Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 368 Online version available in : http://arbitrer.fib.unand.ac.id | 2339-1162 (Print) | 2550-1011 (Online) | JURNAL ARBITRER Submission Track A B S T R A C T Received: May 23, 2025 Final Revision: August 30, 2025 Accepted: September 02, 2025 Available Online: September 25, 2025 This study examines the impact of gender and academic levels on using both traditional and AI-integrated learning strategies among EFL Omani students. This quantitative study utilized a questionnaire with a five- point Likert scale based on Oxford’s Strategy Inventory for Language Learning (SILL) and other AI-related items adapted from current studies, including 152 students from a public Omani university. The research instrument was expert-reviewed, followed by a pilot study, and the main data were analyzed using SPSS, namely t-tests and ANOVA. Out of 35 question items related to traditional learning strategies, Omani female learners outperformed male students in 26 items, significantly in writing new words (F= 4.00, M= 3.63), online English classes (F= 3.36, M= 2.99), practice grammar (F= 3.56, M= 3.01), and learn pronunciation (F= 4.44, M= 3.78). Similarly, Omani female learners outperformed male learners in all nine AI-based strategies, namely AI tools to enhance speaking (F= 3.44, M= 3.15), learn pronunciation (F= 3.54, M= 3.19), and improve writing (F= 3.43, M= 3.25). Students’ academic levels also affected some strategies like listening, speaking, and pronunciation; higher-level students preferred interactive approaches related to AI compared with lower-level students. However, AI tools for learning grammar and writing were less commonly used. These findings suggest that integrating traditional and AI- assisted strategies could support learning foreign languages. Consequently, educators should encourage active engagement in AI-based learning while addressing students’ dependence on traditional strategies. Keywords Language learning strategies, AI, gender, academic levels, Omani students Correspondence *E-mail: nayef.jomaa@utas.edu.om Article Traditional Strategies and AI-Integrated Strategies in Learning English among EFL Omani Students Nayef Jomaa1*, Badri Abdulhakim Mudhsh2, Khalid AlGhafri3 1-3Preparatory Studies Center, University of Technology and Applied Sciences-Salalah, Dhofar, Sultanate of Oman Under License of Creative Commons Attribution-Non Commercial 4.0 International.DOI: https://doi.org/10.25077/ar.12.3.368-382.2025 I. INTRODUCTION Learning English could be achieved through language learning strategies (Jomaa, Attamimi, & AlGhafri, 2025b; Oxford, 1990; Rahimi & Katal, 2012). In this regard, various factors can affect these strategies, such as gender, proficiency levels, and areas of studying (Šafranj, 2013; Tamimi & Razeq, 2020). Higher-achieving students utilize more strategies, namely metacognitive ones, in comparison with lower-achieving students (Jomaa et al., 2025b; Santihastuti & Wahjuningsih, 2019). However, though some studies have suggested that gender significantly influences these strategies (Zeynali, 2012; Montero-SaizAja, 2021), others, such as Behforouz and Al Ghaithi (2022), have found no relationship. Similarly, studies that have examined the influence of age and levels of study have yielded contrasting results (Rahimi & Katal, 2012; Jomaa, Attamimi, & Al Mahri, 2024). For instance, some studies have revealed that the level of proficiency affects the use of strategies; in other words, highly proficient learners prefer metacognitive and cognitive strategies (Ping & Luan, 2017; Park, 1997), whereas other studies argue that external factors, including teaching methods and motivation, have a decisive role in language learning (Ghafournia, 2014; Jomaa, Attamimi, & Al Mahri, 2025a; Tahriri & Divsar, 2011). These inconsistencies in the results imply a need for more examinations among EFL Arab students, particularly in Omani public universities, to obtain further insights into their LLSs (Alrashidi, Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 369 2022; Tamimi & Razeq, 2020). In Oman, English is learned as a third language after acquiring various Omani local languages, followed by Arabic, and then English (Alkathiri, Jomaa, Mudhsh, Al Saqr, & Ali, 2025). Investigating these strategies could enable teachers, educators, and university management to adopt more effective teaching methods and policies as well as enhance students’ learning experiences (Mahayanti, Putro, Widodo, & Alonzo, 2022; Susanto, 2022). In this complicated process, multiple issues have been shown to influence using LLSs and their possible effectiveness, including age, gender, proficiency levels, and the possible influence of artificial intelligence (AI) (Al-Raimi et al., 2024; Al-Saiari et al., 2024; Jomaa et al., 2024, 2025a, 2025b). For instance, younger learners tend to be more proficient due to greater brain plasticity (Dey et al., 2024), whereas older learners may face more challenges but often exhibit higher motivation (Chen, 2014; Dey et al., 2024). In other words, different age groups prefer distinct strategies, with compensation strategies being more common among older students (Sepasdar & Soori, 2014; Chen, 2014). Social and affective strategies are also frequently used by university students (Sepasdar & Soori, 2014; Chen, 2014). Additionally, the relationship between LLSs and course grades is stronger in younger students (Tragant & Victori, 2012). Cognitive strategy use increases with age, whereas social and contextual strategy use decreases (Riazi et al., 2005). Other influencing factors include the nature of tasks, course methodology, and parental support (Suesca Torres & Torres Pérez, 2017). These findings underscore the need for age-specific language teaching methods (Dey et al., 2024; Tanjung, 2018). Further, research on gender differences in LLSs use has yielded mixed results (Alhaysony, 2017; Aliakbari & Hayatzadeh, 2008; Zeynali, 2012; Montero-SaizAja, 2021). The most commonly used strategies among both genders are cognitive, metacognitive, and compensation strategies (Alhaysony, 2017; Ariyani et al., 2018). Although some studies have found gender differences in strategy use, others have not found such differences (Kashefian-Naeeini & Maarof, 2016; Tahriri & Divsar, 2011). Furthermore, the proficiency level affects strategy use, with more successful learners employing strategies more frequently (Green & Oxford, 1995). Research has also shown a positive correlation between LLSs use and productive vocabulary acquisition (Montero-SaizAja, 2021). Despite these findings, strategy use among learners typically ranges from low to medium (Alhaysony, 2017). Overall, learners across different studies have been found to be medium strategy users, with metacognitive strategies being the most frequently employed (Tahriri & Divsar, 2011). These inconsistencies highlight the need for further research into how gender influences LLSs use in different learning contexts. The level of study also significantly impacts LLSs use. To demonstrate, higher proficiency learners tend to employ more cognitive, metacognitive, and social strategies (Khosravi, 2012; Ghafournia, 2014; Sulthan et al., 2018), with metacognitive strategies being particularly favored by advanced learners (Sulthan et al., 2018; Rahimi et al., 2008). Additionally, the year of study plays a role, as first-year students use more metacognitive and indirect strategies (Kashefian-Naeeini & Maarof, 2016), whereas seniors employ a broader range of strategies (Alrashidi, 2022; Sedighi & Zarafshan, 2006). Motivation also influences strategy use, with integrative motivated students utilizing more strategies (Sedighi & Zarafshan, 2006; Rahimi et al., 2008). However, in their study, Jomaa, Attamimi, and AlGhafri (2025b) revealed that levels of study have no effect on VLSs among Omani EFL students. The integration of AI in language learning has introduced new dimensions to LLSs use (Lavidas et al., 2024). That is, learning languages is no longer associated only with the classroom as it was in the past. Nowadays, learners can use varied applications and AI tools to learn any language at any time outside the classroom. More specifically, recent studies have indicated that AI tools are commonly used for vocabulary learning strategies (Al-Raimi et al., 2024; Jomaa et al., 2024, 2025a). The most frequently used AI-based strategy is translating the meaning of new words, followed by acquiring new vocabulary, translating entire sentences, and mastering pronunciation (Jomaa, Attamimi, & Al Mahri, 2024). However, strategies related to grammar learning, writing, and reading skills are less frequently used. This suggests that while AI is beneficial in some areas, its role in overall language acquisition strategies requires further exploration. Additionally, Jomaa et al. (2024) found that age, gender, and levels of study Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 370 do not significantly affect EFL Omani students’ use of AI tools for English vocabulary learning. These findings highlight the growing influence of AI in language education and suggest a need for further research to maximize its potential in improving LLSs use. These insights emphasize the significance of modified education approaches to improve foreign language learning. Therefore, this study aims to address two research questions: 1. What are the perspectives of EFL Omani students on using both traditional and AI- integrated methods in learning the English language? 2. To what extent do gender and levels of study affect the use of traditional methods and AI-integrated methods in learning English among EFL Omani students? II. METHODS This study adopted a quantitative research design to gain an efficient understanding of the language learning strategies employed by EFL Omani students in learning English in the Omani context. This approach facilitates the systematic collection and analysis of numerical data. The questionnaire consists of 44 items adopted from the Strategy Inventory for Language Learning (SILL) established by Oxford (1990), which is a widely recognized instrument in language learning research. More specifically, items from 1 to 35 were adopted from the SILL, since they are related to traditional methods of learning English. Meanwhile, items from 36 to 44 were recently developed based on the results of several studies (Jomaa, Attamimi, & Al Mahri, 2024; Al-Raimi, Mudhsh, Al-Yafaei, Al-Maashani, 2024) to measure AI-integrated language learning strategies, thus revealing emerging trends related to the possible effect of artificial intelligence on foreign language learning. The research instrument was expert-reviewed, followed by a pilot study. To effectively gauge students’ responses, the questionnaire employed a five-point Likert scale: 1 = Never, 2 = Seldom, 3 = Sometimes, 4 = Often, and 5 = Always. This scale provided a structured framework to measure the frequency and extent of strategy use among the respondents. Respondents The survey was randomly disseminated online through Google Forms to EFL Omani students enrolled in the General Foundation Program (GFP) at the Preparatory Studies Center of a public university in Oman. Out of 500 students, a total of 153 students completed the questionnaire, and after a validation process, 152 responses were deemed suitable for the analysis. The respondents exhibited diversity in terms of gender (72 male students, 80 female students) and proficiency levels (Level One: 30, Level Two: 29, Level Three: 36, Level Four: 57). Table 1. Number of respondents based on gender and levels of study Category Number of students Gender Male 72 Female 80 Level of study Level one 30 Level two 29 Level three 36 Level four 57 Total 152 The respondents were enrolled in one of four levels (Levels 1 to 4), each corresponding to an academic semester lasting four months. Upon university admission, students undertook an English Placement Test, which determined whether they needed to enroll in the Foundation Program and at which level they should begin. The majority of the respondents fell within the 17-21 age range, with only one student classified within the 22-26 age category; therefore, this student was excluded from the sampling, since age is a significant variable, and respondents with different ages may use varied strategies. Data Analysis The collected data were analyzed using SPSS version 26, ensuring accuracy and precision in statistical assessment. The internal consistency of the questionnaire was evaluated using Cronbach’s Alpha, yielding a high-reliability score of 0.949, thereby signifying excellent reliability. Key statistical measures, such as means, standard deviations, frequencies, and the highest and lowest mean values, were reported to summarize students’ responses. Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 371 This analysis examines the differences and similarities between male and female students in their use of traditional methods in learning English. Concerning writing and vocabulary strategies, female students are significantly more likely to write new English words in a notebook (Mean: 4.29 vs. 3.96, p = 0.044). Both genders frequently translate new words into their native language, with little difference (Mean: 4.33 for females, 4.25 for males). However, females are slightly more inclined to use new English words in sentences (Mean: 3.75 vs. 3.40). Regarding grammar and practice exercises, females engage significantly more in grammar exercises (Mean: 3.56 vs. 3.01, p = 0.002). They also follow online English lessons for grammar more frequently (Mean: 3.36 vs. 2.99). Further, the use of mental visualization for remembering grammar rules is slightly more common among females (Mean: 3.40 vs. 3.14). As for listening and pronunciation practices, female students listen to word pronunciations using Google Translate at a significantly higher rate than male students (Mean: 4.44 vs. 3.78). Listening to English texts to learn grammar is also slightly more frequent among females (Mean: 3.48 vs. 3.15). Both genders exhibit a similar tendency to listen to English songs (Mean: 3.23 for females, 3.03 for males) and watch movies or TV shows in English (Mean: 3.74 for females, 3.81 for males). Regarding Table 2. Reliability statistics of the main study Reliability Statistics Cronbach’s Alpha Cronbach’s Alpha Based on Standardized Items No of Items .949 .949 44 Inferential statistical analyses were conducted, including two types of tests. First, an Independent Sample t-test was conducted to examine potential differences in English learning strategies based on gender. Second, a One-way ANOVA was performed to assess the potential impact of students’ academic level (four levels were examined) on their choice of English learning strategies. III. RESULTS In Table 3, the effect of gender on using traditional methods of learning English is illustrated. Overall, female learners consistently outperformed male students in most English learning strategies, particularly in grammar practice, writing, and structured study habits. The largest gender variations were in employing Google Translate for pronunciation, grammar exercises, and maintaining study schedules; all of which were favored by female students. In contrast, male learners showed only slight advantages in a few areas (e.g., watching movies, group discussions, chatting with people), but the differences were minimal. Table 3. The effect of gender on traditional methods of English language learning Question items Gender N Mean Std. Deviation Std. Error Mean 1- Use new English words in a sentence. Male 72 3.40 .914 .108 Female 80 3.75 .948 .106 2- Write the new words on paper or in a notebook. Male 72 3.96 1.067 .126 Female 80 4.29 .903 .101 3- Repeat the new words to myself. Male 72 3.54 .978 .115 Female 80 3.66 .967 .108 4- Translate the new words into my native language. Male 72 4.25 .946 .111 Female 80 4.33 .978 .109 5- Follow online English lessons to learn grammar. Male 72 2.99 1.216 .143 Female 80 3.36 1.022 .114 6- Visualize mental images to remember grammar rules. Male 72 3.14 1.202 .142 Female 80 3.40 1.109 .124 7- Observe my mistakes and use the information to improve. Male 72 3.82 1.053 .124 Female 80 3.98 1.043 .117 8- Practice grammar exercises. Male 72 3.01 1.028 .121 Female 80 3.56 1.089 .122 9- Read English texts to learn grammar. Male 72 3.18 1.142 .135 Female 80 3.39 1.119 .125 10- Listen to English texts to learn grammar. Male 72 3.15 1.134 .134 Female 80 3.48 1.211 .135 11- Listen to word pronunciations on Google Translate. Male 72 3.78 .982 .116 Female 80 4.44 .898 .100 Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 372 12- Try to speak with native English speakers. Male 72 3.36 1.271 .150 Female 80 3.50 1.091 .122 13- Practice pronunciation with English speakers or other learners. Male 72 3.35 1.140 .134 Female 80 3.29 1.127 .126 14- Read newspapers, stories, or books in English. Male 72 2.58 1.110 .131 Female 80 2.78 1.113 .124 15- Read for enjoyment in English. Male 72 2.82 1.226 .144 Female 80 3.05 1.301 .146 16- Skim the English text quickly first, then reread it carefully. Male 72 3.43 1.243 .146 Female 80 3.61 1.288 .144 17- Focus on main headings and subheadings in English texts. Male 72 3.54 1.138 .134 Female 80 3.53 1.169 .131 18- Listen to English songs. Male 72 3.03 1.529 .180 Female 80 3.23 1.501 .168 19- Watch movies or TV shows in English. Male 72 3.81 1.182 .139 Female 80 3.74 1.199 .134 20- Pay attention to people speaking English. Male 72 3.90 .981 .116 Female 80 4.03 1.006 .112 21- Chat with people online in English. Male 72 2.92 1.230 .145 Female 80 2.78 1.158 .129 22- Discuss English learning materials and information with others. Male 72 3.28 1.141 .134 Female 80 3.11 1.125 .126 23- Participate in group discussions in English. Male 72 3.10 1.153 .136 Female 80 3.00 1.114 .125 24- Write essays and short stories in English in my free time. Male 72 2.43 1.254 .148 Female 80 2.05 1.113 .124 25- Write notes, text messages, and reports in English. Male 72 2.74 1.175 .138 Female 80 2.93 1.123 .126 26- Write simple, uncomplicated words in meaningful sentences. Male 72 3.63 1.080 .127 Female 80 4.00 1.091 .122 27- Try to finish English homework before the deadline. Male 72 4.04 1.131 .133 Female 80 4.26 .990 .111 28- Set a specific study schedule for exams. Male 72 3.68 1.287 .152 Female 80 4.03 1.091 .122 29- Try various methods for studying English. Male 72 3.82 .954 .112 Female 80 3.89 1.031 .115 30- Maintain a balance between my life and learning English. Male 72 3.63 1.027 .121 Female 80 3.65 1.092 .122 31- Motivate myself with positive self-talk. Male 72 4.03 1.138 .134 Female 80 4.13 1.036 .116 32- Seek help from experienced individuals to correct my English mistakes. Male 72 4.01 1.028 .121 Female 80 4.04 1.061 .119 33- Record my progress in learning English in a notebook. Male 72 3.24 1.369 .161 Female 80 3.23 1.312 .147 34- Compare my English learning progress with my prior knowledge. Male 72 3.56 1.099 .130 Female 80 3.55 1.157 .129 35- Evaluate myself through tests. Male 72 3.65 1.115 .131 Female 80 3.75 1.185 .133 speaking and interaction strategies, both genders show comparable engagement in speaking with native English speakers (Mean: 3.50 for females, 3.36 for males). They also practice pronunciation with peers at nearly the same level (Mean: 3.29 for females, 3.35 for males). Further, participating in group discussions in English is equally common (Mean: 3.00 for females, 3.10 for males). As for reading and writing practices, females are slightly more engaged in reading for enjoyment in English (Mean: 3.05 vs. 2.82 for males). Further, both genders read newspapers, stories, or books in English at a similar rate (Mean: 2.78 for females, 2.58 for males). However, writing essays and short stories in free time is more common among males, but this difference is not statistically significant (Mean: 2.43 vs. 2.05, p = 0.053). Other strategies related to study habits and self- Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 373 regulation showed both variations and similarities. To demonstrate, female students tend to set a study schedule for exams more frequently than males (Mean: 4.03 vs. 3.68), though this difference is not statistically significant (p = 0.076). Both genders show similar levels of motivation through positive self-talk (Mean: 4.13 for females, 4.03 for males). Besides, comparing English learning progress with prior knowledge is almost identical across genders (Mean: 3.55 for females, 3.56 for males). Keeping track of learning progress in a notebook is also equally common (Mean: 3.23 for both). These results show that female students are more likely to engage in structured learning methods, such as writing new words in a notebook, practicing grammar exercises, and using pronunciation tools (p-values < 0.05). In contrast, male students show slightly higher engagement in freewriting activities, but the difference is not significant. This insight can help educators tailor teaching methods to accommodate different learning preferences. Female students have a slightly higher mean score (3.5639) than male students (3.4222) in using traditional methods. However, the difference is small, and standard deviations are similar, indicating some overlap in behavior. The F-value is 1.917, and the p-value (Sig.) is 0.168, which is greater than 0.05. This indicates no statistically significant difference between male and female students in their use of traditional learning methods. In Table 4, the effect of gender on AI-integrated language learning strategies is explained. The data reveal that both male and female students use AI applications for learning English, with mean scores generally ranging between 3.13 and 3.88 on a 5-point scale. This suggests that AI is moderately utilized in language learning but has not yet become the dominant approach. While students engage with AI across different language skills, their usage varies based on specific learning needs. A notable trend is the slight gender difference in AI usage, with female students consistently reporting higher mean scores than male students across all categories. The most significant differences appear in AI use for strengthening speaking skills (Male: 3.15, Female: 3.44) and enhancing pronunciation accuracy (Male: 3.19, Female: 3.54). This suggests that female learners may be more inclined to use AI for oral communication and pronunciation improvement, possibly indicating greater confidence or willingness to engage with technology for interactive language learning. When examining the most and least used AI applications, the data show that AI for translating new words is the most widely adopted strategy (Male: 3.85, Female: 3.88). This suggests that learners primarily use AI as a translation tool rather than for productive language skills like writing or speaking. Conversely, AI for learning grammar had the lowest mean scores (Male: 3.13, Female: 3.24), implying that students may still prefer traditional grammar-learning methods over AI-based tools, possibly due to the structured nature of grammar Table 4. The effect of gender on AI-integrated language learning strategies Questionnaire items Gender N Mean Std. Deviation Std. Error Mean 36- Use language AI applications to learn English. Male 72 3.26 1.332 .157 Female 80 3.43 1.357 .152 37- Use AI applications to acquire new vocabulary. Male 72 3.40 1.296 .153 Female 80 3.55 1.292 .144 38- Use language AI applications to improve writing skills. Male 72 3.25 1.264 .149 Female 80 3.43 1.290 .144 39- Use language AI applications to strengthen speaking skills. Male 72 3.15 1.218 .144 Female 80 3.44 1.221 .136 40- Use language AI applications to enhance reading skills. Male 72 3.21 1.321 .156 Female 80 3.31 1.279 .143 41- Use language AI applications to improve listening skills. Male 72 3.36 1.259 .148 Female 80 3.38 1.226 .137 42- Use language AI applications to learn English grammar. Male 72 3.13 1.310 .154 Female 80 3.24 1.324 .148 43- Use language AI applications to enhance pronunciation accuracy. Male 72 3.19 1.263 .149 Female 80 3.54 1.242 .139 44- Use language AI applications to translate the meanings of new words. Male 72 3.85 1.218 .144 Female 80 3.88 1.335 .149 Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 374 instruction. Looking at AI usage across different language skills, the findings indicate that AI applications are well-used for vocabulary learning (Male: 3.40, Female: 3.55), showing that students find AI helpful in expanding their word bank. AI- assisted writing improvement is also moderately used (Male: 3.25, Female: 3.43), suggesting that while students turn to AI for writing support, it is not their primary resource. In contrast, AI use for reading (Male: 3.21, Female: 3.31) and listening (Male: 3.36, Female: 3.38) suggests a moderate reliance on AI for comprehension-based skills. The analysis of results shows that the significance (Sig.) values for all the variables are above 0.05, indicating no statistically significant differences between genders in the use of AI applications for learning English. The eta squared values, which measure the strength of association, are all quite low (ranging from 0.000 to 0.019). This suggests that gender explains little to no variation in AI usage patterns. Since all p-values (Sig.) exceed 0.05, there is no statistically significant gender- based difference in AI-assisted English learning. Table 5. The effect of the level of study on traditional methods of learning English Sum of Squares df Mean Square F Sig. 1- Use new English words in a sentence. Between Groups (Combined) 4.004 3 1.335 1.509 .215 Within Groups 130.884 148 .884 Total 134.888 151 2- Write the new words on paper or in a notebook. Between Groups (Combined) 7.800 3 2.600 2.718 .047 Within Groups 141.569 148 .957 Total 149.368 151 3- Repeat the new words to myself. Between Groups (Combined) 8.193 3 2.731 3.014 .032 Within Groups 134.123 148 .906 Total 142.316 151 4- Translate the new words into my native language. Between Groups (Combined) .433 3 .144 .154 .927 Within Groups 138.830 148 .938 Total 139.263 151 5- Follow online English lessons to learn grammar. Between Groups (Combined) 4.008 3 1.336 1.047 .374 Within Groups 188.834 148 1.276 Total 192.842 151 6- Visualize mental images to remember grammar rules. Between Groups (Combined) 4.405 3 1.468 1.098 .352 Within Groups 197.990 148 1.338 Total 202.395 151 7- Observe my mistakes and use the information to improve. Between Groups (Combined) 6.178 3 2.059 1.913 .130 Within Groups 159.341 148 1.077 Total 165.520 151 8- Practice grammar exercises. Between Groups (Combined) 4.602 3 1.534 1.294 .279 Within Groups 175.477 148 1.186 Total 180.079 151 9- Read English texts to learn grammar. Between Groups (Combined) 4.606 3 1.535 1.205 .310 Within Groups 188.657 148 1.275 Total 193.263 151 Table 5 reveals the effect of levels of study on learning English following the traditional methods. This analysis examines the traditional methods of learning English among EFL Omani students across four academic levels (Level 1, Level 2, Level 3, and Level 4) using an ANOVA test. The key findings are grouped into several categories based on their strategy. First, regarding writing and memorization strategies, using new words in a sentence based on the ANOVA result show F(3,148) = 1.509, p = .215, indicating no statistically significant difference across levels. Writing new words in a notebook: F(3,148) = 2.718, p = .047 suggests a significant difference among levels, meaning that students at different levels vary in their tendency to write new words for memorization. Repeating new words to oneself resulted in F(3,148) = 3.014, p = .032, indicating a significant difference, whereby higher-level students might use this method more effectively than lower-level ones. While writing down words is significantly different across levels, repetition also shows a difference, suggesting that higher-level Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 375 10- Listen to English texts to learn grammar. Between Groups (Combined) 17.147 3 5.716 4.359 .006 Within Groups 194.056 148 1.311 Total 211.204 151 11- Listen to word pronunciations on Google Translate. Between Groups (Combined) 1.438 3 .479 .482 .695 Within Groups 147.187 148 .995 Total 148.625 151 12- Try to speak with native English speakers. Between Groups (Combined) 16.132 3 5.377 4.119 .008 Within Groups 193.210 148 1.305 Total 209.342 151 13- Practice pronunciation with English speakers or other learners. Between Groups (Combined) 12.158 3 4.053 3.319 .022 Within Groups 180.684 148 1.221 Total 192.842 151 14- Read newspapers, stories, or books in English. Between Groups (Combined) 3.248 3 1.083 .873 .457 Within Groups 183.594 148 1.241 Total 186.842 151 15- Read for enjoyment in English. Between Groups (Combined) 6.600 3 2.200 1.381 .251 Within Groups 235.867 148 1.594 Total 242.467 151 16- Skim the English text quickly first, then reread it carefully. Between Groups (Combined) 9.629 3 3.210 2.045 .110 Within Groups 232.266 148 1.569 Total 241.895 151 17- Focus on main headings and subheadings in English texts. Between Groups (Combined) 4.229 3 1.410 1.067 .365 Within Groups 195.606 148 1.322 Total 199.836 151 18- Listen to English songs. Between Groups (Combined) 24.938 3 8.313 3.840 .011 Within Groups 320.430 148 2.165 Total 345.368 151 19- Watch movies or TV shows in English. Between Groups (Combined) 12.505 3 4.168 3.078 .029 Within Groups 200.436 148 1.354 Total 212.941 151 20- Pay attention to people speaking English. Between Groups (Combined) 4.496 3 1.499 1.537 .207 Within Groups 144.340 148 .975 Total 148.836 151 21- Chat with people online in English. Between Groups (Combined) 4.463 3 1.488 1.050 .373 Within Groups 209.748 148 1.417 Total 214.211 151 22- Discuss English learning materials and information with others. Between Groups (Combined) 1.920 3 .640 .494 .687 Within Groups 191.547 148 1.294 Total 193.467 151 23- Participate in group discussions in English. Between Groups (Combined) 11.201 3 3.734 3.045 .031 Within Groups 181.476 148 1.226 Total 192.678 151 24- Write essays and short stories in English in my free time. Between Groups (Combined) 6.597 3 2.199 1.562 .201 Within Groups 208.344 148 1.408 Total 214.941 151 25- Write notes, text messages, and reports in English. Between Groups (Combined) 3.781 3 1.260 .956 .415 Within Groups 195.107 148 1.318 Total 198.888 151 26- Write simple, uncomplicated words in meaningful sentences. Between Groups (Combined) 8.494 3 2.831 2.412 .069 Within Groups 173.710 148 1.174 Total 182.204 151 27- Try to finish English homework before the deadline. Between Groups (Combined) 7.306 3 2.435 2.212 .089 Within Groups 162.905 148 1.101 Total 170.211 151 28- Set a specific study schedule for exams. Between Groups (Combined) 7.326 3 2.442 1.731 .163 Within Groups 208.773 148 1.411 Total 216.099 151 Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 376 29- Try various methods for studying English. Between Groups (Combined) 4.369 3 1.456 1.492 .219 Within Groups 144.447 148 .976 Total 148.816 151 30- Maintain a balance between my life and learning English. Between Groups (Combined) 4.931 3 1.644 1.482 .222 Within Groups 164.168 148 1.109 Total 169.099 151 31- Motivate myself with positive self-talk. Between Groups (Combined) 7.095 3 2.365 2.059 .108 Within Groups 169.958 148 1.148 Total 177.053 151 32- Seek help from experienced individuals to correct my English mistakes. Between Groups (Combined) 3.305 3 1.102 1.015 .388 Within Groups 160.590 148 1.085 Total 163.895 151 33- Record my progress in learning English in a notebook. Between Groups (Combined) 3.647 3 1.216 .678 .567 Within Groups 265.294 148 1.793 Total 268.941 151 34- Compare my English learning progress with my prior knowledge. Between Groups (Combined) 3.575 3 1.192 .938 .424 Within Groups 188.004 148 1.270 Total 191.579 151 35- Evaluate myself through tests. Between Groups (Combined) 7.988 3 2.663 2.056 .109 Within Groups 191.689 148 1.295 Total 199.678 151 students rely more on these strategies compared to beginners. Lower-level students may not be as disciplined in noting new words, while advanced students might integrate writing and repetition more effectively. Second, translating new words into the native language: F (3,148) = 0.154, p = .927, indicates no significant difference across levels. This suggests that translation remains a common method among all levels, implying that EFL Omani students continue relying on their native language to support their English learning regardless of proficiency. Third, grammar learning strategies following online English grammar lessons showed F(3,148) = 1.047, p = .374, which is not significant. Visualizing mental images for grammar rules: F(3,148) = 1.098, p = .352 is also not significant. Similarly, observing mistakes for improvement: F(3,148) = 1.913, p = .130 and practicing grammar exercises: F(3,148) = 1.294, p = .279 are not significant. In general, no significant differences were found across levels, suggesting that students at all levels use similar grammar learning methods. This may indicate a lack of differentiation in how grammar is taught or studied, implying that grammar learning remains uniform across academic progression. Fourth, concerning reading and listening strategies, listening to English texts to learn grammar: F(3,148) = 4.359, p = .006 is significant. Though reading English texts for grammar: F(3,148) = 1.205, p = .310 is not significant, listening to English songs: F(3,148) = 3.840, p = .011, and watching movies or TV shows in English: F(3,148) = 3.078, p = .029 are significant. It can be reported that listening-based strategies are significantly different across levels, suggesting that higher-level students engage with these activities more frequently than beginners. In contrast, reading strategies did not show significant differences, which may suggest that reading habits are more stable across different levels of study. Fifth, speaking and pronunciation strategies showed significant differences. More specifically, speaking with native speakers: F(3,148) = 4.119, p = .008, practicing pronunciation with others: F(3,148) = 3.319, p = .022, and participating in group discussions: F(3,148) = 3.045, p = .031 are significant. This can reveal that speaking and pronunciation-related strategies show significant differences across levels, suggesting that higher- level students engage in active communication more frequently than lower-level students. This may indicate that confidence and proficiency increase with level progression, leading students to seek more interaction with native and fluent speakers. The dataset examines whether the level of study significantly affects traditional methods of learning English. The analysis is based on ANOVA, with statistical significance (p-values) and effect sizes (Eta Squared) examined. Statistically Significant Differences (p < 0.05) were found in the following traditional methods of learning English among Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 377 EFL Omani students; writing new words on paper (p = 0.047), repeating new words to oneself (p = 0.032), listening to English texts to learn grammar (p = 0.006), speaking with native English speakers (p = 0.008), practicing pronunciation with others (p = 0.022), listening to English songs (p = 0.011), watching movies or TV shows in participating in group discussions (p = 0.031). These results indicate that the level of study significantly affects the use of these traditional methods. In contrast, most of the other traditional methods, including translating words, reading English texts, following online lessons, and using grammar exercises, showed no significant differences across levels of study. However, the largest Effect Size (Eta Squared) were found in the following traditional methods of learning English by EFL Omani students: listening to English texts to learn grammar (0.081), speaking with native speakers (0.077), listening to English songs (0.072), practicing pronunciation (0.063), watching movies/TV shows (0.059), and group discussions (0.058). These indicate moderate effects, meaning the level of study plays a meaningful role in these learning behaviors. In Table 6, the dataset provides mean scores across four study levels for various AI-integrated English learning activities among EFL Omani students. The mean scores of general AI use in learning English range from 3.11 (Level Three) to 3.49 (Level Four), suggesting that higher-level students use AI applications slightly more, but the differences are small. Concerning vocabulary learning, Level Two (3.69) and Level Four (3.56) students report higher AI use, whereas Level Three students show the lowest (3.17). As for writing skills improvement, Level Two students (3.62) use AI more, whereas Level Three students report the least (2.89). Regarding speaking skills strengthening, Levels One, Two, and Four have similar usage (around 3.30–3.53), whereas Level Three is the lowest (2.89). However, in reading and listening skills enhancement, minor variations exist, with means ranging from 3.06 to 3.45. Regarding grammar learning and pronunciation accuracy, Levels Two and Four students show slightly higher means than other levels. The strategy related to the translation of new words showed that the highest usage is observed in Level One (4.17), decreasing slightly in higher levels. It could be concluded that the means suggest that AI-integrated methods are used across all study levels, but there is no clear Table 6. The effect of the level of study on AI-integrated language learning strategies Descriptives NO Mean St. Dev. St. Error Lower Bound Upper Bound 36- Use language AI applications to learn English. Level 1 30 3.43 1.406 .257 2.91 3.96 Level 2 29 3.28 1.437 .267 2.73 3.82 Level 3 36 3.11 1.304 .217 2.67 3.55 Level 4 57 3.49 1.297 .172 3.15 3.84 Total 152 3.35 1.343 .109 3.13 3.56 37- Use AI applications to acquire new vocabulary. Level 1 30 3.50 1.358 .248 2.99 4.01 Level 2 29 3.69 1.168 .217 3.25 4.13 Level 3 36 3.17 1.444 .241 2.68 3.66 Level 4 57 3.56 1.210 .160 3.24 3.88 Total 152 3.48 1.292 .105 3.27 3.69 38- Use language AI applications to improve writing skills. Level 1 30 3.30 1.368 .250 2.79 3.81 Level 2 29 3.62 1.293 .240 3.13 4.11 Level 3 36 2.89 1.282 .214 2.46 3.32 Level 4 57 3.51 1.167 .155 3.20 3.82 Total 152 3.34 1.277 .104 3.14 3.55 39- Use language AI applications to strengthen speaking skills. Level 1 30 3.30 1.236 .226 2.84 3.76 Level 2 29 3.38 1.293 .240 2.89 3.87 Level 3 36 2.89 1.214 .202 2.48 3.30 Level 4 57 3.53 1.151 .152 3.22 3.83 Total 152 3.30 1.224 .099 3.11 3.50 Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 378 40- Use language AI applications to enhance reading skills. Level 1 30 3.17 1.234 .225 2.71 3.63 Level 2 29 3.45 1.298 .241 2.95 3.94 Level 3 36 3.06 1.308 .218 2.61 3.50 Level 4 57 3.35 1.329 .176 3.00 3.70 Total 152 3.26 1.296 .105 3.06 3.47 41- Use language AI applications to improve listening skills. Level 1 30 3.17 1.117 .204 2.75 3.58 Level 2 29 3.66 1.317 .245 3.15 4.16 Level 3 36 3.22 1.312 .219 2.78 3.67 Level 4 57 3.42 1.209 .160 3.10 3.74 Total 152 3.37 1.238 .100 3.17 3.57 42- Use language AI applications to learn English grammar. Level 1 30 3.23 1.382 .252 2.72 3.75 Level 2 29 3.28 1.386 .257 2.75 3.80 Level 3 36 2.83 1.231 .205 2.42 3.25 Level 4 57 3.33 1.286 .170 2.99 3.67 Total 152 3.18 1.314 .107 2.97 3.39 43- Use language AI applications to enhance pronunciation accuracy. Level 1 30 3.20 1.186 .217 2.76 3.64 Level 2 29 3.72 1.386 .257 3.20 4.25 Level 3 36 3.14 1.222 .204 2.73 3.55 Level 4 57 3.44 1.239 .164 3.11 3.77 Total 152 3.38 1.260 .102 3.17 3.58 44- Use language AI applications to translate the meanings of new words. Level 1 30 4.17 1.085 .198 3.76 4.57 Level 2 29 3.59 1.524 .283 3.01 4.17 Level 3 36 3.78 1.376 .229 3.31 4.24 Level 4 57 3.89 1.160 .154 3.59 4.20 Total 152 3.86 1.277 .104 3.66 4.07 linear trend showing increased usage with study progression. AI-assisted vocabulary learning and writing improvement show the most differences between levels, suggesting that specific skills may influence AI adoption more than general proficiency levels. However, EFL Omani students in Level Three consistently report the lowest AI usage, which could indicate external factors (e.g., curriculum difficulty, engagement levels). In contrast, the highest AI use is seen in word translation, especially among Level One students, suggesting beginners rely more on AI for direct translation rather than deeper language learning. The ANOVA tests show that none of the differences in AI usage across study levels are statistically significant (p-values > 0.05) among EFL Omani students. This indicates that the level of study does not have a significant effect on AI- integrated learning methods for English. Although some variations exist in AI usage patterns across study levels, these differences are not statistically significant. This suggests that AI-integrated learning is used relatively consistently regardless of the students’ level of study. IV. DISCUSSION This study employed quantitative research to examine English learning strategies among EFL Omani students, comparing traditional and AI-assisted methods. The findings revealed that traditional methods, particularly vocabulary memorization, translation, and structured learning, were dominant. These three strategies form the basis of learning foreign languages. On the other hand, AI tools were moderately used, mainly for translation, vocabulary learning, and pronunciation, but less so for grammar and writing. In both groups of foreign language learning strategies, vocabulary learning and translation are fundamental. Gender differences showed that female students were more engaged in structured learning strategies. However, the study finds no statistically significant gender differences in the use of AI-integrated applications for learning English. Further, the findings reveal that lower-level students rely heavily on structured techniques like writing new words, repetition, and translation, whereas higher-level students gradually shift toward interactive and communicative strategies, Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 379 such as speaking with native speakers, listening to English media, and engaging in discussions. This shows the linear track of learning foreign languages among non-native speakers of English, starting with learning new words and ending with speaking and listening. That is, Arab learners including EFL Omani students learn reading and writing skills first, followed by speaking and listening skills in contrast with the natural order of acquiring languages. However, strategies of learning grammar seem to be consistent across all students’ levels, thereby demonstrating a standardized instructional approach. A key observation is that vocabulary learning and translation of new words are the most common AI-assisted learning strategies, with higher mean scores compared to AI usage for writing, reading, and grammar. This aligns with Souriyavongsa et al. (2013), who found that students relied on vocabulary books and electronic dictionaries. These findings imply that as students advance in their language learning process, they are willing to implement more active learning methods, which may boost both fluency and confidence in using English. Moreover, students’ level of study does not significantly influence students’ use of AI-integrated methods for learning English. This result aligns with Tamimi and Razeq’s (2020) study, which emphasizes that though students adopt several strategies for learning English, their awareness and effective utilization of these strategies require further improvement and enhancement. However, this result contradicts previous findings (Kashefian- Naeeini & Maarof, 2016) that showed senior students utilize more strategies than freshmen. The findings also point out that students in level three reported the lowest usage of AI- integrated language learning strategies. This result contrasts with Sedighi and Zarafshan (2006), who revealed that senior students adopt more strategies than freshmen. A possible reason can be associated with the greater academic pressure faced by students at this level, thus reducing their engagement with AI-integrated language learning tools. The inconsistency in these studies implies that external factors like curriculum demands or students’ comfort with AI technology could impact AI adoption more than the level of study itself. Pedagogically, these findings advocate AI- integrated methods as a complement rather than a replacement of the traditional learning strategies. These results are in line with Rubaai et al. (2019), who highlighted the significance of adjusting teaching strategies based on students’ preferred learning styles. The variations in adopting AI tools across students’ skills and levels highlight the need for educators to provide targeted guidance on effective AI usage in the teaching and learning process. V. CONCLUSIONS The findings illustrated that both traditional and AI-integrated methods of foreign language learning are utilized with distinct patterns of preference among EFL Omani students. Traditional methods, namely translating words into Arabic, writing new words in notebooks, and practicing pronunciation, are dominant. On the other hand, AI-integrated language learning strategies are gaining traction, especially in vocabulary learning, pronunciation improvement, and listening comprehension. Consequently, these findings imply that AI is predominantly used as a supplementary tool rather than a replacement for traditional language learning strategies. Overall, though the findings imply that AI is a valuable resource in English language learning, its impact is not significantly influenced by students’ academic levels. However, this study has several limitations that should be considered while interpreting the results. First, the dependence on self-reported data might lead to response bias, since students may either overestimate or underestimate their use of AI and traditional learning strategies. Second, the sample consists of only students from one public university in Oman, thus limiting the generalizability of the findings to a broader population. Additionally, the study did not consider employing qualitative insights into students’ experiences and perspectives of AI integration in language learning, which could provide a deeper understanding of the challenges and benefits associated with AI-based learning. Future studies could also explore the possible effect of specific instructional interventions on enhancing AI adoption rates across varied levels. This implies encouraging lower-level students to utilize writing and repetition methods early to increase their vocabulary retention. Moreover, longitudinal studies tracing students’ development over time with AI-assisted foreign language learning could provide valuable insights into the long-term benefits and limitations of integrating AI Nayef Jomaa / Jurnal Arbitrer - Vol. 12 No. 3 (2025) 380 into English language instruction. ETHICS STATEMENT The relevant informed consent was obtained from the university, the Preparatory Studies Center, and students. CREDIT AUTHOR STATEMENT Nayef Jomaa: Designed the whole study, prepared the questionnaire, analysed the data, wrote the findings. Badri Mudhsh: helped in designing the questionnaire, collecting the data, and writing the literature review. 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