Exploring the Interplay of Motivation, International Posture, and Online Informal English Learning: A Mixed-Methods Study

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Nevertheless, not all learners actively participate in OILE, missing out on its established benefits for acquiring language proficiency in an enjoyable manner (Cole & Vanderplank, 2016;Kuppens, 2010;Kusyk, 2017;Kusyk & Sockett, 2012;Sundqvist & Wikström, 2015).Research by Al-noori and Hindi (2022), Cole and Vanderplank (2016), Kusyk (2017), Wei (2022) and Mills (2018) has affirmed that learners' motivation towards language learning significantly influences their engagement in informal language learning.Furthermore, Mills (2018) has proposed that learners' perception of their Ideal L2 self and their global perspective, often referred to as International Posture, can dictate the extent of their engagement with informal language learning.Given these findings, it is reasonable to assert that students may either embrace OILE or overlook the opportunity to leverage it based on their motivation for language learning and their global perspective.This study aims to investigate the connection between students' motivation, their international posture and their level of engagement with online informal English learning.

Literature Review
In this research, the L2 Motivational Self System theory will serve as the theoretical framework to explore students' motivation to learn English in the Saudi Arabian context.This theory posits three primary sources of motivation for language learners: firstly, an intrinsic drive rooted in their envisioned future selves (referred to as the Ideal L2 self); secondly, motivation stemming from external pressures or societal obligations (termed the Ought-to L2 self); and thirdly, motivation arising from the actual language learning experience (referred to as the L2 learning experience) (Dörnyei, 2009).
Additionally, the concept of International Posture (IP) plays a crucial role in understanding motivation (Yashima, 2002(Yashima, , 2009;;Yashima, Zenuk-Nishide, & Shimizu, 2004).IP encompasses various elements such as an interest in global or international matters, a willingness to travel or work abroad, a readiness to engage with individuals from diverse cultures, and ideally, an open and non-ethnocentric attitude towards different cultures (Yashima, 2002, p. 57).Yashima (2002) underscores the significance of IP, particularly in contexts where daily interactions with native English speakers are limited, as it provides a broader and more inclusive perspective beyond specific L2 language groups.In this regard, IP does not exclusively target a particular English-speaking community but rather considers the entire international English-speaking community as its focus.Lamb (2004) noted that many learners perceive learning English as a means to expand their horizons and gain insights into diverse cultures.

Motivation and International Posture
Numerous L2 motivational studies, specifically those within the L2 Motivational Self System (L2MSS) research domain, have delved into the impact of International Posture (IP) on various L2MSS components (Csizér & Kormos, 2009a;Islam, 2013;Kong et al., 2018;Kormos & Csizér, 2008;Munezane, 2013;Papi et al., 2019;Yashima, 2009).In a study by Yashima (2009), the relationship between the Ideal L2 self and IP was explored, revealing a noteworthy connection.Yashima pointed out that individuals exhibiting a higher level of international posture and more frequent cross-cultural communication tend to strongly identify with their ideal selves (Yashima, 2009, p. 159).
Building upon this idea, Aubrey and Nowlan (2013) hypothesized that the Ideal L2 self is an integral part of IP, drawing from Yashima's (2009) argument that IP essentially mirrors the potential future selves of English users in international communities (Yashima, 2009).
Moreover, Kormos and Csizér (2008) delved into the variations in the motivation of Hungarian learners, examining factors such as age (i.e., secondary-school students, university students, adult learners) and their attitudes toward English as a global language.Their research found that International Posture and the experiences of L2 learners significantly contributed to the construction of the Ideal L2 self.The Ought-to L2 self was excluded from their study due to its low reliability.Notably, Kormos and Csizér (2008) highlighted that IP played a role in motivating adult students exclusively and that it emerged as the most robust predictor of the Ideal L2 self across all age groups.Furthermore, Csizér and Kormos (2009a), who initially postulated that both the Ideal L2 self and the Ought-to L2 self would be influenced by IP, discovered that their results supported a connection between IP and only the Ideal L2 self.They also found that the L2 learning experience had an impact on IP, which, in turn, influenced the formation of the Ideal L2 self.Similarly, Taylan (2017) identified a significant contribution of IP to Turkish learners' Ideal L2 selves.Kormos et al. (2011) unveiled the impact of IP on the Ideal L2 self, while the L2 learning experience influenced IP.Lamb (2012) reinforced these findings, demonstrating that IP played a role in motivating learners.Furthermore, Lamb (2012) noted that urban learners exhibited higher levels of IP compared to their counterparts in rural areas.In separate studies, Munezane (2013) and Islam et al. (2013) explored the L2 Motivational Self System and its relationship with IP, both concluding that IP served as a predictor of the Ideal L2 self.

Online Informal Learning of English
According to research by Lee and Dressman (2018) and Lyrigkou (2019), the field of online informal learning of English (OILE) is still in its early stages.Sockett (2014) distinguished between formal learning, non-formal learning, and informal learning.Formal learning, as defined, is structured education provided by academic institutions that lead to certification.Non-formal learning, on the other hand, is structured but not provided by educational institutions and doesn't result in certification.Informal learning, the focus here, is associated with daily life activities for entertainment or communication with family and friends.It is unstructured, often unintentional, and less formalized.
This study concentrates on online informal learning of English and adopts the acronym introduced by Sockett (2014), 'online informal learning of English' (OILE).As described by Toffoli and Sockett (2015), OILE is primarily a communication-driven process, with language learning being a by-product of this communication.Kusyk (2017) defines OILE as a field of research aimed at investigating non-native English learners' engagement with online informal learning.Tan, Ng, and Saw (2010) conducted an exploratory study on Malaysian school students' online English engagement and discovered that 77% of their internet usage is in English.Toffoli and Sockett (2010) studied French students' online English habits, revealing that 90% of the students listen to English online monthly, and 50% do so weekly.Additionally, 25% read English online weekly, primarily through social networks.Jarvis (2014) examined Thai university students' use of technology and social media in different languages, with English being the predominant choice, even for students with varying proficiency levels.Kusyk (2017) investigated German and French students' informal online engagement with English and found that L2 development in the online context is complex and non-linear, with a greater focus on receptive skills than productive skills.The researcher also highlighted potential variables affecting learners' OILE activities, such as aptitude and motivation.Trinder (2017) studied Austrian intermediate to advanced university students' informal English learning habits and their use of new media outside the classroom, revealing that 40% of respondents regularly engage with new media in English, with 72% expressing an intention to improve their English through OILE. Lee and Dressman (2018) conducted a mixed-methods study involving 94 Korean students, differentiating between meaning-focused and form-focused OILE activities.They found that students engaged more in meaning-focused activities, such as reading English news, and that a combination of both types positively impacted their language proficiency.Students also frequently watched videos and listened to music.Jurkovič (2019) explored the online informal English learning habits of Slovenian undergraduate students using smartphones, finding a preference for receptive tasks over productive ones.The study suggested that higher self-reported communicative competence in English led to increased English use online and vice versa.

Motivation and OILE
As previously mentioned, the field of OILE is still in its early stages (Lee & Dressman, 2018;Lyrigkou, 2019).Consequently, there is a limited body of research discussing the application of technology in language learning with regards to students' motivation.Notable exceptions include studies conducted by Adolphs et al. (2018), Gleason and Suvorov (2012), Lamb and Arisandy (2019), Little andAl Wahaibi (2017), andMcCarty (2009).
In their evaluation of Computer-Assisted Language Learning (CALL) studies and motivation theories, Bodnar et al. (2016) emphasized the significant influence of a learner's motivational experience during practice on their actual practice behavior and eventual learning outcomes.They stressed the need for comprehensive assessments of students' motivation in CALL system evaluations.Bodnar et al. (2016) specifically recommended the use of the L2 Motivational Self System (L2MSS), as it is grounded in motivational psychology, widely recognized in Second Language Acquisition (SLA) studies, and adaptable to various educational contexts.The L2MSS framework conceptualizes motivation as an internal process related to personal aspirations, notably the "Ideal L2 self," making it particularly suitable for CALL applications.
Several studies have delved into learners' motivation and their engagement in online practice.McCarty (2009) encouraged students to use social networking apps like Maxi voluntarily to foster integrative motivation by bridging the gap between students and teachers.Gleason and Suvorov (2012) employed the L2 Motivational Self System to investigate adult learners' perceptions of how computer-mediated technology, specifically Wimb Voice (WV), could shape their L2 selves.Their mixed-methods study, comprising questionnaires and interviews, revealed a spectrum of perspectives, indicating that individual differences played a substantial role in the findings.
Little and Al Wahaibi (2017) explored learners' motivation to participate in social media platforms, examining the relationship between autonomy, identity, and motivation.They found that students' Ideal L2 selves were intertwined with their national and religious interests, as they felt responsible for correcting misconceptions about their religion.Moreover, students' ambitious English language goals appeared to be linked with their cultural and religious affiliations.
Lamb and Arisandy (2019) carried out a mixed-methods study with Indonesian university students learning English through OILE.They investigated students' OILE usage habits and their connection to L2 motivation, particularly in the context of the L2 Motivational Self System.The study also explored how OILE use influenced students' perceptions of in-class learning.The findings showed a positive correlation between students' OILE habits and their Ideal L2 selves, although not with the Ought-to L2 selves.Additionally, the study did not find a significant impact of students' engagement with OILE on their attitudes toward traditional classroom learning.

International Posture and OILE
Limited research has explored the relationship between International Posture (IP) and informal learning.In a study conducted by Mills (2018) involving Japanese university students, the L2 Motivational Self System (L2MSS) served as the theoretical framework to examine learners' motivation.The study incorporated two key components: the Ideal L2 self and the Ought-to L2 self.Mills (2018) discovered that the students exhibited a positive International Posture, but they displayed little interest in global news.Additionally, the students engaged in various informal language learning activities.Notably, a positive correlation emerged between the students' Ideal L2 self and IP concerning informal learning.However, no such correlation was found between the Ought-to L2 self and informal learning.The study highlighted how learners' desire to be part of an international community drove them to participate more actively in informal language learning.Furthermore, Yashima and her colleagues (Yashima & Zenuk-Nishide, 2008;Yashima et al., 2004) conducted studies that explored the relationship between IP and activities outside the classroom.For instance, Yashima et al. (2004) examined IP in connection with English communication frequency both inside and outside the classroom, using items like "I talked with friends or acquaintances outside school in English."The results suggested that a positive IP contributes to more communicative behavior.
It is essential to note the complex nature of the relationship between motivation and the use of OILE, as well as the connection between IP and OILE use or informal learning in general.In fact, establishing causality is a challenging task.Existing literature suggests two potential directions: technology may impact learners' motivation and self-concept (as seen in studies by Adolphs et al., 2018;Gleason & Suvorov, 2012;Lamb & Arisandy, 2019), or learners' motivation and self-concept can influence their utilization of technology (as noted in studies by Cole & Vanderplank, 2016;Kusyk, 2017;Mills, 2018).The studies mentioned previously were exploratory in nature, making it difficult to infer causality from them.Adolphs et al. (2018) and Lamb and Arisandy (2019) acknowledged the potential positive impact of recent technological advancements on language motivation, while recognizing the challenge of determining causality in exploratory studies that primarily rely on correlational analyses.Stockwell (2013) posited that the relationship between technology and motivation could work in both directions, with learners who extensively use technology potentially displaying higher motivation to learn English in our globally connected digital world, and vice versa.Al-Shehri (2009) and Dörnyei (2009) suggested that the clearer a learner's vision of their L2 self, the more motivated they will be to enhance their English proficiency, which can be facilitated through engagement with new media.Mills (2018) contended that IP and the Ideal L2 self contribute to learners' informal learning, albeit relying solely on correlation analyses.As previously emphasized, correlation does not imply causation.Nonetheless, there is some evidence (e.g., Cole & Vanderplank, 2016;Kusyk, 2017;Mills, 2018) indicating that motivation and IP may lead to increased engagement with OILE.

Research Methodology
This mixed-methods study used questionnaire followed by purposeful sampling for the semi-structured interviews based on participants' motivational and IP profiles.The aim of the study is to answer the following research questions: 1) What are students OILE habits?
2) What is the relationship between students' motivation, IP and their OILE habits?

Questionnaire
The questionnaire had three parts (motivation, International Posture and OILE habits).
The first part is the motivation section, and it contains three subsections: Ideal L2 self (10 items): This is the image the learner forms about a proficient language speaker that he or she aspires to achieve.This construct is considered the core of Dörnyei's (2005Dörnyei's ( , 2009) L2 Motivational Self System theory.The variable aims to measure students' future image of themselves as language learners.
Example: I can imagine myself as someone who is able to speak English.
Ought-to L2 self (10 items): This is the image the learner feels obligated to meet, and this image is usually instilled by others.The variable aims to assess the role of different others (parents, teachers, friends and significant others) in learners' motivation to learn English.It could also refer to life obligations and external pressures.Ought-to L2 self scale was found to have several limitations in previous studies (Lamb, 2012).Hence, in this study, I adapted Taguchi et al. (2009) questionnaire where "all the statements included the pronouns "I" or "me" and so made explicit reference to the subjects' own self" (Lamb, 2012(Lamb, , p. 1007)).In Dörnyei's (2009) L2 Motivational Self System model and the scale used by Taguchi et al. (2009), there was no differentiation between the others, as in some items the others were teachers or parents etc.Hence, all possible others (friends/parents/teachers/other people) were included in every item related to Ought-to L2 self to clarify and provide the students with several examples of what "others" means.
Example: I study English because my friends/parents/teachers/other people think it is important.
L2 learning experience (6 items): This variable aims to measure the learners' attitude towards the immediate learning context, and the whole experience of learning English.The scale did not include any item evaluating teachers, as learners might feel uncomfortable evaluating their teachers in the presence of those teachers.
Example: I like the atmosphere of my English class.
The second section contains 10 items related to International Posture which means learners' openness towards the world, their tendency to be part of the international community and to be interested in what is happening in the world, and their willingness to communicate with different others (Yashima, 2002).
Example: I often watch news about foreign countries.
The third section related to OILE frequency which refers to learners' habits of using English in an informal environment, and the items included different skills practised by learner's online.Most items were adapted from the literature.
Example: I talk online in English using voice services.

Semi Structure Interviews
Interviews are the most common instrument in qualitative data collection in various disciplines including applied linguistics (Dörnyei, 2007).This study employed semi-structured interviews.One main advantage of this type of interview is that it is pre-planned so the researcher can follow the interview guide while having the opportunity to expand further on any topic (Dörnyei, 2007).The interview guide used in this study contains three main sections: learners' general experience of learning English, learners' motivation (L2MSS); the nature of learners' International Posture; and learners' OILE habits.The interview guide was designed by the researchers based on the literature ( Islam ,2013;Zeng,2015).To select interviewees, the scores for each scale (e.g., Ideal L2 self, Ought-to L2 self and International Posture) were computed in SPSS.Then, to calculate the length of the category for a five-point Likert scale, the following law was used: Degrees of freedom of the item's responses (5-1)/ Levels of answer= Length of category (5-1) /5] = (0.8) (1) Hence, the score of the respondents' answers ranged as follows: Strongly Disagree Disagree Neutral Agree Strongly Agree Less than 1.8 1.8-2.6 2.6-3.4 3.4-4.24.2-5 Then the three main dispositions were classified as follows:

Variable Low Neutral High
Ideal L2 Self 1 to 2.6 2.6 to 3.4 3.4 to 5

International Posture
Any participant who scored 2.6 was considered as having a low profile, any participant who scored between 2.6 to 3.4 was considered as having a neutral profile and any participant who scored higher than 3.4 was identified as having a high profile.The aim was to interview two participants from the three dispositions for each variable.The non-OILE users were also interviewed to get a deeper understanding of their avoidance of using English when online.After following the previously mentioned criteria, two participants were chosen from each disposition, except for the "Low Ideal L2 self" where only one participant was found, who was also a non-English user of online activities.It is important to note that a participant might have various profiles towards each variable, such as a high or low profile for all variables.In short, 19 participants were chosen, and each participant had a different profile with regard to the other variables.Two non-English users of online activities were chosen regardless of their profiles.

Factor Analysis
After collecting data from a total of 550 students, the information was transferred from Qualtrics to SPSS (Version 28).The next step was to verify that the items on the scales were indeed measuring the same underlying concepts, as suggested by Cohen et al. (2011).This validation process involved conducting an exploratory factor analysis (EFA), a statistical method aimed at identifying clusters of items and condensing the data into a more manageable form.
Initially, the analysis revealed the presence of 14 extracted factors with eigenvalues exceeding 1.00, accounting for a total variation of 61.31%.Subsequently, additional rotations were carried out, and items with low factor loadings (values below 0.4) were removed to enhance the quality of the scales, following the guidelines of Pallant (2016).Furthermore, any factor containing only one item loading was excluded from consideration.The final results of this rigorous analysis identified five factors with satisfactory eigenvalues (eigenvalues surpassing 1.00), encompassing roughly 60% of the total variance (specifically, 59.54%).In summary, this investigation confirmed that all the scales used in this study represented distinct constructs.
This section reports the results of internal consistency which shows if the items of the scale are measuring the same underlying construct (Pallant, 2016).Normally for a 10-item scale the reliability score should not be less than (0.8).Dörnyei (2007) explained that in applied linguistics and language research it is unlikely to have long scales as researchers usually test various constructs at the same time, which is also the case in this study.Therefore, Dörnyei (2007) suggested that Cronbach's alpha should not be less than (.07).However, Pallant (2016) andCohen et al. (2011) highlighted that a reliability of (0.6) could also be acceptable in the field of social science for short scales.The table below provides the Cronbach's alpha value for each scale along with the mean inter-item correlations.

Students OILE Habits
The aggregated score for the items of frequency of OILE was M = 2.12, SD = 1.01 which might suggest that the use of OILE was below moderate as it is less than three in a five-point scale.As depicted in Table 2 above, the mean values indicate that the students, on the whole, did not exhibit significant involvement in OILE activities.Additionally, the table provides information on the frequency and percentage of student responses for each scale.Notably, the results reveal that a mere 10% of students practiced these activities on a daily basis, while over 50% reported that they never participated in some of the OILE activities.
To simplify the categorization of OILE use, I have adopted a methodology consistent with the recommendations of Jeong (2016) and Norman (2010).These scholars advocate for collapsing lengthy Likert scales into a more straightforward scale during the analysis phase of the study.They argue that dichotomizing or trichotomizing Likert scales is a reliable approach for streamlining interpretation.Consequently, in order to classify the means as either high or low for each item, the length of the 5-point Likert scale was computed as follows: Degrees of the freedom for the Likert scale/Levels of the answer = Length of category (5 -1) / 5 = 0.80 (1) Subsequently, number one, which is the least value in the scale, was added to identify the maximum number of this category.Thus, the category would be as follows: • From 1 to 1.80 represents (almost never) • From 1.81 to 2.60 represents a week) • From 2.61 to 3.40 represents (several times a week) • From 3.41 to 4.20 represents (once a day) • From 4.21 to 5 represents (several times a day) Later on, the use of these activities was classified as follows: Low use Moderate use High use 1 to 2.6 2.6 to 3.4 3.4 to 5 From this, it appears that students typically engage less in certain activities like extensive online English chatting, email writing, voice chatting, or online English reading.They exhibit moderate usage of online communication through social networks and text messages.Notably, high usage in any of the OILE activities is not commonly observed.In summary, students generally fall within the low to moderate usage range, with prevalent OILE activities revolving around quick text messaging and socializing on social networks.Activities requiring a higher level of English proficiency, such as online writing or reading, remain limited, with approximately 64% of the sample reporting no experience in writing emails in English and around 50% indicating no experience in reading lengthy English documents online.

The Relationship Between IP and the Components of L2MSS
This section explores the connection between IP and L2MSS components.Despite the third component (L2 learning experience) being environment-derived, it was considered due to its link to learners' positive experiences in learning English and their openness towards the world (IP) according to Aubrey and Nowlan (2013).In the study, Ideal L2 self and International Posture showed a weak positive correlation (r = .237,p < .007),as did International Posture with Ought-to L2 self (r = .199,p < .007)and L2 learning experience (r = .273,p < .007).Although positively correlated, the strength of these correlations is considered weak.The bivariate Pearson correlations overall indicate positive associations between International Posture and all L2MSS components, but with weak strength.
Moving on to the relationship between OILE frequency and L2MSS components and IP, students' OILE use positively correlated with all L2MSS components and International Posture.Notably, Ideal L2 self and OILE frequency (r = .356,p < .007),frequency of OILE and L2 learning experience (r = .347,p < .007),and frequency of OILE and IP (r = .331,p < .007)showed positive and moderate correlations.However, Ought-to L2 self had a positive and weak correlation with OILE frequency (r = .140,p < .007).
Examining correlation coefficients, Ideal L2 self positively correlated with IP (r1 = .237),and IP positively correlated with L2 learning experience (r2 = .273),both with weak effect sizes.The correlation between Ideal L2 self and L2 learning experiences (r3 = .526)was strong.Comparing these correlations using an online calculator resulted in Z = -0.902,p = 0.184, indicating no statistically significant difference.Additionally, comparing L2 learning experience and IP with Ought-to self and IP revealed a significantly stronger correlation between L2 learning experience and IP (Z = 3.194, p = .001).Notably, comparisons between IP and Ought-to L2 self or Ideal L2 self were not made due to the non-significant correlation between Ideal L2 self and Ought-to L2 self.
Stepwise multiple regression analysis was also conducted to further investigate this relationship, with the results presented in the following table.This final model consists of three variables (i.e., Ideal L2 self, IP and L2 Learning experience).Together these predictors explain 47% of the variance in learner's frequency of OILE, R 2 = .47,F(3,451) = 41.55,p = .000.As it can be seen from the table above, Ideal L2 self contributes to OILE and uniquely explains around 3% of the variance in frequency of OILE.In other words, R 2 would decrease by 3.92% if the Ideal L2 self were removed from the model.Similarly, the scale of IP contributes to the frequency of OILE and explains 5% of the variance in OILE frequency.Then L2 learning experience contributes to OILE frequency and explains 3.53 of the variance.The effect size of this multiple regression was calculated manually as f 2 (.47/1-.47)= .89.According to Cohen (1988) this is considered a large effect size.

What Are Students OILE Habits?
As previously discussed in the literature section, there is no established norm in published research for assessing the level of OILE habits (Jurkovič, 2019).Dichotomisation and trichotomisation were employed to categorize the Likert scale measuring the frequency of OILE into high, moderate, and low users.Overall, the results indicated that students were not high users of OILE activities, being instead moderate users of social media for short posts and online chatting in English.
Contrary to some previous studies suggesting high OILE engagement among learners, this study revealed that female Saudi university students, as a cohort, are not high OILE users.The qualitative data complemented this by uncovering that students engage in both receptive and productive tasks online, such as watching videos, voice chatting, and writing posts on social media.
A limitation of the OILE frequency scale is its focus on productive tasks, excluding items related to receptive tasks due to low factor analysis loading.However, qualitative data revealed that students engage in both types of activities, contrary to previous suggestions that learners predominantly indulge in receptive OILE habits.The mixed-methods approach in this study efficiently captured students' OILE habits, enriching understanding beyond quantitative findings.
The qualitative data delved into various OILE activities, including social media use, watching YouTube videos, and TV viewing.Voice chatting via the Cambly app, internet surfing in English, online games, and instant text messages were also reported.Surprisingly, few students listened to English music, and activities requiring high English proficiency, such as reading online articles or writing in English, were infrequent.In summary, the qualitative findings provided a detailed exploration of OILE activities, identifying high OILE users and offering a nuanced perspective that enriched the overall understanding of students' online engagement.

What Is the Relationship Between Students' Motivation, IP and OILE Habits?
The quantitative findings revealed a moderate positive correlation between the frequency of OILE habits and both Ideal L2 self and the L2 learning experience.Comparing the correlation coefficients using Fisher's Z-transformation showed no statistically significant differences between the associations of OILE frequency with Ideal L2 self and with L2 learning experiences.This aligns with Lamb and Arisandy's (2019) study on Indonesian university students, suggesting a potential bidirectional relationship where high Ideal L2 selves may drive OILE engagement or vice versa.Caution is warranted regarding the circular argument that motivation leads to OILE use and vice versa.Cohen et al. (2011) emphasized the potential for statistical analysis and qualitative data to shed light on causation and directionality.
Ideal L2 self contributed to OILE frequency, explaining 3% of the unique variance in the outcome.Qualitative data affirmed this relationship, with interviewees expressing a conscious effort to align their online engagement with their envisioned Ideal L2 selves.Metacognitive thinking and correction of grammar errors before posting online were reported by high Ideal L2 self learners, supporting findings by Lai and Gu (2011) and Ekşi and Aydin (2013) regarding higher metacognitive engagement in technology-assisted language learning.Even if students disliked the classroom environment, the influence of their Ideal L2 selves motivated them to engage in OILE use, reinforcing the quantitative finding that Ideal L2 self was the sole predictor of OILE use among L2MSS components.
Contrary to expectations, Ought-to L2 self showed only a weak correlation with OILE frequency, in line with Lamb and Arisandy (2019) and Mills (2018).The weak correlation may suggest that learners perceiving English learning as an external obligation still engage in OILE or vice versa.In contrast, the Ideal L2 self and L2 learning experiences exhibited a stronger correlation with OILE frequency.
Quantitative data indicated a positive and moderate correlation between International Posture (IP) and OILE frequency.The regression analysis demonstrated that IP contributed to OILE frequency, explaining 1% of the unique variance.Qualitative data reinforced this, revealing that higher IP was associated with increased engagement in OILE.This supports Mill's (2018) finding of a positive correlation between IP and informal language learning.The literature suggests that IP is linked to more communicative behavior, and based on the study's findings, learners with higher IP seek more OILE opportunities, potentially viewing it as a means to be part of a broader international community.

Conclusion
The sample, representing female Saudi university students from a specific university, may not be applicable to students in private universities with different backgrounds.Gender-specific aspects, particularly in International Posture (IP) and Online Informal Language Learning (OILE), could vary, as indicated in previous studies.The study contributes to L2 motivation literature by connecting learners' motivation to OILE, aligning with the call for using L2 Motivational Self System (L2MSS) as a theoretical framework in technology-based language learning research.The findings highlight the role of Ideal L2 self in influencing increased OILE use, supporting recent literature.
Exploring learners' IP is a unique aspect of this study within the context of Saudi Arabia and Eastern cultures, shedding light on a relatively low-to-moderate level of IP among female Saudi students.The association between IP and learners' motivation, specifically Ideal L2 self, is confirmed.The use of mixed-methods research enhances the study's methodological contribution, providing a comprehensive understanding of learners' motivation, IP, and OILE use.

Table 1 .
Reliability analysis of the constructs

Table 1 .
Table (2) below presents the descriptive statistics for each item on the OILE frequency scale: mean values, standard deviations and the percentage and frequency of the responses.Descriptive Statistics for the frequency of OILE items( Mean, Standard Deviation)

Table 2 .
Stepwise Multiple Regression Analysis based on OILE as a predictor