A Study of the Predictors of English and Persian Language Learners’ Psychological Well-Being

Introduction

A close scrutiny of the recent studies (e.g. Talebzadeh et al., 2020; Teng & Zhang, 2016, 2018; Xie & Derakhshan, 2021; Yin et al., 2019; Zhang et al., 2012) highlights the fact that positive psychology has become a recurrent line of research in the empirical studies of higher education.  Seligman and Csikszentmihalyi (2000) stated that the interest in this approach to human psychology in the field of education stems from the researchers’ realization of the fact that learners’ positive emotions have the potential to prevent their negative feelings, such as anxiety, from intervening in their process of learning in higher education settings.

Considering this issue, Peterson (2006) defined positive psychology as the scientific scrutiny of the individuals’ affective factors that are likely to ameliorate their attitudes toward life and their performance in diverse academic and occupational contexts. Likewise, Wang et al. (2023) pointed out that this field of psychology focuses on the circumstances that promote people’s optimal functioning in diverse situational contexts. As they explained, positive psychology intends to ameliorate human beings’ life quality. To this end, it focuses on specific concepts including true happiness, flourishment, and subjective well-being among others, and examines the degree to which these concepts influence individuals’ mental health in occupational, educational, and social settings.

Moreover, Strecker et al. (2020) stated that this psychology branch mainly focuses on individuals’ subjective feelings about their good lives. They pointed out that good life encompasses three main sub-components including self-expression, life-engagement, and well-being. As they explained, self-expression refers to people’s capability to represent their emotions, thoughts, and beliefs in an explicit way in order to develop a unique identity in their community. Furthermore, life engagement refers to individuals’ capability to determine their objectives and to engage in activities that facilitate their achievement of the relevant objectives. In addition, well-being involves the individuals’ psychological, physical, and emotional health resulting in their satisfaction with different aspects of their lives. Lastly, Ryff (2022) stated that positive psychology is mainly concerned with people’s quality of life. According to him, quality of life determines the individuals’ perspectives on their own life enjoyment, effective occupational and educational functioning, and relationships with other individuals in different situational contexts. 

 As Peterson (2006) noted, the positive affective factors that are highlighted in positive psychology empower the learners to stifle their negative emotions by capitalizing on their positive feelings. As he noted, among the above-mentioned factors, learners’ Psychological Well-Being (PWB), grit, Emotion Regulation (ER), and Academic Engagement (AE) have received considerable attention in relevant studies.

Oxford (2016) defined learners’ PWB as their satisfaction with their life condition and their academic field of study that results in their improved task performance and attainment in their relevant field. Moreover, Akos and Kretchmar (2017) noted that the learners’ grit encompasses their interest in their field of study and their constant effort to achieve success during the process of their education. Furthermore, Thompson (2008) stated that ER refers to the degree to which learners are able to control and modify their negative emotions in order to effectively perform their academic tasks. Lastly, Jiang and Zhang (2021) pointed out that learners’ AE refers to their whole-person involvement in the academic tasks of their field in their relevant academic setting.

The examination of the relevant studies of higher education learners’ PWB indicates that they have focused on certain research lines to the exclusion of others. More specifically, a group of these studies (e.g., Ryff, 1989; Ryff & Keyes, 1995) have made an attempt to develop valid instruments for assessing the learners’ PWB. Other studies of this affective factor (e.g., Dagenais-Desmarais & Savoie, 2012; Xiyun, 2022) have examined its construct validity. Lastly, a few studies (e.g., Vaknin-Nusbaum & Tuckwiller, 2023) have examined the effect of learners’ PWB on their academic achievement. Nonetheless, the relevant studies have not examined the degree to which the higher education learners’ affective factors including their grit, ER, and AE predict their PWB in different academic fields.

The present study strived to deal with this inadequacy of research in the case of the university learners of English Language and Literature (ELL) and learners of Persian Language and Literature (PLL) in the context of Iran. To this end, it endeavored to answer the following three questions:

1. Do ELL learners’ grit, ER, and AE significantly predict their PWB?
2. Do PLL learners’ grit, ER, and AE significantly predict their PWB?
3. Is there a significant difference between ELL and PLL learners’ PWB?

2. Review of the Related Literature

2.1. PWB

In the field of education, learners’ PWB has attracted more attention in comparison with other affective factors (Garg et al., 2014). According to Oxford (2016), the widespread interest in this construct stems from the fact that it is likely to affect all aspects of higher education learners’ mental health and academic performance. Considering this issue, Oxford (2016) noted that PWB constitutes the essence of positive psychology in the field of education. Likewise, Seligman and Csikszentmihalyi (2000) pointed out that, PWB is the main affective factor in learners’ academic life. They defined this factor as the learners’ satisfaction with their mental and physical health and their academic studies that results in their personal growth.

The significant role of PWB in learners’ academic success has prompted researchers to develop its models in the field of education. In this regard, Ryff (1989) developed a model of PHB that encompasses six major components including autonomy, life purpose, environmental mastery, personal growth, self-acceptance, and positive relations with others. According to him, in this model, autonomy and life purpose respectively refer to the learners’ ability to take responsibility for their academic education and their attitudes toward the main goal of their lives. Moreover, environmental mastery and personal growth respectively indicate the degree to which the learners are comfortable with their academic setting and make an effort to develop effective academic skills. Lastly, self-acceptance and positive relations with others respectively refer to the learners’ development of positive attitudes toward their capabilities and their effort to develop working relationships with other individuals in their academic settings. Considering these sub-constructs, Ryff and Keyes (1995) developed the 18-item scale of PWB which constitutes a valid measure of higher education learners’ PWB. As they noted, PWB may be closely associated with other affective factors including grit, EM, and AE.

2.2. Grit

The examination of the studies of academic achievement (e.g., Vaknin-Nusbaum & Tuckwiller, 2023) indicates that they have focused on the construct of grit as a main predictor of success in different fields of knowledge. Steinmayr et al. (2018) defined grit as the learners’ interest and passion that expedites their goal achievement. Accordingly, they developed a model of grit that encompasses two main sub-constructs including effort consistency and effort perseverance. As they explained, effort consistency refers to the learners’ ability to maintain interest in their field of knowledge despite the relevant academic challenges. Moreover, effort perseverance indicates the degree to which the learners have a tendency to strive to achieve their academic objectives without being negatively influenced by diverse contextual factors that have a negative effect on their academic achievement. Teimouri et al. (2021) developed a 9-item scale of higher education learners’ grit based on Steinmayr et al.’s (2018) grit model. As they noted, grit is likely to be related to learners’ ability to regulate their emotions in academic settings.

2.3. ER

The construct of ER has been a recurrent variable in empirical studies of the field of education in previous decades (Teng & Zhang, 2016). The focus on this affective variable can be ascribed to the fact that it prevents negative affective factors, such as anxiety and stress, from disturbing the process of education in academic settings (Teng & Zhang, 2018). Greenier et al. (2021) pointed out that ER refers to the learners’ behavioral and emotional measures that empower them to control the impact of their negative emotions on their performance. Likewise, Thompson (2008) noted that ER specifies the degree to which learners are able to take advantage of their internal resources in order to capitalize on their positive feelings and to stifle their negative emotions in the context of the classroom. Moreover, Teng and Zhang (2018) noted that learners with higher ER are able to develop and maintain constructive and working relationships with both their peers and professors

Based on these discussions, Gross and John (2003) developed a model of ER that involves two main sub-constructs including cognitive reappraisal and expressive suppression. Furthermore, they developed a 10-item scale that examines these sub-components of ER. As they explained, cognitive reappraisal determines the learners’ ability to modify their perspectives on educational situations by focusing on their positive aspects. Moreover, expressive suppression refers to the learners’ ability to regulate their reflexive emotional reactions, such as their laughter, in a conscious way. They concluded that learners’ ER is likely to influence their perspectives on their academic studies.

2.4. AE   

In academic settings, the learners’ success is deeply influenced by their pedagogical behavior (Reschly & Christenson, 2012). The main aspect of higher education learners’ academic behavior is their AE (Hiver et al., 2021). Jiang and Zhang (2021) defined AE as the learners’ whole-person involvement in their academic tasks. Accordingly, they distinguished three main levels of AE including the cognitive, emotional, and behavioral levels. As they explained, the cognitive domain of learners’ AE refers to their focused attention to their learning tasks that expedites their task performance. Moreover, the emotional aspect of AE determines the degree to which the learners are emotionally attached to their tasks and considers them as consequential aspects of the process of their education. Lastly, the behavioral aspect of AE comprises the learners’ actual pedagogical practices to actively take part in the learning tasks of their classes.

Considering the above-mentioned dimensions of AE, Freda et al. (2023) developed a model of AE that encompasses six underlying sub-components including the sense of belonging, university choice persistence, university value, engagement with professors, engagement with peers, and the university-relational net association. Furthermore, they developed a 29-item scale of AE that focuses on these sub-components. As they explained, in this model, sense of belonging and university choice persistence respectively refer to the learners’ emotional attachment to their academic setting and their satisfaction with their choice of academic setting. Moreover, university value and engagement with professors respectively indicate the learners’ perspectives on the social and academic value of their educational setting and their ability to develop working relationships with their professors. Finally, engagement with peers and the university-relational net association refers to the learners’ capability to establish constructive relationships with their peers and the degree to which their personal relationships with their friends and acquaintances are influenced by their educational setting. Freda et al. (2023) concluded that higher education learners’ AE may be linked to various affective factors.

 Materials and Methods

3.1. Design

In the present study, the researchers used a predictive correlational design to answer the raised research questions of the present study. Creswell and Creswell (2017) pointed out that, this quantitative research design empowers the researchers to determine the extent to which a number of independent or predictor variables are able to predict a specific dependent or criterion variable. Likewise, in the present study, the researchers used Structural Equation Modelling (SEM) to specify the degree to which ELL and PLL learners’ grit, ER, and AE predicted the variance in their PWB.

3.2. Participants

Considering the main objectives, the researchers used convenience sampling to select the English and Persian language learners at a university in Tabriz (Iran). More specifically, first, they contacted the English and Persian language departments at the university, apprised the heads of the departments of the objectives of the study, obtained their consent to the study, and asked them to provide the contact information of the lecturers/professors who taught the courses of ELL and PLL fields. At this point, the researchers were provided with the contact information of 4 Professors of ELL and 3 professors of PLL. Second, they contacted these lecturers/professors, informed them about the aims of the study, and arranged the visit times to their relevant classes. After arranging the visit times, the researchers visited 6 classes of technical courses of ELL (which involved 252 learners) and 5 classes of technical courses of PLL (which encompassed 202 learners), provided their learners with information on the purpose of the study, and invited them to take part in the study. At this point, 31 ELL learners and 24 PLL learners declined to participate in the study due to various reasons such as their busy schedules among others. As a result, 221 ELL learners (i.e. 98 male and 123 female) and 178 PLL learners (i.e. 83 male and 95 female) constituted the main participants of the study. The researchers assured the participants of their anonymity and data confidentiality and obtained written informed consent from them prior to the onset of the data collection.

3.3. Instrumentation

The following instruments were employed to gather the data:

3.3.1. PWB Scale

Considering the main objectives, the researchers utilized Ryff and Keyes’s (1995) PWB scale to examine ELL and PLL learners’ PWB.  This self-report scale encompassed 18 items that were rated on a five-point scale ranging from strongly agree to strongly disagree. They focused on six main aspects of PWB including autonomy, life purpose, environmental mastery, personal growth, self-acceptance, and positive relations with others. The English and Persian versions of this scale were respectively administered to the ELL and PLL learners. The results of Cronbach’s alpha reliability analysis indicated that the reliability indices of its English and Persian versions were respectively .84 and .81 and they could be used in the present study.

3.3.2. Grit Scale 

To examine the learners’ grit, the researchers used Teimouri et al.’s (2021) grit scale. This questionnaire involved 9 Likert-scale items that focused on two main aspects of grit including effort consistency and effort perseverance and were rated on a five-point scale ranging from strongly agree to strongly disagree. The English version and Persian version of this scale were respectively administered to ELL and PLL learners. Based on the results of Cronbach’s alpha reliability analyses, the reliability indices of English and Persian versions of this scale were .89 and .85 respectively. Therefore, they were used in the present study.

3.3.3. ER Scale

 In the present study, the researchers employed Gross and John’s (2003) ER scale to assess the participants’ ER. This scale encompassed 10 Likert-scale items that were rated on a seven-point scale ranging from strangle agree to strongly disagree. The relevant items examined two main aspects of ER including cognitive reappraisal and expressive suppression. Cronbach’s alpha reliability analyses showed that the reliability indices of the English and Persian versions of this questionnaire were respectively .84 and .79. Consequently, the English version and the Persian version were respectively administered to the ELL and PLL learners.

3.3.4. AE Scale 

In order to examine the ELL and PLL learners’ AE, the researchers used Freda et al.’s (2023) AE scale. This instrument comprised 29 Likert-scale items that were rated on a five-point scale ranging from strongly agree to strongly disagree. These items examined six main sub-constructs of AE including the sense of belonging, university choice persistence, university value, engagement with professors, engagement with peers, and the university-relational net association. Based on the results of Cronbach’s alpha reliability analyses, the reliability of the English version (.87) and Persian version (.80) of this instrument was satisfactory and they were administered to ELL and PLL learners respectively.

3.4. Procedure

In the present study, first, the researchers used convenience sampling in order to select 221 ELL learners and 178 PLL learners from among the ELL and PLL learners of a university in Tabriz (Iran) as the participants. Second, they obtained written informed consent from all of the participants and ensured the anonymity and confidentiality of their data. Moreover, the researchers informed them of their capability to withdraw from the study at any point of its data collection. Third, the researchers used Google Forms to administer the English version of Ryff and Keyes’s (1995) PWB scale, Teimouri et al.’s (2021) grit scale, Gross and John’s (2003) ER scale, and Freda et al.’s (2023) AE scale to the ELL learners in a two-week period of time (i.e. two instruments per week). Moreover, they administered the Persian versions of all of these scales to the PLL learners using Google Forms in the same period of time. Lastly, the researchers utilized SPSS 25 and Amos 24 to perform the data analysis of the study.

3.5. Data Analysis

The present study strived to determine the degree to which ELL and PLL learners’ grit, ER, and AE predicted the variance in their PWB. Considering this objective, the researchers used SEM to examine the linear causal relationships between the sub-components of ELL and PLL learners’ grit, ER, AE, and their PWB and to control the accompanying measurement errors of the relevant correlation analyses. Moreover, the study intended to determine the significant difference between ELL and PLL learners’ PWB. Accordingly, the researchers used Welch’s independent-samples t-test (due to unequal sample sizes) to examine the difference between the PWB of these groups of learners.     

 Results

The first research question of the study focused on the role of ELL learners’ grit, ER, and AE in the prediction of their PWB. Considering this objective, the researchers used SEM analysis to develop the model of the interrelationships among these participants’ affective variables. Figure 1 shows the relevant model for the ELL learners:

 Figure 1. Model of ELL Learners’ PWB

In order to determine the degree to which ELL learners’ grit, ER, and AE significantly predicted their PWB, the researchers examined the regression weights of these variables. Table 1 provides these results:

Table 1. Regression Weights of ELL Learners’ Grit, ER, and AE

As shown in Table 1, ELL learners’ grit, ER, and AE were significant predictors of their PWB (C.R.>1.96; p<.05). As a result, the researchers examined the standardized estimates to determine the most significant predictor of their PWB. Table 2 shows these results:

Table 2. Standardized Estimates of ELL Learners’ Grit, ER, and AE

As shown in Table 2, ELL learners’ AE (.386), ER (.373), and grit (.261) were respectively the first, the second, and the third most significant predictors of their PWB. Considering these results, the researchers examined the model fit. Table 3 provides these results:

 Table 3. Model Fit Summary of ELL Leaners’ PWB

As shown in Table 3, the model fit of ELL learners’ PWB was satisfactory (p>.05; CMIN<3).  As a result, the researchers examined the baseline comparisons of this model to ensure its fit. Table 4 provides these results:

Table 4. Baseline Comparisons of ELL Leaners’ PWB Model

According to Table 4, ELL learners’ PWB model fit was acceptable (IFI>9; TLI>9; and CFI>9).

The second research question of the study focused on the role of PLL learners’ grit, ER, and AE in the prediction of their PWB. Based on the aim of this question, the researchers used SEM to develop the model of these learners’ PWB. Figure 2 shows these results:

Figure 2. Model of PLL Learners’ PWB

 To determine the degree to which PLL learners’ grit, ER, and AE significantly predicted their PWB, the researchers examined the regression weights of these variables. Table 5 provides these results:

Table 5. Regression Weights of PLL Learners’ Grit, ER, and AE

As shown in Table 5, PLL learners’ grit and AE were significant predictors of their PWB (CR>1.96; p<.05). As a result, the researchers scrutinized the standardized estimates to determine the most significant predictor of their PWB. Table 6 provides these results

Table 6. Standardized Estimates of PLL Learners’ Grit and AE

As shown in Table 6, PLL learners’ AE (.441), and grit (.363) were respectively the first, and the second most significant predictors of their PWB. Considering these results, the researchers examined the model fit. Table 7 provides these results:

Table 7. Model Fit Summary of PLL Leaners’ PWB

As shown in Table 7, the model fit of PLL learners’ PWB was satisfactory (p>.05; CMIN<3).  Therefore, the researchers examined the baseline comparisons of this model to ensure its fit. Table 8 provides these results:

Table 8. Baseline Comparisons of PLL Leaners’ PWB Model

According to Table 8, PLL learners’ PWB model fit was acceptable (IFI>9; TLI>9; and CFI>9).

The third research question tried to examine the difference between ELL and PLL learners’ PWB. Consequently, the researchers compared ELL and PLL learners’ PWB. Table 9 shows the descriptive statistics on these participants’ PWB.

Table 9. Descriptive Statistics on ELL and PLL Learners’ PWB

The researchers used Welch’s independent-samples t-test (due to unequal sample sizes) to examine the significance of the group mean values. Table 10 provides these results:

Table 10. Welch’s t-test of ELL and PLL Learners’ PWB

As shown in Tables 9 and 10, the difference between the mean values of the ELL group and the PLL group was statistically significant (M = 72.43, SD = 9.151), t (221) = 6.050, p = .000.). Figure 3 depicts these results:

Figure 3. ELL and PLL Learners’ PWB

 Discussion

In this study, question one examined the degree to which ELL learners’ grit, ER, and AE significantly predicted their PWB. The obtained results showed that all of the above-mentioned affective factors were significant predictors of ELL learners’ PWB. In general, these results, corroborate the results of the studies that were carried out by Eskreis-Winkler et al. (2014), Wolters and Hussain (2015), Steinmayr et al. (2018), Vazsonyi et al. (2019), Khajavy et al. (2020), Şenkal Ertürk et al. (2020), Singh et al. (2020), Wenzel et al. (2020), Derakhshan (2021), Hiver et al. (2021), Jiang and Zhang (2021), Khajavy (2021), Mystkowska-Wiertelak  (2021), Tang et al. (2021), Ghafouri and Tahriri (2023), and Hiver and Wu (2023). These studies reported that language learners’ higher levels of grit, ER, and AE were significantly correlated with their PWB in different academic settings.

Pate et al. (2017) pointed out that learners’ higher grit levels may improve their PWB. They explained that learners’ PWB is greatly influenced by the specification of their academic objectives, self-acceptance, and belief in their capabilities. Moreover, as they noted, learners with higher grit are very passionate and develop and implement plans to achieve their long-term objectives in their academic settings. According to Pate et al. (2017), these discussions show that the learners’ higher grit may ameliorate their perspectives on their self-worth and is likely to improve their confidence. Moreover, Greenier et al. (2021) noted that learners’ ER might ameliorate their PWB due to the fact that it reduces the impact of negative emotions on their academic performance. They explained that the learners with high ER are able to capitalize on their positive emotions in order to stifle their negative feelings in their academic settings. As a result, they develop mastery over their environment and effectively deal with academic challenges. Lastly, Reschly and Christenson (2012) averred that learners’ AE improves their PWB since it enables them to develop harmonious relationships with other individuals in academic settings. As they pointed out, the learners’ higher levels of AE empower them to engage with both their professors and peers and to take advantage of the benefits of their constructive relationships with these individuals in the process of their education.

These discussions highlight the fact that the ELL learners’ grit, ER, and AE constituted significant predictors of their PWB since they prompted these learners to develop long-term goals and follow them passionately. Moreover, they helped the learners to achieve mastery over their academic setting by capitalizing on their positive emotions. Finally, they helped the ELL learners to develop working relationships with their peers and professors in the academic setting of the university.

Question two tried to determine the extent to which PLL learners’ grit, ER, and AE significantly predicted their PWB. Based on the results, while these learners’ grit and AE were significant predictors of their PWB, their ER did not significantly predict the variance in their PWB.  In general, these results are in line with the results of the studies that were conducted by Ivcevic and Brackett (2014), Sturman and Zappala-Piemme (2017), Alan et al. (2019), Clark and Malecki (2019), Jiang et al. (2019), Hiver et al. (2020), Park et al. (2020), Sağkal et al. (2020), Dewaele and Li (2021), and Kuruveettissery et al. (2021).

Tang et al. (2019) argued that the learners’ higher grit results in their prolonged interest in their academic studies and prompts them to strive to effectively perform their academic tasks. As they noted, learners’ satisfactory task performance further increases their interest in their field, ameliorates their self-confidence, and results in their personal growth. They pointed out that, the learners’ self-confidence improves their autonomy and ameliorates their PWB. Furthermore, Jiang and Zhang (2021) stated that the learners’ AE intensifies their sense of belonging to their academic setting and ameliorates their perspectives on their university studies. They stated that these issues positively affect the learners’ self-acceptance and improve their PWB. 

Considering these discussions, it can be stated that, in the present study, PLL learners’ PWB was significantly predicted by their grit and AE since these factors increased their interest in their academic field, improved their sense of belonging to their academic setting, and ameliorated their perspectives on their academic studies.

Lastly, question three focused on the difference between ELL and PLL learners’ PWB. The results indicated that ELL learners’ PWB was significantly higher than PLL learners’ PWB. In general, these results underpin the results of the studies that were conducted by Seligman and Csikszentmihalyi (2000), and Garg et al. (2014). These studies reported that learners’ PWB was influenced by diverse learner internal resources and contextual factors in different academic settings.

Seligman (2011) noted that, in academic settings, learners’ PWB is greatly influenced by their perspectives on the academic and social value of their field of study. Likewise, Proietti Ergün and Dewaele (2021) noted that the learners’ opinions about the occupation-related opportunities that are provided to them due to their academic field are likely to have a noticeable effect on their PWB.

Consequently, ELL learners’ higher PWB can be ascribed to their positive perspectives on the academic and social value of their field of study and the occupation-related opportunities that were provided to them by this academic field.

6. Conclusion

The results of the present study showed that ELL and PLL learners’ affective factors including their grit, ER, and AE significantly predicted the variance in their PWB. These results may have practical implications in the field of education. First, the results show that there is a need to redress the process of lecturer/professor education in the settings of universities. The examination of the selection criteria of the academic board members in different universities in Iran shows that they mainly focus on applicants’ technical knowledge of their field and disregard their knowledge of learner factors (e.g., grit, ER, and AE) that are likely to affect their PWB. Therefore, it is necessary to provide lecturers/professors in different fields with education on positive psychology learner factors in order to empower them to deal with the learners’ psychological problems in a more satisfactory way.

Second, the results indicated that the syllabus designers need to develop a lecturer/professor manual that apprises the lecturers/professors in various university academic fields with sufficient knowledge of the learners’ affective factors including their grit, ER, AE, and PWB. This kind of manual can enable university professors to specify the main stress-inducing factors that have a negative effect on their learners’ PWB and can help them to effectively deal with the stressors and improve their learners’ PWB.

Lastly, based on the results, it can be argued that lecturers/professors in different academic fields have to obtain adequate information on learners’ affective variables (e.g., grit) using different sources such as the recent empirical studies of positive psychology factors in education (e.g., the present study) and various textbooks on learners’ affective factors. Furthermore, they can form various peer groups on social media applications to take advantage of their peers’ feedback and guidance on the ways of dealing with the sources of stress and anxiety in their classes.

The present study had a number of limitations since the researchers were not able to examine the effect of the learners’ age and gender on the obtained results. Furthermore, they could not collect qualitative data on participants’ perspectives on the factors in their PWB using qualitative data collection techniques such as semi-structured interviews among others. Moreover, they delimited the study by focusing on ELL and PLL learners as the participants and examining their grit, EM, and AE without dealing with the other positive psychology variables (e.g., resilience). Future studies need to deal with these limitations and delimitations. In addition, these studies have to utilize mixed-methods designs to provide a deeper insight into the factors that influence university learners’ PWB. Lastly, these studies have to examine the degree to which university learners’ PWB influences their academic performance in their academic settings.

 Funding: The authors did not receive financial support from any organization for the submitted article.