Introduction

For learners who are immersed in learning English as a second or foreign language, it is essential to develop their skills in listening, speaking, reading, and writing (Karim & Mohamed, 2019; Karim et al., 2021). Equipping oneself with a good command of the English language stimulates both educational and professional success (Karim et al., 2022; Karim et al., 2023). Reading is linked to knowledge acquisition (Ismail et al., 2018) and reading comprehension (RC) skills are essential for readers to determine the true meaning of a given text.

Thailand, which is a core member of the Association of South East Asia Nations (ASEAN) and is an EFL country, necessitates the study of reading as a significant factor that promotes the communicative ability of its students in English—an official lingua franca in ASEAN (Baker, 2012). English is thus a compulsory subject in Thai public schools. Moreover, attaining proficiency in English is a prerequisite for Thailand to produce a globally efficient workforce (Kasemsap & Lee, 2015). In addition, both the academic success and professional development of Thais are determined by the extent to which they can communicate in English. Reading is therefore of importance since it helps learners acquire new vocabulary, achieve greater syntactic accuracy, and become familiar with various writing genres. However, there are also some pitfalls.

The nationally and internationally conducted reading tests designed by the Education Ministry of Thailand, the Programme for International Student Assessment (PISA), and the Organisation for Economic Co-operation and Development (OECD) indicated that Thai students possess poor ability in reading due to a lack of quality teaching that might have contributed to enhancing their reading performance (Hui et al., 2020). In addition, the time allocated for English reading in the classroom, reliance on Google Translator, and limited ability to apply cognitive strategies in reading substantiate their low performance in reading.

The present study furthers the investigation into the effect of demographic features on Thai learners’ RC skills to determine whether SES, regional differences, and gender play any role in determining the RC ability of the learners. Moreover, this study can add value to existing knowledge since a newly devised tool is employed to assess the reading performance of Thai learners.

Review of the Literature

The power of RC offers readers the opportunity to extract the intended message of the text through an interactive process which involves learners in extensive reading, resulting in the enrichment of their vocabulary, general knowledge, and cultural awareness. Both academic and professional success are connected to RC (Trapman et al., 2014) and RC skills are associated with the achievement of long-term academic success (Blything et al., 2020). Good RC ability can result in better grades for students. The capacity to read and comprehend written directives or instructions or relevant textual information is essential to get professional success. Ismail et al. (2018) also identified as successful students as those who are capable of understanding and extracting the meaning of the text and responding accordingly. As can be seen, over recent decades, much attention has been given to the examination of the RC skills of English language learners. Literature related to this field suggests serious and pervasive problems (le Roux et al., 2014) that limit the learners’ improvement in RC. Students’ involvement in reading and their success in RC are influenced by numerous social, behavioral, and environmental factors, including parental education, and the home environment (i.e., a chaotic, peaceful, or study-friendly environment), and attention to reading. The RC ability of English as a Second Language (ESL) or English as a Foreign Language (EFL) learners may also be affected more by demographic features (e.g., age, gender, socioeconomic status [SES], region, family history, and home literacy) than academic factors (e.g., institutional support, teachers and their style of teaching, learning materials, peer influences and relationships, the school itself, and its reading curriculum). Researchers have also argued that gender, SES, and region may or may not be significant predictors for ESL and EFL learners’ RC skills (Froiland & Oros, 2014; Melby-Lervag & Lervag, 2014).

Previous studies also presented mixed findings pertaining to the influence of these variables on learners’ RC ability. To illustrate, research showed that regional differences may positively or negatively affect learners’ reading comprehension because regional differences cause a variation in infrastructure, such as school facilities, instructional equipment, language learning materials, the professional competence of the teachers, and the ethnicity of the students in developed and less-developed regions of a country (Beckman et al., 2012; Cheung & Slavin, 2005; Figueroa & Sassenrath, 1989; Hu, 2003; Skrentny, 2020). Similarly, SES, which was also found by Cummins (1979), Melby-Lervåg and Lervåg (2014) to be a key contributing factor in learners’ development of second-language literacy skills, can also positively or negatively affect their RC ability (Cheng & Wu, 2017; Ismail et al., 2018; Modirkhemene, 2006; Romeo et al., 2018). Likewise, gender can be either a significant or non-significant predictor for learners’ RC skills (Corpas Arellano, 2013; Kaya & Yıldırım, 2018; Kusdemir & Bulut, 2018; Ngongare et al., 2020).

Worried about the mixed findings concerning the independent variables and dependent variable, the influence of regional differences, SES, and gender on ESL or EFL learners’ reading comprehension was examined in the current study to determine which factors predict Thai tertiary-level students’ RC. The study used the Thai Reading Evaluation and Decoding System (T-READS) to identify the reading comprehension ability of university students in Thailand since T-READS can be used in other settings to assess the actual reading performance of the learners (Appendix 2).

Prior studies have identified various issues associated with reading encountered by Thai learners. For instance, Hui et al. (2020) reported the low level of Thai students’ reading ability. The result of a reading test administered by the Education Ministry of Thailand suggested the poor level of Thai students in terms of reading (Rodklai as cited in Kasemsap & Lee, 2015). In the reading performance of the Programme for International Student Assessment (PISA) 2015, Thailand underperformed compared to its neighbouring countries, such as Vietnam. The performance of 15-year-old Thai students (M=409) was also found to be lower than the Organisation for Economic Co-operation and Development (OECD) average (M=493) (Organisation for Economic Co-operation and Development [OECD], 2018).Thai students also failed to achieve standard scores for the General Aptitude Test (GAT2) for English every year from 2016 to 2022. Moreover, the results from GAT2 suggested that Thai EFL students still required guidance to improve their reading performance, as can be seen in Figure 1. The analysis revealed that Thai EFL students tended to underperform in English proficiency tests.

Source: Source: The National Institute of Educational Testing Service (NIETS), 2022

Figure 1: Students’ GAT2 scores for English in percentages from 2016 to 2022

Previous studies and research hypotheses

Socio-economic status and reading comprehension

The socio-economic status of the ESL learners plays a significant role in the enhancement of the second language skills (Cummins, 1979; Hu, 2003). Melby-Lervåg and Lervåg (2014) added that learners with a higher SES tend to use context-independent language at home that corresponds to the language used in schooling, and this helps in the development of the learners’ literacy skills. Furthermore, SES has been identified as an antecedent of reading achievement that stands out for its comprehensiveness and attention to home factors, and thus may be a good predictor of long-term English literacy attainment (Reese et al., 2000). SES, therefore, may be a decisive factor for RC since it is linked to the education, profession, and earnings of the learners’ parents. Sirin (2005) revealed that learners’ academic performance mostly depends on the SES of the family. For example, as depicted by relevant prior studies, learners who are from financially secure backgrounds and have literate parents, have a better chance of getting higher scores than their counterparts (Beckman et al., 2012; Qi et al., 2006; Sirin, 2005).

As such, it can be assumed that academic success and SES are positively correlated (Calvo & Bialystok, 2014) as the more wealthy the family is, the better the quality of the resources and education provided for the children (Froiland & Oros, 2014). Moreover, Bradley and Corwyn (2002) reported a wealthy family home offers an environment that is conducive to learning and offers elevated social status. They found a stronger connection between SES and performance by observing that cognitive abilities such as memory, intellect, and language were influenced by SES. A similar study, by Powell et al. (2012), revealed that Euro-American children with parents with higher SES demonstrated better development than their African-American and Latino counterparts. Froiland et al. (2013) argued that family SES acts as a robust predictor of reading ability and Altschul (2012) suggested that SES is a potential predictor of reading comprehension achievements of learners from Mexican American families. Furthermore, Calvo and Bialystok (2014), in a study on Canadian learners, found that SES played a significant role in success in terms of academic and intellectual performance. The study demonstrated that working-class learners could not perform well in intricate tasks because of the influence of SES. Romeo et al. (2018) reported that Roma students with a poor SES profile had less RC growth in comparison to their non-Roma counterparts. Earlier, a study conducted by Cheng and Wu (2017) also indicated a similar role of SES in determining the RC of learners. However, Modirkhemene (2006) and Ismail et al. (2018) found SES to be a non-significant predictor for ESL learners’ RC.

Gender and reading comprehension

There is evidence to suggest a positive correlation between gender and RC. For example, Sheorey and Mokhtari (2001) asserted that learners’ gender not only had an influence on native speakers of American English but also on non-native learners. Corpas Arellano (2013), in a Spain-based study, indicated that girls outperformed boys in comprehending EFL texts. The study explained that gender differences were usually greater when the text contained implicit information. In contrast, a smaller difference was observed when the information was explicit in the text. The study also revealed that boys had serious difficulties in dealing with implicit information. In addition, Kusdemir and Bulut (2018) also found that the students’ level of RC varied significantly by gender in favor of the female students. Moreover, in a recent study, Ngongare et al. (2020) concluded that gender difference affected the RC of the learners by confirming that female students were better than male students in RC. Harper and Pelletier (2008) revealed that the development of literacy skills varied depending on the gender of the learners. The results of the Test of Early Reading Ability (TERA) suggested the existence of gender differences in children’s early reading development, where female students tended to obtain higher scores than their male counterparts. However, it is evident that the variation in scores of reading performance of girls and boys is commonly seen in young children, and such differences are seldom observed in the performance of older ones (MacFarlane, 2001). If has also been claimed that girls are more likely to outperform boys on tasks that included reading processes, such as phonological and semantic skills and RC, which suggests another reason for girls’ superiority in reading, according to Halper (1997) (see also Chiu & McBride-Chang, 2006; Mullis et al., 2003). To illustrate this, girls and boys tend to employ distinct techniques or strategies in RC tasks (Abu-Rabia, 2004; Chavez, 2001). Male students seem to be more analytical when compared to their female peers who seem to be more global when approaching RC tasks (Oxford, 1994). Wei (2009) noted that males tended to apply more rules whereas females adhered more to cultural differences. They added that learners, irrespective of gender, deploy various strategies, yet female learners were better able to do so more effectively. Moreover, Wassenburg et al. (2017) found that, when constructing and using sentences and words, girls were more likely to be consistent and coherent. However, a non-significant relationship between gender and RC has also been documented in the literature. For instance, Brantmeier (2003) asserted that gender had no impact on the learners’ RC. Kaya and Yıldırım (2018) argued that gender is a non-significant predictor for profiling the RC of the learners. They administered researcher-developed comprehension tests that focused on the deep and literal comprehension levels of the students. The study revealed that the gender of the students did not cause significant differences in reading fluency and reading comprehension. Using TERA–2, Harper and Pelletier (2008) stated that there was no significant difference in the scores obtained by girls and boys. Similarly, learners’ scores on the TERA–3 test suggested no influence of gender on reading ability. The findings of Harper and Pelletier’s (2008) study were congruent with Ismail et al. (2018).

Regional difference and reading comprehension

Regional difference is another significant factor that may affect the English proficiency of learners. Skrentny (2020) argued that region and ethnicity share similar characteristics with regard to ontology, the relationship of time, and boundaries. Ikegulu (2004) defined the role of ethnicity in predicting academic achievement. Variations in ethnic groups were studied in regard to learners’ RC skills. Cheung and Slavin (2005) confirmed that Latino and Caribbean children tended to perform poorly in ESL reading at schools in the United States. Beckman et al. (2012) examined the role of ethnicity (e.g., Black, Hispanic, and White) in the Nebraska State Accountability (NeSA) reading test. The study reported no difference in reading test scores as a result of ethnicity. Concerning ethnicity, research evidence revealed that Hispanic students scored higher in school than their Euro-American counterparts (Figueroa & Sassenrath, 1989). In addition, the researchers also revealed both positive and negative impacts of ethnicity on learners’ reading achievement (Beckman et al., 2012; Cheung & Slavin, 2005). Since studies indicated both significant and non-significant correlations between ethnicity and RC skills, and region shares similar characteristics as ethnicity, we can assume that region could also affect learners’ RC skills. Hu also (2003) presented clear region-oriented differences that had a significant effect on the reading, writing, listening, and speaking skills of the learners. Hu pointed out that regional difference is one of the decisive factors for learners’ reading comprehension ability. This claim has been endorsed by the previous literature arguing that contextual factors, such as region, play a pivotal role in determining learners’ reading comprehension abilities (Major et al., 2005; Medgyes & Niklove, 2002; Oxford, 2002). Regional differences result in the diversity of culture, which may positively or negatively affect the learners’ RC skills as culturally familiar texts are comprehended more accurately than culturally unfamiliar ones. In a study that employed three different reading comprehension sub-tests: a reading sub-test including culturally familiar topics and two reading sub-tests with culturally unfamiliar topics, Yousef et al. (2014) found that students attained greater scores in culturally familiar reading tests than culturally unfamiliar ones.

Numerous studies have been conducted to determine whether regional differences, socio-economic status (SES), and gender affect the learning of English as a Second Language (ESL) and reading comprehension (Corpas Arellano, 2013; Beckman et al., 2012; Cheung & Slavin, 2005; Figueroa & Sassernrath, 1989; Hu, 2003; Ismail et al., 2018; Melby-Lervåg & Lervåg, 2014; Modirkhemene, 2006; Ngongare et al., 2021; Romeo et al., 2018; Skrentny, 2020). Some of these studies reported the influence of the variables on ESL learners’ RC while others found no significant relationships. Thus the present study aims at examining the influence of gender, socioeconomic status, and regional difference on predicting EFL learners’ RC. García and Cain (2014) claimed that the existing literature presents little evidence concerning whether or not these factors positively or negatively affect the reading comprehension of the learners and, thus, necessitated research to be conducted in this regard. Consequently, Thailand, an EFL context, was selected to accomplish the study. Such study remains relatively unexplored not only in the Thai context, but also in other EFL contexts.

Concerning the correlation between the independent variables (SES, gender, and regional difference) and the dependent variable (reading comprehension), there are mixed observations documented in the previous literature. While most of the studies found a positive correlation between the independent and dependent variables, the non-significant nature of the relationship has been reported in some studies. To test this in a Thai setting, the following hypotheses were formulated:

Hypothesis 1: Gender predicts Thai EFL learners’ reading comprehension.

Hypothesis 2: Socioeconomic status predicts Thai EFL learners’ reading comprehension.

Hypothesis 3: Regional difference predicts Thai EFL learners’ reading comprehension.

Research Methodology

Research site

Founded in 1996, King Mongkut’s Institute of Technology Ladkrabang (KMITL) is a public higher education institution located in Bangkok, Thailand. It has seven faculties and four colleges with an enrollment of approximately 30,000 undergraduate and graduate students. It has provided higher education and research to advance technology, specifically in science and engineering for the sustainable development of Thailand. The institute is currently one of the best technological universities in Thailand and South-East Asia (Hui et al., 2020).

The skill of reading is perceived as essential for Thai engineering students to acquire and transfer knowledge, which, in turn, affects the nation’s infrastructural prosperity and economic growth. However, tertiary students’ reading comprehension ability has been identified as inadequate to facilitate knowledge acquisition, as confirmed by numerous tests of English reading comprehension ability (Hui et al., 2020). The current study was an attempt to examine the impact of gender, SES, and regional difference on the RC skills of learners.

Participants of the study

The target population of this study was 6,289 KMITL freshmen students. Convenience sampling (Patton, 2002) was chosen because the students who participated in this study were easily accessible since they all studied Foundation English. Instructors on two campuses (Bangkok and Chumphon provinces) were formally contacted to obtain permission to administer the test during scheduled classes. Based on Krejcie and Morgan’s (1970) table, for a given population of 6,289, a sample size of 361 is satisfactory to represent a cross-section of the population within a 5% margin of error and a 95% confidence level. However, we increased the sample size to at least 10% of the target population, and a convenience sample of 820 was recruited.

The participants were first-year university undergraduates from nine faculties and various academic programs. They represented a cross-section of gender, SES, and region where SES was determined based on monthly family income. The commonly adopted practice for determining SES is to consider family income, parental education, and parental occupation together (Bradley & Corwyn, 2002; Sirin, 2005). For the current study, the researchers employed family income to determine the SES of the participants. Four groups were identified as shown in Table 1.

Table 1: SES and participants

Moreover, the participants were members of different regions as illustrated in Table 2.

Table 2: Region and participants

The participants’ responses in regard to demographic information were obtained from the test. Intriguingly, although KMITL is in the central region, the participants from the northern region made up a majority. The gender of the participants is shown in Table 3.

Table 3: Gender and participants

As mentioned above, the initial number of participants was 820. However, some of the participants were excluded from the study because of incomplete answers to the questions or inadequate information (i.e., not answering all the questions concerning either socioeconomic status or region). The inclusion criteria set for the study involved completing the test and supplying the required information by including all of the requested demographic data that determined their SES, gender, and place of origin to satisfy the research need. In the process, 730 participants remained who formed the final sample for the study.

Instrumentation

In Thailand, standardized testing is employed; however, the results of the tests do not provide evidence about the reading comprehension abilities of the students. There is also no English placement test to determine RC ability of each student (Hui et al., 2020). As such, the need for profiling undergraduates by adopting statistically sound and reliable testing instruments for assessing ability in RC is echoed in many studies. An instrument was developed, known as the Thai Reading Evaluation and Decoding System (T-READS), to assist in testing English reading comprehension ability. Notably, using such an instrument to measure reading comprehension ability would inform the undergraduates about their “comprehensibility profile” (Isaacs et al., 2018, p. 199) and foster awareness of their actual reading comprehension ability.

The most significant element of T-READS concerns the inclusion of cut scores (i.e., categorizing the students who scored below and above the standard) that offer more precise information about their RC skills. The cut scores have imperative significance for test-takers and test-developers, especially within the context of diagnostic tests, such as T-READS (Hui et al., 2020). By employing T-READS in universities, the cut scores reflect the detailed information of the students studying English courses. Hui et al. argued that determining the cut scores assists in placing students at a level that matched their ability.

Nevertheless, validity generalization and test utility must be considered. There is disagreement over these issues because this original test instrument was predominantly developed and administered to Malaysian students and thereby involved contextual biases. For that reason, the original Reading Evaluation and Decoding System (READS) was considered unfit for Thai students. Adapting the test instrument, rather than developing a new one explicitly for the target stakeholder is considered more suitable since using an adapted version offers higher validity within an increasingly diverse population In the adaptation process, the original READS was adopted and only one main factor affecting student test results, contextual bias, was adapted.

It is worth mentioning that adapting a test instrument is a complex task since it involves a careful arrangement and procedure, particularly materials and test utility, for the target audience (Cassepp-Borges et al. as cited in Borsa et al., 2012). It should be noted that the adaptation maintains a cultural fit and is the groundwork for practice in diverse cultural contexts. Three individuals who specialized in English language assessment were involved in the adaptation of READS. These experts were given a paper-based test of the original READS to give opinions about biases inherent in the test instrument and ways to amend it. Other vital aspects, such as layout and the level of difficulty, were also then evaluated. The experts then considered whether the vocabulary could be applied in a Thai context and whether it was suited for the target audience. In a reading passage, for instance, Malaysia Airlines was replaced with Thai Airways, and Hashim, a Malay name, was changed to Ekkapon to reflect Thai culture (Hui et al., 2020). Such changes ensure that the test is a test of reading comprehension rather than a test of global knowledge as cultural and background differences may lead to assessment inaccuracies Thus, the test should not contain elements that require cultural knowledge. As an example, in a passage in the original READS, Ujian Pencapaian Sekolah Rendah (UPSR) is mentioned. While Malaysian people would be familiar with it because it is form of assessment in Malaysia, Thaistudents have no knowledge of UPSR. Therefore, a localized Thai version was developed and employed to assess undergraduates’ English reading comprehension at any level in Thai universities.

Content Validity Index (CVI) refers to the index of interrater agreement from experts. The item's relevance is calculated through a validation process of the entire scale. The Content Validity Index is the most-used approach of content validity to enable the rejection or retention of each item (Ahmad et al., 2019). As for T-READS, the test was evaluated by a panel of three experts, who were senior English teachers from Thailand. The experts rated the relevance of the T-READS items by using a 4-point scale validation form (1=not relevant; 2=somewhat relevant; 3=quite relevant; 4=highly relevant). The test was revised and finalized based on the feedback from the experts.

Table 4: S-CVI for relevancy of T-READS

As shown in Table 2, the S-CVI rating is based on the S-CVI guideline suggested by Davis (1992). Furthermore, to confirm that the instrument is reliable, a pilot study was conducted (Ismail et al., 2018). A total of 624 university students took the test. Using the KR-20 coefficient in Statistical Package for the Social Sciences (IBM SPSS) software version 22 indicated the homogeneity of the test (KR-20 = 0.91).

Table 5: Analysis of test reliability

The T-READS showed a high value of 0.91 in the KR-20 and 0.97 S-CVI, which suggested the homogeneity of the test, implying that the instrument was applicable in measuring the undergraduates’ reading performance. In short, we perceived that in a large-scale study, it would be essential to know the technical indicators which define the quality of the educational instrument employed. The Thai version of READS employed to determine the Thai undergraduates’ reading comprehension ability (Khemanuwong et al., 2018). According to Ismail et al. (2018), the content validity of the T-READS was high with 0.92 of the index of item objective congruence (IOC). Moreover, the T-READS attained test reliability with a KR-20 coefficient of 0.91.

Fundamentally, T-READS comprises three components – the Encoder (i.e., the test instrument), which is one of the instruments of the test to understand the reading comprehension ability of EFL learners as explained in Ismail et al. (2018); the analyzer or reading matrix, and, the decoder, which explains the reading performance of a student as illustrated in Figure 2. Firstly, 60 multiple-choice questions were administered that enabled the Encoder to measure the participants’ ability in RC. As a cross-reference for the ability in RC, the Reading Matrix marks an individual to an appropriate level of “Above Standard,” “Meet Standard,” “Below Standard,” and “Academic Warning.” Lastly, the Descriptors of Reading Abilities (from Band 1 to Band 6) are used to determine what learners were (or were not) able to achieve based on the given answers.

Figure 2: Components of the T-READS adaptation based on Ismail et al. (2018)    

Table 6: T-READS bands

Considering the adjustment of T-READS, which affected only the Encoder (test), the results of the Analyser (the Reading Matrix) and Decoder (the Descriptors of Reading Abilities) were employed to inform the test developers about the necessary information of the test-takers’ RC abilities (Ismail et al., 2018).

According to Boopathiraj and Chellamani (2013), questions in a test should indicate a certain level of difficulty. In the T-READS test, 60 questions with three difficulty levels – easy (25%), moderate (50%), and difficult (25%) were included (Mok, 2000) with three sub-skills of reading comprehension (i.e., literal, reorganization, and inferential), based on Barrett’s taxonomy of reading comprehension (Lim et al., 2014). Finally, the T-READS test was found to be high in the power of discrimination with 0.51 while the Malaysian READS was at 0.22. From the power of discrimination index, the T-READS could also illustrate students’ abilities in each sub-skill with three levels of difficulty (i.e., low, moderate, and high).

Data collection procedure

To examine the relationship between the independent variables (gender, socioeconomic status, and region) and the dependent variable (reading comprehension), the reading comprehension score of the participants was identified first by adopting T-READS. After that, the relationship between the independent and dependent variables was examined. Before the participants took the test, a brief orientation session presenting the main purpose of the research was conducted.

In T-READS, undergraduates respond to various types of text, such as conversations, news, academic reports, and descriptive texts (Hui et al., 2020). Appendix 1 contains sample questions that indicate the nature of the questions included in the test. The test was uploaded onto the KMITL Online Test of English Proficiency website for the undergraduates to take online (see examples in Figures 3, 4, 5, 6). During the test, the procedures for using the T-READS followed the time allocation guidelines in Ismail et al.’s (2018) study, which provided 70 minutes for test-takers to complete the online test.

Figure 3: Approaching T-READS

Figure 4: Login page

Figure 5: Student menu

Figure 6: Student result

Ethical considerations

At the onset of data collection, the second author applied for administrative approval from the university and the Research Ethics Committee of King Mongkut’s Institute of Technology Ladkrabang (Study Code: EC-KMITL_67_092) to gain official permission to conduct the study and sought the participants’ consent. The participants were informed about the purpose of the study, the confidentiality and anonymity that were maintained in reporting the findings, the dissemination of the findings, the benefits of the findings, and their right to withdraw from the study prior to seeking their consent for participating in the study (Creswell & Poth, 2017). These were accomplished to ensure that the inquiry was ethical and respectful. The test was administered to the university undergraduates following the procedures set for the application of READS as outlined by Ismail et al. (2018).

Data analysis

An exploratory process was applied for data analysis. In the first phase of the exploratory part, data sets have been summarized. Then, the data were subjected to SPSS with a particular focus on linear regression to determine the predictability of the independent variables (gender, socioeconomic status, and region) against the dependent variable (reading comprehension).

Findings

The current study employed linear regression analysis to examine the relationship between the dependent variable (READS score) and independent variables (gender, SES, and region). The analysis of the data suggested that gender was not a significant predictor in determining EFL learners’ reading comprehension as indicated by p>.05 (p=.30 related to gender in this study). This is congruent with Kaya and Yıldırım’s (2018) study that reported that gender and students’ RC were not positively correlated. This finding is also consistent with that of Ismail et al. (2018) although Harper and Pelletier (2008) suggested that the learners’ ability in RC varied depending on their gender.

Table 7: Coefficients

SES was also not found to be a determinant for EFL learners’ reading comprehension, indicated by p>.05 (p=.941 related to SES in this study). The findings of the current study did not concur with those of previous studies. Romeo et al. (2018) reported the predictive ability of SES in determining the RC of learners and Cheng and Wu (2017) identified the significance of SES in determining the RC of the learners. Calvo and Bialystok (2014) identified SES as a strong determinant, as indicated by p<.05, for the language and cognitive development of the learners. Likewise, Powell et al. (2012) and Altschul (2012) defined SES as a significant predictor of the learners’ achievement and mastery in RC. However, the findings of this study corresponded to that of Modirkhamene (2006), in that there was no relationship between SES and RC, as estimated with p>.05 (with ps=.98, .07, .08). In the same vein, Beckman et al. (2012) reported that poverty was not an influential factor for learners’ RC, as indicated by p<.05. Furthermore, the current study observed no predictability in regard to region for EFL learners’ reading comprehension with p>.05 (p =.393 related to the regional difference in this study).

Hypothesis Testing

The findings of the current study enable us to test the hypotheses as follows:

Hypothesis 1: Gender predicts Thai EFL learners’ reading comprehension → Rejected.

Hypothesis 2: Socioeconomic status predicts Thai EFL learners’ reading comprehension → Rejected.

Hypothesis 3: Regional difference predicts Thai EFL learners’ reading comprehension → Rejected.

Discussion

In the present study, T-READs was employed to obtain the RC scores of EFL learners. Demographic information was also collected to inform the researchers about gender, SES, and region. Data analysis was conducted to determine whether the three distinct independent variables (gender, SES, and regional difference) influenced RC. The study revealed that the distinct independent variables were not significant predictors of EFL learners’ RC. The study also revealed that gender was not a significant predictor of Thai EFL learners’ RC, reflecting the results of previous studies that indicated that the sexes shared similar features (Sainsbury & Schagen, 2004). Considering the use of reading strategies, Poole (2005) also found no significant difference between male and female students in terms of reading strategy use. Yet, some other studies suggested that female students were more likely to use reading strategies than male students (Poole, 2009). In regard to Thailand, the homogeneous nature of reading strategy use was predicted for both male and female students and the present study observed no role of gender in predicting Thai learners’ RC. Moreover, with a similar mean for both sexes - 1.9928 and 1.9978 respectively, there was no visible difference observed in their attained scores in the T-READS test. However, the level of education (first-year students at the university) might be an influential factor. As regards university students in Thailand, it can be predicted that they seem to share a common attitude towards reading for which gender has no significance in terms of their reading comprehension.

Like gender, regional differences were also identified to be insignificant predictors of RC in the current study. However, some studies reported the influence of regional variations. For instance, Major et al. (2005) reported that regional factors were key predictors of learners’ comprehension. Hu’s (2003) study identified a clear region-based difference in learners’ proficiency in reading. According to Hu, regional difference came into prominence once economic, political, cultural, and curricular factors became functional and eventually develop the constraints involved in approaches to teaching and learning English. According to these findings, Thailand may not have suffered from those economic, political, cultural, and curricular constraints that had affected English teaching and learning in other locations. For this reason, the role of regional difference was found to be insignificant in predicting Thai learners’ RC. Hu also suggested that infrastructural resources, including school facilities, instructional equipment, language learning materials, and the professional competence of teachers, could be the product of government policies and economic development. Since we observed no impact of regional differences in the university studied, it is possible that there was homogeneity in terms of school facilities, instructional equipment, language learning materials, and professional competence of teachers. Similar means for Central, Northern, Southern, Eastern, and Western Regions in the T-READS scores (1.5227, 1.6366, 1.6087, 1.6000, 1.5692, and 1.6250 respectively). Thus, regional differences were not be found to be influential to the outcome of the current study.

The SES of the parents also was shown not to be a predictor of Thai learners’ RC, although Parcel and Menaghan (1990) expressed the idea that parents involved in intellectually stimulating jobs tended to provide more support and thought-provoking educational materials for their children With diversity in SES, the limited ability of Thai parents to provide their children with supportive and stimulating materials could limit the progress of the learner. In addition, a similar mean for the participants with various SES (1.6087 (0-10000), 1.6204 (10000-25000), 1.6596 (25001-40000), and 1.6020 (40001-Above) respectively) was seen in the READS scores. Thus, due to a diversity in SES and the variation in the number of participants from different SES, the difference in SES was influential to the outcome of the study.

Future studies

The present study was limited to understanding the correlation between three demographic factors (social economic status (SES), regional difference, and gender) and Thai learners’ reading comprehension ability. However, other factors might positively or negatively affect the ability of the learners to comprehend a reading test. For example, the first language of the learners could affect the development of second-language skills. Considering the time-on-task hypothesis by Porter (1990), Melby-Lervåg and Lervåg (2014) argued that the time spent learning the first language could have a significant impact on the development of second-language skills. Added to this, intrinsic motivation positively or negatively affects in building ability in RC (Becker et al., 2010). In line with this, the current study proposed future studies be dedicated to examining the RC ability in the light of these variables. T-READS can be considered as a valuable instrument for profiling the actual reading standards of the learners in Thailand, but may need to be adjusted to suit local settings elsewhere. As a result, other countries could reconsider the impact of gender, SES, and regions on developing the RC of learners. T-READS acts as an effective tool to measure the correlation of RC with any variable because to keep the track of the performance of the students on reading, the conventional system of assessment does not identify or specify the particular status of reading comprehensibility of the learners whereas T-READS is set with some certain descriptors that can define the status of reading comprehensibility of the learners.

Conclusion

The current study examined the effect of social economic status (SES), regional variations and gender on determining Thai learners’ reading comprehension. Data was collected from first-year EFL undergraduates from nine faculties and various academic programs of a Thai university. These provided the demographic information which let them discover the participants’ gender, SES, and regions. Then an instrument known as T-READS (Thai Reading Evaluation and Decoding System) was developed and applied to test learners’ English reading ability and ascertain their scores in reading comprehension. Applying linear regression in SPSS, the researchers discovered that gender, SES, and regional differences did not play any role in determining the reading comprehension ability of the participants in the study. The participants were limited to one university which limited to possibility to make definitive conclusions on the results of each variable. Hence, a nationwide study, using the methods applied in this study to collect data from learners of different regions and educational levels would further contribute to determining the effect of SES, regional variation, and gender on the reading comprehension of Thai students.

References

Abu‐Rabia, S. (2004). Teachers' role, learners' gender differences, and FL anxiety among seventh‐grade students studying English as a FL. Educational Psychology, 24(5), 711-721. https://doi.org/10.1080/0144341042000263006

Ahmad, N. A., Drus, S. M., Kasim, H., & Othman, M. M. (2019, April). Assessing content validity of enterprise architecture adoption questionnaire (EAAQ) among content experts. 2019 IEEE 9th Symposium on Computer Applications & Industrial Electronics (ISCAIE) (pp. 160-165). IEEE. https://doi.org/10.1109/ISCAIE.2019.8743918

Altschul, I. (2012). Linking socioeconomic status to the academic achievement of Mexican American youth through parent involvement in education. Journal of the Society for Social Work and Research, 3(1), 13-30. https://doi.org/10.5243/jsswr.2012.2

Baker, W. (2012). English as a lingua franca in Thailand: Characterisations and implications. Englishes in Practice, 1(1), 18-27.

Blything, L. P., Hardie, A., & Cain, K. (2020). Question asking during reading comprehension instruction: Acorpus study of how question type influences the linguistic complexity of primary school students’ responses. Reading Research Quarterly, 55(3), 443-472. https://doi.org/10.1002/rrq.279

Boopathiraj, C., & Chellamani, K. (2013). Analysis of test items on difficulty level and discrimination index in the test for research in education. International Journal of Social Science & Interdisciplinary Research, 2(2), 189-193.

Borsa, J. C., Damásio, B. F., & Bandeira, D. R. (2012). Cross-cultural adaptation and validation of psychological instruments: Some considerations. Paidéia (Ribeirão Preto), 22(53), 423-432. https://doi.org/10.1590/S0103-863X2012000300014

Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic status and child development. Annual Review of Psychology, 53(1), 371-399. https://doi.org/10.1146/annurev.psych.53.100901.135233

Brantmeier, C. (2003). Does gender make a difference? Passage content and comprehension in second language reading. Reading in a Foreign Language, 15(1), 1539-1578. http://hdl.handle.net/10125/66585

Calvo, A., & Bialystok, E. (2014). Independent effects of bilingualism and socioeconomic status on language ability and executive functioning. Cognition, 130(3), 278-288. https://doi.org/10.1016/j.cognition.2013.11.015

Chavez, M. (2001). Gender in the language classroom. McGraw-Hill.

Cheng, Y., & Wu, X. (2017). The relationship between SES and reading comprehension in Chinese: A mediation model. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.00672  

Cheung, A., & Slavin, R. E. (2005). Effective reading programs for English language learners and other language-minority students. Bilingual Research Journal, 29(2), 241-267. https://doi.org/10.1080/15235882.2005.10162835  

Chiu, M. M., & McBride-Chang, C. (2006). Gender, context, and reading: A comparison of students in 43 countries. Scientific Studies of Reading, 10(4), 331-362. https://doi.org/10.1207/s1532799xssr1004_1  

Corpas Arellano, M. D. (2013). Gender differences in reading comprehension achievement in English as a foreign language in compulsory secondary education. Tejuelo, 17(1), 67–84. http://hdl.handle.net/10662/4773

Creswell J. W., & Poth C. N. (2017). Qualitative inquiry and research design: Choosing among five approaches. Sage.

Cummins, J. (1979). Linguistic interdependence and the educational development of bilingual children. Review of Educational Research, 49(2), 222–251. https://doi.org/10.3102/00346543049002222  

Davis, L. L. (1992). Instrument review: Getting the most from a panel of experts. Applied Nursing Research, 5(4), 194-197. https://doi.org/10.1016/S0897-1897(05)80008-4

Figueroa, R. A., & Sassenrath, J. M. (1989). A longitudinal study of the predictive validity of the system of multicultural pluralistic assessment (SOMPA). Psychology in the Schools, 26(1), 5-19. https://doi.org/10.1002/1520-6807  

Froiland, J. M., Powell, D. R., Diamond, K. E., & Son, S. H. C. (2013). Neighborhood socioeconomic well‐being, home literacy, and early literacy skills of at‐risk preschoolers. Psychology in the Schools, 50(8), 755-769.https://doi.org/10.1002/pits.21711

Froiland, J. M., & Oros, E. (2014). Intrinsic motivation, perceived competence and classroom engagement as longitudinal predictors of adolescent reading achievement. Educational Psychology, 34(2), 119-132. https://doi.org/10.1080/01443410.2013.822964  

García, J. R., & Cain, K. (2014). Decoding and reading comprehension: A meta-analysis to identify which reader and assessment characteristics influence the strength of the relationship in English. Review of Educational Research, 84(1), 74-111. https://doi.org/10.3102/0034654313499616

Halpern, D. F. (1997). Sex differences in intelligence: Implications for education. American Psychologist, 52(10), 1091-1102.

Harper, S. N., & Pelletier, J. P. (2008). Gender and language issues in assessing early literacy: Group differences in children's performance on the test of early reading ability. Journal of Psychoeducational Assessment, 26(2), 185-194. https://doi.org/10.1177/0734282908314105  

Hu, G. (2003). English language teaching in China: Regional differences and contributing factors. Journal of Multilingual and Multicultural Development, 24(4), 290-318. https://doi.org/10.1080/01434630308666503  

Hui, K. S., Saeed, K. M., & Khemanuwong, T. (2020). Reading comprehension ability of future engineers in Thailand. MEXTESOL Journal, 44(4). https://www.mextesol.net/journal/index.php?page=journal&id_article=22026

Ikegulu, T. N. (2004). The impacts of demographic factors in predicting student
performance on a state reading test (ED509320). ERIC. https://eric.ed.gov/?id=ED509320

Isaacs, T., Trofimovich, P., & Foote, J. A. (2018). Developing a user-oriented second language comprehensibility scale for English medium universities. Language Testing, 35(2), 193-216. https://doi.org/10.1177/0265532217703433

Ismail, S. A. M. M., Karim, A., & Mohamed, A. R. (2018). The role of gender, socioeconomic status, and ethnicity in predicting ESL learners’ reading comprehension. Reading & Writing Quarterly, 34(6), 457-484. https://doi.org/10.1080/10573569.2018.1462745

Kang, E. Y., & Shin, M. (2019). The contributions of reading fluency and decoding to reading comprehension for struggling readers in fourth grade. Reading & Writing Quarterly, 35(3), 179-192. https://doi.org/10.1080/10573569.2018.1521758

Karim, A., Islam, M. S., Hamid, M. O., Rahman, M. M., & Amin, E. U. (2023). Language ideology, development of English proficiency, and performance in professional communication: voices of STEM+ business graduates of English medium university. Asian-Pacific Journal of Second and Foreign Language Education, 8(1), 1-27. https://doi.org/10.1186/s40862-023-00200-w

Karim, A., Kabilan, M. K., Rahman, S., Shahed, F. H., & Rahman, M. M. (2021). Revisiting the high-profile English in Action teacher professional development program in Bangladesh: Promises, prospects, and eventualities. MEXTESOL Journal, 45(2). https://www.mextesol.net/journal/index.php?page=journal&id_article=23530

Karim, A., Kabilan, M. K., Sultana, S., Reshmin, L., & Ahmed, Z. (2022). English medium instruction in higher education: An attempt to understanding teacher identity in Malaysia and China. MEXTESOL Journal, 46(1). https://doi.org/10.61871/mj.v46n1-12

Karim, A., & Mohamed, A. R. (2019). Examining the impact of an English in Action training program on secondary-school English teachers’ classroom practice in Bangladesh. The Qualitative Report, 24(3), 441-469. https://doi.org/10.46743/2160-3715/2019.3703

Kasemsap, B., & Lee, H. Y.-H. (2015). L2 reading in Thailand: Vocational college students’ application of reading strategies to their reading of English texts. The Reading Matrix: An International Online Journal, 15(2), 101-117. https://www.readingmatrix.com/files/13-p0gvv09k.pdf

Kaya, D., & Yıldırım, K. (2018). Akıcı okuma ve okuduğunu anlama arasındaki ilişkilerde cinsiyet nasıl bir rol oynamaktadır? [How does gender impact the relationship between reading fluency and reading comprehension?]. Journal of Human Sciences, 15(2), 931-942.

Khemanuwong, T., Mohamed, A. R., & Ismail, S. A. M. M. (2018). Developing a Thai READS encoder to gauge EFL reading proficiency of Thai undergraduate students. TLEMC (Teaching and Learning English in Multicultural Contexts), 2(1), 23-34. https://psycnet.apa.org/doi/10.1037/0003-066X.52.10.1091

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and psychological measurement, 30(3), 607-610. https://doi.org/10.1177/001316447003000308

Kuşdemir, Y., & Bulut, P. (2018). The relationship between elementary school students’ reading comprehension and reading motivation. Journal of Education and Training Studies, 6(12), 97-110. https://redfame.com/journal/index.php/jets/article/view/3595

Lim, C. K., Eng, L. S., & Mohamed, A. R. (2014). Benchmarking year five students' reading abilities. English Language Teaching, 7(5), 50-58. https://doi.org/10.5539/elt.v7n5p50

MacFarlane, L.M. (2001). Gender differences in reading achievement and early literacy experiences (ED451476] ERIC.http://files.eric.ed.gov/fulltext/ED451476.pdf

Major, R. C., Fitzmaurice, S. M., Bunta, F., & Balasubramanian, C. (2005). Testing the effects of regional, ethnic, and international dialects of English on listening comprehension. Language Learning, 55(1), 37-69. https://doi.org/10.1111/j.0023-8333.2005.00289.x

Medgyes, P., & Nikolov, M. (2002) Curriculum development: The interface between political and professional decisions. In R.B. Kaplan (Ed.). The Oxford handbook of applied linguistics (pp. 195–206). Oxford University Press.  

Melby-Lervåg, M., & Lervåg, A. (2014). Reading comprehension and its underlying components in second-language learners: A meta-analysis of studies comparing first-and second-language learners. Psychological Bulletin, 140(2), 409-433. https://doi.org/10.1037/a0033890  

Mok, S. S. (2000). Ilmu pendidikan untuk KPLI (Kursus perguruan lepas Ijazah) [Educational knowledge for KPLI (Graduate teaching course)]. Kumpulan Budiman.

Mullis, I. V. S., Martin, M., Gonzalez, E. J., & Kennedy, A. M. (2003). PIRLS 2001 international report: IEA’s study of reading literacy achievement in primary schools in 35 countries. Boston College.

le Roux, M. C., Swartz, L., & Swart, E. (2014, December). The effect of an animal-assisted reading program on the reading rate, accuracy and comprehension of grade 3 students: A randomized control study. Child & Youth Care Forum, 43, 655-673. https://doi.org/10.1007/s10566-014-9262-1  

Lim, C. K., Eng, L. S., & Mohamed, A. R. (2014). Benchmarking year five students' reading abilities. English Language Teaching, 7(5), 50-58. https://eric.ed.gov/?id=EJ1075733

Modirkhamene, S. (2006). The reading achievement of third language versus second language learners of English in relation to the interdependence hypothesis. International Journal of Multilingualism, 3(4), 280-295. https://doi.org/10.2167/ijm043.0

Ngongare, G., Samola, N. F., & Rettob, A. (2020). The influence of gender on reading comprehension. Journal of English Language and Literature Teaching, 5(2), 104-109. http://ejurnal.unima.ac.id/index.php/jellt/article/view/6880

Oxford, R. (1994). Language learning strategies: An update (ED376707). https://files.eric.ed.gov/fulltext/ED376707.pdf

Oxford, R. L. (2002) Sources of variation in language learning. In R.B. Kaplan (Ed.) The Oxford handbook of applied linguistics(pp. 245–252). Oxford University Press.

Parcel, T. L., & Menaghan, E. G. (1990). Maternal working conditions and children's verbal facility: Studying the intergenerational transmission of inequality from mothers to young children. Social Psychology Quarterly, 53(2). 132-147. https://psycnet.apa.org/doi/10.2307/2786675

Patton, M. Q. (2002). Two decades of developments in qualitative inquiry: A personal, experiential perspective. Qualitative Social Work, 1(3), 261–283. https://doi.org/10.1177/1473325002001003636

Poole, A. (2005). Gender differences in reading strategy use among ESL college students. Journal of College Reading and Learning, 36(1), 7-20. https://doi.org/10.1080/10790195.2005.10850177

Poole, A. (2009). The reading strategies used by male and female English language learners: A study of Colombian high school students. The New England Reading Association Journal, 46(1), 55-63.

Porter, R. (1990). Forked tongue: The politics of bilingual education. Basic Books.

Powell, D. R., Son, S.-H., File, N., & Froiland, J. M. (2012). Changes in parent involvement across the transition from public school prekindergarten to first grade and children's academic outcomes. The Elementary School Journal, 113(2), 276-300. https://doi.org/10.1086/667726  

Qi C. H., Kaiser A. P., Milan S., & Hancock T. (2006). Language performance of low-income African American and European American preschool children on the PPVT-III. Language, Speech, and Hearing Services in Schools, 37, 5– 16. https://doi.org/10.1044/0161-1461(2006/002)

Reese, L., Garnier, H., Gallimore, R., & Goldenberg, C. (2000). Longitudinal analysis of the antecedents of emergent Spanish literacy and middle-school English reading achievement of Spanish-speaking students. American Educational Research Journal, 37(3), 633-662. https://doi.org/10.3102/00028312037003633

Romeo, R. R., Christodoulou, J. A., Halverson, K. K., Murtagh, J., Cyr, A. B., Schimmel, C., Chang, P., Hook P. E., & Gabrieli, J. D. (2018). Socioeconomic status and reading disability: neuroanatomy and plasticity in response to intervention. Cerebral Cortex, 28(7), 2297-2312. https://doi.org/10.1093/cercor/bhx131  

Sainsbury, M., & Schagen, I. (2004). Attitudes to reading at ages nine and eleven. Journal of Research in Reading, 27(4), 373-386. https://doi.org/10.1111/j.1467-9817.2004.00240.x

Sheorey, R., & Mokhtari, K. (2001). Differences in the metacognitive awareness of reading strategies among native and non-native readers. System, 29(4), 431-449. https://doi.org/10.1016/S0346-251X(01)00039-2

Shepard, J., Beckman, T. O., Cates, B., & Messersmith, K. (2012). Ethnicity, language and poverty predicting scores on the Nebraska state accountability reading test. International Journal of Psychology, 11, 31-47. https://doi.org/10.7220/1941-7233.11.2  

Sireci, S. G., Yang, Y., Harter, J., & Ehrlich, E. J. (2006). Evaluating guidelines for test adaptations: A methodological analysis of translation quality. Journal of Cross-Cultural Psychology, 37(5), 557-567. https://doi.org/10.1177/0022022106290478

Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75(3), 417-453. https://doi.org/10.3102/00346543075003417

Skrentny, J. D. (2020). Theorizing region: Links to ethnicity, nation, and race. Sociological Theory, 38(1), 1-15. https://doi.org/10.1177/0735275120902182

Trapman, M., van Gelderen, A., van Steensel, R., van Schooten, E., & Hulstijn, J. (2014). Linguistic knowledge, fluency and meta‐cognitive knowledge as components of reading comprehension in adolescent low achievers: Differences between monolinguals and bilinguals. Journal of Research in Reading, 37(S1), S3-S21. https://doi.org/10.1111/j.1467-9817.2012.01539.x  

 Wassenburg, S. I., de Koning, B. B., de Vries, M. H., Boonstra, A. M., & van der Schoot, M. (2017). Gender differences in mental simulation during sentence and word processing. Journal of Research in Reading, 40(3), 274-296. https://doi.org/10.1111/1467-9817.12066

Wei, W. (2009). Gender differences in reading comprehension for Chinese secondary school students. [Unpublished master’s thesis]. University of Wisconsin-Platteville. https://minds.wisconsin.edu/bitstream/handle/1793/34565/WeiWei.pdf?sequence=5

Yousef, H., Karimi, L., & Janfeshan, K. (2014). The relationship between cultural background and reading comprehension.Theory & Practice in Language Studies, 4(4), 707-714. https://doi.org/10.4304/tpls.4.4.707-714