new contexts can use this scale
to refine the measure. The VLS4SP developed in this study is beginning to understandthe English instructors’ VL for smartphone photography. Future studies could expand
the scope by including L2 instructors from various regions around the world. This
would not only diversify the sample but also enhance the generalizability of the scale,making it more universally applicable and robust across different cultural and educational contexts. This broader approach could provide more comprehensive insights into
VL in ELT.

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Appendix

Table 11 Items constructing the VLS4SP
Items representing factor 1
13. I know how to take/interpret photos that visualize subjective/objective relations between the photographedpeople/objects and the viewer
18. I know how to take/interpret photos that visualize an imaginary relation between the photographed people/
objects and the viewer
34. I know how to take/interpret photos that directly/indirectly address the viewer
40. I know how to take/interpret photos that use different camera angles intended to affect attitudes between
the photographed people/objects and the viewer
46. I know how to take/interpret photos that photograph people/objects that seem to offer information to theviewer
49. I know how to take/interpret photos that visualize the concept of power between the photographed people/
objects and the viewers
50. I know how to take/interpret photos that accurately visualize the subject matter and evoke a realistic feeling
57. I know how to take/interpret photos that visualize people/objects as parts of a whole class
62. I know how to take/interpret photos that use close/medium/long shots to visualize the social distance
between the photographed people/objects and the viewer
67. I know how to take/interpret photos that intend to visualize people/objects as symbols
Items representing factor 2
12. I know how to take/interpret photos of people/objects that visualize a social class membership
14. I know how to take/interpret photos that visualize people/objects associated with a special idea or concept
19. I know how to take/interpret photos that deliberately do not include certain people/objects
22. I know how to take/interpret photos that try to visualize who or what the photographed people/objects are
26. I know how to take/interpret photos that visualize the process of social relations between photographedpeople/objects
27. I know how to take/interpret photos that visualize people/objects with some features and exclude someother features
32. I know how to take/interpret photos that lay claim upon the viewers asking the viewers to reflect on what thephotographed people/objects want
42. I know how to take/interpret photos that convey the roles of photographed people/objects in an activity
51. I know how to take/interpret photos that visualize people/objects as typical of a particular group
63. I know how to take/interpret photos that intend to narrate an action taking place between the photographed people/objects
Items representing factor 3
15. I know how to take/interpret photos that place photographed people/objects in different spaces of photos
to achieve an intended meaningful whole
17. I know how to take/interpret photos that visualize the relative significance of represented participants, withthe most important elements depicted prominently and the least important elements relegated to a secondaryor tertiary role
20. I know how to take/interpret photos that visualize photographed people/objects in layouts creating sensesof connection or disconnection
24. I know how to take/interpret photos that intend to visualize photographed people/objects as different unitsof meaning
37. I know how to take/interpret photos that make the photographed people/objects more noticeable among
other elements
39. I know how to take/interpret photos that visualize photographed people/objects as new/given bits of information
56. I know how to take/interpret photos that visualize the photographed people/objects to stand out as separate
units or a group of the related unit

Abbreviations
VL	Visual literacy
VLS4SP	Visual literacy scale for smartphone photography
ELT	English language teaching
SEM	Structural equation modeling
L2	Second language
ACRL	Association of College and Research Libraries
EFA	Exploratory factor analysis
CFA	Confirmatory factor analysis
TLI	Tucker-Lewis index
CFI	Comparative fit index

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RMSEA	Root-mean-square error of approximation
GFI	Goodness-of-fit index
KMO	Kaiser-Meyer-Olkin
SLA	Second-language acquisition
Acknowledgements
We would like to acknowledge the significant contributions made by Professor Theo Van Leeuwen to this study. We
would also like to thank all language teachers who participated in this study. We would also like to acknowledge theeditor and the reviewers of this journal for encouraging our work to be much better.
Authors’ contributions
The authors confirm contribution to the paper as follows: study conception and design, AK; data collection, AK; analysis
and interpretation of results, both authors; and drafting and revising the manuscript, RK. Both authors reviewed theresults and approved the final version of the manuscript.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Availability of data and materials
The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Declarations
Competing interests
The authors declare that they have no competing interests.
Received: 12 April 2024 Accepted: 26 July 2024

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