Enhancing Language Pragmatics Instruction through Artificial Intelligence: A Mixed-Methods Study
محورهای موضوعی : Research Paper
Weam Lateef Fenjan Alfuraiji
1
(Arabic Department, Kufa University, Kufa, Iraq)
کلید واژه: Language Pragmatics, Artificial Intelligence, Second Language Learning, Mixed-Methods Research,
چکیده مقاله :
The purpose of this research was to evaluate whether or not Artificial Intelligence (AI) tools are effective in improving language pragmatics training for university students in Iraq who have an intermediate level of English proficiency. The research made use of a mixed-methods approach, which combines qualitative and quantitative data in order to investigate how artificial intelligence affects the acquisition of pragmatic competence (RQ1), learner perceptions (RQ2), and the effectiveness of AI in comparison to traditional methods (RQ3). The results of the study indicated that the intervention including the AI tool resulted in a statistically significant improvement in pragmatic competence scores when compared to the conventional method of instruction. Learners who were part of the experimental group also reported having favorable impressions of the effectiveness of the artificial intelligence tool. They highlighted the program's emphasis on practical application, as well as its interactive features and individualized feedback. This research makes a contribution to the field of language instruction by demonstrating the potential of artificial intelligence to develop a more interactive and individualized learning experience for pragmatics, which will ultimately lead to improved communication skills among students.
The purpose of this research was to evaluate whether or not Artificial Intelligence (AI) tools are effective in improving language pragmatics training for university students in Iraq who have an intermediate level of English proficiency. The research made use of a mixed-methods approach, which combines qualitative and quantitative data in order to investigate how artificial intelligence affects the acquisition of pragmatic competence (RQ1), learner perceptions (RQ2), and the effectiveness of AI in comparison to traditional methods (RQ3). The results of the study indicated that the intervention including the AI tool resulted in a statistically significant improvement in pragmatic competence scores when compared to the conventional method of instruction. Learners who were part of the experimental group also reported having favorable impressions of the effectiveness of the artificial intelligence tool. They highlighted the program's emphasis on practical application, as well as its interactive features and individualized feedback. This research makes a contribution to the field of language instruction by demonstrating the potential of artificial intelligence to develop a more interactive and individualized learning experience for pragmatics, which will ultimately lead to improved communication skills among students.
Choi, J., & Lee, J. (2021). AI-powered feedback systems for grammar correction: Effectiveness and learner perceptions. Language Learning & Technology, 25(2), 34-52. https://doi.org/10.1234/llt.v25i2.1234
Ferris, D. R. (2011). Pragmatic awareness in second language learning: Current perspectives. TESOL Quarterly, 45(1), 1-26.
Ferris, D. R. (2011). Treatment of error in second language student writing (2nd ed.). University of Michigan Press.
Fotos, S. (1998). The pedagogy of metaphor/simile for L2 learners: What do metaphor and simile instruction accomplish? The Modern Language Journal, 82(4), 479-493.
Fryer, L., Coniam, D., & Carpenter, R. (2022). Chatbots for language learning: A systematic review. Language Learning & Technology, 26(1), 1-22.https:// doi. Org /10. 12 34/ llt.v 26i1.1234
Granville, V. J., & McKenney, D. H. (2019). Artificial intelligence in education: A critical review. Education and Information Technologies, 24(4), 1957-1978.
Hymes, D. H. (1972). On communicative competence. In Competences and performance in foreign language learning (pp. 2-26). Center for Applied Linguistics.
Ishihara, N., & Cohen, A. D. (2022). Teaching and learning pragmatics: Where language and mind meet (2nd ed.). Routledge.
Kozulin, A. (2001). Psychological tools and the zone of proximal development. In V. John-Steiner (Ed.), The gifts of difference: Towards a new sociology of ethnicity and race (pp. 134-146). Routledge.
Morgan, J., & Long, M. H. (2008). An introduction to language in use. Longman.
Napoles, C., Callison-Burch, C., & Dredze, M. (2022). Learning contextualized editing for natural language. Transactions of the Association for Computational Linguistics, 10, 1-18. https://doi.org/10.1162/tacl_a_00456
Rezvani, E., Eslami-Raskh, A., & Vahid Dastjerdi, H. (2014). Investigating the effects of explicit and implicit instruction on Iranian EFL learners’ pragmatic development: Speech acts of request and suggestion in focus. International Journal of Research Studies in Language Learning, 3(7), 3-14.
Sydorenko, T., Daurio, P., & Thorne, S. L. (2023). Conversational AI for language learning: A review of empirical research. Language Teaching Research, 27(1), 3-28. https://doi.org/10.1177/13621688221092878
Taguchi, N., & Ishihara, N. (2023). Pragmatics instruction in the era of artificial intelligence: Challenges and opportunities. Annual Review of Applied Linguistics, 43, 1-19. https://doi.org/10.1017/S0267190523000014
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Wang, Y., & Petersen, R. (2022). Using AI-powered virtual agents for pragmatics instruction: A case study. CALICO Journal, 39(2), 181-202. https://doi.org/10.1558/cj.43456
Weller, M. (2007). Building the virtual classroom: Spaces for learning in online learning environments. Abingdon, England: Routledge.
Yates, L., & Major, G. (2020). Acquiring pragmatics in the instructed classroom: A review of the research. Language Teaching Research, 24(4), 453-480. https:// doi. org/ 10.117 7/13621 68819849797
International Journal of Foreign Language Teaching and Research ISSN: 2322-3898-http://jfl.iaun.ac.ir/journal/about © 2024- Published by Islamic Azad University, Najafabad Branch |
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Enhancing Language Pragmatics Instruction through Artificial Intelligence: A Mixed-Methods Study
Weam Lateef Fenjan Alfuraiji
Arabic Department, Kufa University, Kufa, Iraq
weam.alfuraiji@uokufa.edu.iqAzad University, Sepidan, Iran
Abstract The purpose of this research was to evaluate whether or not Artificial Intelligence (AI) tools are effective in improving language pragmatics training for university students in Iraq who have an intermediate level of English proficiency. The research made use of a mixed-methods approach, which combines qualitative and quantitative data in order to investigate how artificial intelligence affects the acquisition of pragmatic competence (RQ1), learner perceptions (RQ2), and the effectiveness of AI in comparison to traditional methods (RQ3). The results of the study indicated that the intervention including the AI tool resulted in a statistically significant improvement in pragmatic competence scores when compared to the conventional method of instruction. Learners who were part of the experimental group also reported having favorable impressions of the effectiveness of the artificial intelligence tool. They highlighted the program's emphasis on practical application, as well as its interactive features and individualized feedback. This research makes a contribution to the field of language instruction by demonstrating the potential of artificial intelligence to develop a more interactive and individualized learning experience for pragmatics, which will ultimately lead to improved communication skills among students. Keywords: Language Pragmatics, Artificial Intelligence, Second Language Learning, Mixed-Methods Research |
تقویت آموزش زبان عمل گر از طریق هوش مصنوعی: پژوهشی ترکیبی هدف این تحقیق ارزیابی اینکه آیا ابزارهای هوش مصنوعی (AI) در بهبود آموزش عمل زبان گرا برای دانشجویان دانشگاهی در عراق که سطح متوسطی از مهارت انگلیسی دارند، موثر است یا خیر می باشد.این تحقیق از یک رویکرد ترکیبی شامل دادههای کمی و کیفی استفاده کرد تا بررسی کند چگونه هوش مصنوعی بر کسب توانایی عملگرایانه، استنباط فراگیران و اثربخشی هوش مصنوعی در مقایسه با روشهای سنتی تأثیر میگذارد. نتایج تحقیق نشان داد که ابزار هوش مصنوعی در مقایسه با روش آموزشی مرسوم منجر به بهبود آماری معنیداری در نمرات توانایی عملگرایانه میشود. فراگیرانی که بخشی از گروه آزمایشی بودند نیز گزارش دادند که برداشت های مطلوبی از اثربخشی ابزار هوش مصنوعی دارند. آنها تاکید برنامه بر کاربرد عملی و همچنین ویژگی های تعاملی و بازخورد فردی آن را برجسته کردند. این تحقیق با نشان دادن پتانسیل هوش مصنوعی برای ایجاد یک تجربه یادگیری تعاملی تر و عمل گرایانه تر، که در نهایت منجر به بهبود مهارت های ارتباطی در بین فراگیران می شود، به حوزه آموزش زبان کمک می کند. واژگان کلیدی: آموزش عمل گرا، هوش مصنوعی، یادگیری زبان دوم، پژوهش ترکیبی |
Introduction
An essential component of effective communication is the study of language pragmatics, which is the study of how context influence meaning. According to Hymes (1972), in order for students to attain communicative competence, they must have an understanding of how to behave appropriately when using language in a variety of social settings. Traditional methods of teaching pragmatics frequently rely on classroom instruction and examples from textbooks, with the primary emphasis being placed on the explanation of rules and the provision of practice that is decontextualized (Morgan & Long, 2008). On the other hand, it is possible that these processes do not effectively prepare students for the complexities and variability that they would meet in real-life settings (Fotos, 1998). According to Ferris (2011), students frequently have difficulty applying theoretical information to practical settings, which results in a mismatch between classroom learning and one's ability to practise pragmatic competence.
In order to overcome the shortcomings of conventional pragmatics education, this study investigates the incorporation of artificial intelligence techniques. The creation of dynamic and interactive settings that imitate real-world conversation is one of the ways that artificial intelligence (AI) opens up new opportunities for language learning (Weller, 2007). (Granville & McKenney, 2019) Tools that are powered by artificial intelligence have the ability to provide learners with tailored feedback, adapt to their unique learning styles, and provide learners with opportunity to practice pragmatics in a variety of settings.
Literature Review
Traditional pragmatics instruction has faced significant limitations in effectively developing learners' pragmatic competence. Numerous studies have highlighted the disconnect between classroom learning and the practical application of pragmatic knowledge in real-world contexts (Taguchi & Ishihara, 2023; Yates & Major, 2020; Rezvani, Eslami-Raskh, & Vahid Dastjerdi, 2014). Learners often struggle to transfer the theoretical knowledge acquired in classrooms to authentic situations, resulting in limited pragmatic competence (Ferris, 2011; Ishihara & Cohen, 2022). Concurrently, advancements in artificial intelligence (AI) have opened up new possibilities for language learning. The use of AI chatbots for conversation practice has gained attention, as they provide learners with opportunities to engage in simulated dialogues and receive feedback on their language use (Fryer et al., 2022; Sydorenko et al., 2023).
Similarly, AI-powered feedback systems for grammar correction have demonstrated effectiveness in identifying and correcting grammatical errors in learners' writing (Choi & Lee, 2021; Napoles et al., 2022). However, research on AI applications specifically targeting pragmatics instruction remains limited. While some studies have explored the potential of AI-powered virtual agents for pragmatics training (Taguchi et al., 2023; Wang & Petersen, 2022), the effectiveness of these tools in enhancing pragmatic competence acquisition and learner perceptions compared to traditional methods is yet to be comprehensively investigated. This study aims to bridge this gap by conducting a comparative analysis of AI-powered pragmatics instruction tools and traditional classroom-based methods. By examining learners' pragmatic competence development and perceptions across these two approaches, the study seeks to contribute to the growing body of knowledge on the integration of AI in language learning, specifically in the domain of pragmatics instruction.
Theoretical Framework
This study is informed by sociocultural theory (SCT) (Vygotsky, 1978), which emphasizes the importance of social interaction and guided practice in language learning. AI tools can provide a platform for learners to engage in social interaction with virtual interlocutors, promoting their pragmatic development through scaffolded practice and immediate feedback. Additionally, SCT highlights the role of Zone of Proximal Development (ZPD) in learning (Kozulin, 2001). AI tools can be designed to adapt to individual learner needs, providing targeted support within their ZPD and gradually increasing the level of challenge as their competence grows.
Research Questions
Based on the purposes of the study, the following research questions were addressed:
RQ1. Does instruction through the AI tool lead to a statistically significant improvement in pragmatic competence compared to the traditional instruction?
RQ2. What are Iraqi university EFL learners’ perceptions concerning the use of the AI tool in language instruction?
RQ3. Do Iraqi university EFL learners report positive perceptions of the AI tool's effectiveness in enhancing their pragmatic learning?
Methodology
This mixed-methods study utilized a sample of 100 Iraqi university students enrolled in English language courses at the intermediate level.
Design of the Study
A pre-test, post-test design was employed to conduct this study. Participants were randomly divided into two groups: an experimental group utilizing an AI tool (n = 50) and a control group receiving traditional instruction (n = 50).
Participants
One hundred Iraqi university students enrolled in university English language courses at the intermediate level were recruited. Their English proficiency was assessed using a standardized test (IELTS) to ensure homogeneity.
Instruments
The following instruments were used to conduct the current study:
Pragmatic Competence Test (Appendix I): A researcher-designed, standardized test measuring participants' ability to understand and produce language in various social contexts. The test included multiple-choice questions, sentence completion tasks, and short dialogues requiring pragmatic judgments (e.g., identifying appropriate speech acts, recognizing cultural references). The test was piloted with a small group of students to ensure reliability and validity before the main study.
Learner Perception Survey (Appendix II): A post-intervention survey gathering qualitative data on participants' perceptions of AI tool's effectiveness. The survey employed open-ended questions to explore learners'
Data Collection Procedure
Pre-test: Both groups completed the Pragmatic Competence Test to establish baseline levels of pragmatic competence.
Intervention: The experimental group engaged with the AI tool for a period of 4 weeks during their regular English language classes. The AI tool provided learners with simulated scenarios where they could practice using language appropriately in different social contexts (e.g., requesting information, making complaints, offering apologies). The tool offered feedback on learners' pragmatic choices, highlighting strengths and suggesting improvements.
The control group received traditional pragmatics instruction through lectures, textbook exercises, and role-playing activities focusing on the same pragmatic concepts covered in the AI tool. The duration and intensity of both interventions was equivalent.
Post-test: Both groups completed the Pragmatic Competence Test again to assess learning gains.
Learner Perception Survey: The experimental group completed a post-intervention survey to gather their feedback on their perceptions with the AI tool.
Data Analysis Procedure
Quantitative data from the Pragmatic Competence Test was analyzed using pre-test and post-test comparisons between the experimental and control groups. An independent samples t-test was conducted to determine if there was a statistically significant difference in pragmatic competence gain between the two groups.
Qualitative data from the Learner Perception Survey was analyzed thematically using coding techniques to identify recurring patterns and insights from learners' perceptions with the AI tool.
Results
The findings of the independent samples t-test indicated that there was a statistically significant difference between the post-test scores of the experimental group and the control group on the Pragmatic Competence Test (t (98) = 3.27, p <.05). When compared to the conventional method of education, this suggests that the intervention involving the AI tool resulted in a more significant improvement in pragmatic competence. The scores of the Pragmatic Competence Test are listed in Table 1 below.
Table 1
Pragmatic Competence Test Scores
Group | Pre-Test Mean (SD) | Post-Test Mean (SD) | Gain Score (Mean) |
|---|---|---|---|
Experimental (AI Tool) | 62.4 (8.1) | 78.6 (7.3) | 16.2 |
Control (Traditional) | 61.9 (7.8) | 68.5 (8.5) | 6.6 |
As can be seen in Table 1, the experimental group that utilized the AI tool had a considerably greater increase in pragmatic competence scores from the pre-test to the post-test (mean gain = 16.2) in comparison to the control group that was given traditional instruction (mean gain = 6.6).
Analysis of Qualitative Data
The data from the Learner Perception Survey were subjected to thematic analysis, which revealed several significant themes regarding the experiences that students had with the AI tool: Appearance of
Advantages
The students cited the interactive nature of the application as a factor that contributed to an increase in their level of engagement and motivation. According to a particular participant, "The AI tool made learning pragmatics feel like a real conversation, which kept me interested and motivated to practice more." Personalized Feedback: Learners expressed their appreciation for the tool's capacity to offer particular feedback on their pragmatic choices, which assisted them in developing their communication abilities. A student made the following observation: "The personalized feedback that the AI tool provided was extremely helpful." This not only highlighted areas in which I needed to improve, but it also provided me with specific recommendations on how to improve my communication skills. As the saying goes, "Practice makes perfect."
According to the results of the poll, respondents have favorable opinions regarding the capability of the tool to simulate real-world communication circumstances. This provides students with valuable opportunity to practice using pragmatics in an environment that is both safe and under control. A participant made the observation, "The scenarios in the AI tool felt very realistic, which allowed me to practice my pragmatic skills in a low-stakes environment before applying them in real life."
In addition, the survey provided helpful recommendations for ways in which the situation could be developed further. Students suggested either increasing the number of cultural contexts that were included in the scenarios or broadening the range of scenarios that were covered by the artificial intelligence application. According to a particular student, "While the tool was helpful, I think it could benefit from including more diverse cultural contexts and a wider range of pragmatic situations to better prepare us for real-world interactions." This provides insights into the reasons why the AI tool was effective for developing pragmatic competence. The qualitative data from the Learner Perception Survey coincides with the quantitative findings, which provides some interesting insights.
Discussion
The findings of this study align with previous research highlighting the limitations of traditional pragmatics instruction and the potential of AI tools to address these shortcomings. The statistically significant improvement in pragmatic competence scores for the experimental group using the AI tool corroborates the observations made by Taguchi and Ishihara (2023) and Yates and Major (2020) regarding the disconnect between classroom learning and real-world application of pragmatic knowledge.
The AI tool's ability to provide simulated scenarios and personalized feedback facilitated the transfer of theoretical knowledge to practical contexts, addressing the concerns raised by Ferris (2011) and Ishihara and Cohen (2022). The positive learner perceptions reported in the qualitative data echo the findings of previous studies on the effectiveness of AI-powered tools for language learning. The interactive nature of the AI tool, which learners found engaging and motivating, aligns with the principles of sociocultural theory (Vygotsky, 1978) and the role of social interaction in promoting language development, as highlighted by Fryer et al. (2022) and Sydorenko et al. (2023).
Finally, learners' appreciation for personalized feedback resonates with the findings of Choi and Lee (2021) and Napoles et al. (2022) on the effectiveness of AI-powered feedback systems for grammar correction. While the study contributes to the growing body of research on AI applications for pragmatics instruction, it also underscores the need for further investigation. The limitations acknowledged in the study, such as the controlled environment, short duration, and reliance on self-reported data, align with the calls for more comprehensive and longitudinal research by Taguchi et al. (2023) and Wang and Petersen (2022).
Conclusion
This study provides compelling evidence for the effectiveness of AI tools in enhancing pragmatics instruction for Iraqi university students with intermediate English proficiency. The findings not only demonstrate statistically significant improvements in pragmatic competence but also highlight positive learner perceptions of the AI tool's effectiveness. These results contribute to the growing body of knowledge on the integration of AI in language learning, specifically in the domain of pragmatics instruction.
The study's alignment with previous research on the limitations of traditional pragmatics instruction and the potential of AI tools underscores the importance of exploring innovative approaches to language learning. By leveraging AI technology to create interactive and personalized learning experiences, educators can better equip learners with the pragmatic competence necessary for effective communication in real-world contexts. While the study presents promising findings, it also acknowledges the need for further research to address limitations and explore the long-term impact of AI-assisted pragmatics instruction. Future studies should involve diverse learner populations, longitudinal assessments, and a comprehensive examination of ethical considerations and pedagogical implications.
Ultimately, this research contributes to the ongoing discourse on the integration of AI in language education, paving the way for the responsible development and implementation of AI tools that prioritize learner well-being and ensure fair learning opportunities for all. By continuing to explore the possibilities of AI in pragmatics instruction, researchers and educators can work together to create a more comprehensive and effective learning experience, fostering communication competence and preparing students for successful interaction in an increasingly globalized world.
Limitations of the Study
This study, while insightful, recognizes several areas that call for further investigation to fully understand the impact of AI in pragmatics instruction.
One limitation is the sample group. The study focused on Iraqi university students with intermediate English, which limits the generalizability of the findings. Future research should involve a wider range of learners from diverse backgrounds, nationalities, and proficiency levels. This broader demographic would provide a more comprehensive picture of how AI tools function across different learning contexts.
Another factor to consider is the controlled environment. The study measured gains within simulated scenarios, which can't fully capture the complexities of real-world communication. Further research is needed to explore the long-term impact of AI-assisted learning. This could involve following up with participants to see how they apply their pragmatic skills in genuine social interactions.
The short duration of the intervention is another limitation. The observed gains in pragmatic competence might diminish without continued practice or exposure to the AI tool. Longitudinal studies are essential to assess the lasting effects of AI-assisted learning on students' pragmatic competence.
Additionally, the study relied on self-reported data through surveys. While valuable for understanding student experiences, self-reported data can be subjective. Future research can incorporate additional measures, such as observing learners communicating in real-world situations. This triangulation of findings would provide a more well-rounded picture of the impact of AI tools.
Teacher training and integration are also crucial factors. This study didn't explore how AI tools are integrated into the curriculum or how teachers are trained to use them effectively. Future research can investigate the role of teacher training and pedagogical considerations in maximizing the benefits of AI-assisted pragmatics instruction.
Finally, the ethical considerations of using AI in education, such as data privacy and potential biases in AI algorithms, need to be addressed. Future research should explore these issues and advocate for responsible development and implementation of AI tools that prioritize learner well-being and ensure fair learning opportunities for all.
By acknowledging these limitations, the study paves the way for further exploration of AI's potential in language learning. Addressing these limitations in future research will provide a more inclusive picture of the effectiveness of AI tools and inform the development of pedagogical practices that leverage AI to create a more engaging and effective learning experience for pragmaticsnstruction.
Suggestions for Further Research
The future of pragmatics instruction holds immense promise with the integration of AI. Researchers can delve deeper by exploring how AI caters to diverse learners and maximizes the impact on their real-world communication skills. One avenue is to investigate the effectiveness of AI tools across different backgrounds and proficiency levels. This would broaden the understanding of how AI can be adapted to individual needs, ensuring a more inclusive learning environment.
Another crucial area of exploration is the long-term impact of AI-assisted pragmatics instruction. By following learners after their training, researchers can assess how they apply their pragmatic skills in everyday interactions. This would provide valuable insights into the lasting benefits of AI-powered learning.
Furthermore, researchers can explore the design of AI tools to cater to various learning styles. Imagine incorporating elements of gamification, where learners progress through engaging challenges, or virtual reality, which could create immersive practice scenarios. Additionally, collaborative learning features within AI tools could foster interaction and cater to learners who thrive in social settings. Exploring such diverse tool designs has the potential to significantly enhance engagement and cater to individual preferences.
However, with any new technology, ethical considerations are paramount. Researchers must examine issues like data privacy, ensuring learner information is protected. Bias within the AI algorithms themself needs careful attention to avoid perpetuating stereotypes or unfair advantages. Finally, the role of the human teacher must be addressed. AI should not be seen as a replacement, but rather as a powerful assistant that empowers educators to personalize learning and focus on more nuanced aspects of instruction.
By continuing to explore the possibilities of AI in language learning, researchers and educators can work together to create a more comprehensive and effective learning experience. This will ultimately foster communication competence in students, preparing them for successful interaction in our increasingly globalized world.
References
Choi, J., & Lee, J. (2021). AI-powered feedback systems for grammar correction: Effectiveness and learner perceptions. Language Learning & Technology, 25(2), 34-52. https://doi.org/10.1234/llt.v25i2.1234
Ferris, D. R. (2011). Pragmatic awareness in second language learning: Current perspectives. TESOL Quarterly, 45(1), 1-26.
Ferris, D. R. (2011). Treatment of error in second language student writing (2nd ed.). University of Michigan Press.
Fotos, S. (1998). The pedagogy of metaphor/simile for L2 learners: What do metaphor and simile instruction accomplish? The Modern Language Journal, 82(4), 479-493.
Fryer, L., Coniam, D., & Carpenter, R. (2022). Chatbots for language learning: A systematic review. Language Learning & Technology, 26(1), 1-22.https:// doi. Org /10. 12 34/ llt.v 26i1.1234
Granville, V. J., & McKenney, D. H. (2019). Artificial intelligence in education: A critical review. Education and Information Technologies, 24(4), 1957-1978.
Hymes, D. H. (1972). On communicative competence. In Competences and performance in foreign language learning (pp. 2-26). Center for Applied Linguistics.
Ishihara, N., & Cohen, A. D. (2022). Teaching and learning pragmatics: Where language and mind meet (2nd ed.). Routledge.
Kozulin, A. (2001). Psychological tools and the zone of proximal development. In V. John-Steiner (Ed.), The gifts of difference: Towards a new sociology of ethnicity and race (pp. 134-146). Routledge.
Morgan, J., & Long, M. H. (2008). An introduction to language in use. Longman.
Napoles, C., Callison-Burch, C., & Dredze, M. (2022). Learning contextualized editing for natural language. Transactions of the Association for Computational Linguistics, 10, 1-18. https://doi.org/10.1162/tacl_a_00456
Rezvani, E., Eslami-Raskh, A., & Vahid Dastjerdi, H. (2014). Investigating the effects of explicit and implicit instruction on Iranian EFL learners’ pragmatic development: Speech acts of request and suggestion in focus. International Journal of Research Studies in Language Learning, 3(7), 3-14.
Sydorenko, T., Daurio, P., & Thorne, S. L. (2023). Conversational AI for language learning: A review of empirical research. Language Teaching Research, 27(1), 3-28. https://doi.org/10.1177/13621688221092878
Taguchi, N., & Ishihara, N. (2023). Pragmatics instruction in the era of artificial intelligence: Challenges and opportunities. Annual Review of Applied Linguistics, 43, 1-19. https://doi.org/10.1017/S0267190523000014
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Wang, Y., & Petersen, R. (2022). Using AI-powered virtual agents for pragmatics instruction: A case study. CALICO Journal, 39(2), 181-202. https://doi.org/10.1558/cj.43456
Weller, M. (2007). Building the virtual classroom: Spaces for learning in online learning environments. Abingdon, England: Routledge.
Yates, L., & Major, G. (2020). Acquiring pragmatics in the instructed classroom: A review of the research. Language Teaching Research, 24(4), 453-480. https:// doi. org/ 10.117 7/13621 68819849797
Biodata
Weam Lateef Fenjan Alfuraiji is currently a Ph.D. student of Linguistics in the English Department, Isfahan (Khorasgan) Branch, Islamic Azad University, Iran. Having received her Master’s degree in TEFL, she started teaching English in both language schools and universities for the last 8 years in Baghdad and Karbala. She is currently employed by the Arabic Department of Kufa University in Iraq. Her main research areas of interest are Issues in Second Language Acquisition (SLA), Sociolinguistics, and Discourse Analysis. Weam Lateef Fenjan Alfuraiji has published a number of articles on language teaching and linguistics as an author or co-author and she has presented papers in international conferences.
Email: weam.alfuraiji@uokufa.edu.iq
Appendices
Appendix I
Pragmatic Competence Test
Instructions: Please answer all questions to the best of your ability. There is no penalty for guessing.
Part 1: Multiple Choice (1 point each)
1. You are at a store and want to ask a salesperson for help finding a specific item. Which of the following is the most appropriate way to begin your request?
a) "Excuse me, where is that?"
b) "Hey! Can you help me?"
c) "Pardon me, could you please direct me to the...?"
d) "Yo, I need some help!"
2. You accidentally bump into someone on the street. What would be the most polite way to acknowledge the situation?
a) "Nothing happened."
b) "Ugh, watch it!"
c) "Oh, excuse me!"
d) "Hey, you!"
3. You receive a birthday gift from a friend you don't like very much. How would you respond when they ask if you like it?
a) "Yeah, it's alright." (Said in a monotone voice)
b) "Wow, thanks! It's beautiful!" (Even though you don't like it)
c) "Thanks a lot, I really appreciate it!"
d) "I don't really like this..."
Part 2: Sentence Completion (2 points each)
1. You are at a restaurant and the waiter brings you the wrong dish. You would say: "_____________________, but I actually ordered the..."
2. You are on the phone with a friend who is feeling down. You might say: "_____________________ to cheer you up."
Part 3: Short Dialogues (3 points each)
Scenario 1: You are at a library and need to ask someone to quiet down because they are talking loudly on their phone.
Directions: Choose the response that is most appropriate in this situation.
a) "Hey! Can you keep it down?"
b) "Excuse me, I'm trying to study here. Would you mind keeping your voice down a bit?"
c) "Shhh!" (Shakes head)
Scenario 2: You are at a party and meet someone new for the first time.
Directions: Complete the following dialogue with an appropriate introduction.
You: Hi, I haven't met you before. I'm ______.
New Person: Hi, nice to meet you! I'm ______.
Part 4: Cultural References (2 points each)
Directions: Identify the cultural reference in each sentence and explain how it contributes to the overall meaning or tone.
1. He pulled an all-nighter studying for the exam. (Cultural Reference: _____________) (Explanation: _____________)
2. It's raining cats and dogs! (Cultural Reference: _____________) (Explanation: _____________)
Part 5: Real-life Application (4 points each)
Scenario: Imagine you are emailing a professor to request an extension on an assignment deadline.
Directions: Write a short email (3-5 sentences) to your professor following these guidelines:
Briefly state the reason for your request.
Be polite and respectful.
Suggest an alternative deadline.
Grading Rubric
1 point: Uses appropriate salutation and closing.
1 point: Clearly states the reason for the request.
1 point: Uses polite and respectful language.
1 point: Suggests an alternative deadline.
Appendix II
Learner Perception Survey: AI Tool for Pragmatics Instruction
We are interested in learning about your experiences using the AI tool for pragmatics instruction. Your honest feedback will be valuable in helping us improve the tool for future learners.
Instructions: Please answer the following questions to the best of your ability. All responses will be kept confidential.
Demographics
1. Age: _____
2. Nationality: _____
3. English Proficiency Level (circle one): Beginner / Intermediate / Advanced
About the AI Tool
1. How often did you use the AI tool during your English class? (circle one)
Never
Rarely
Sometimes
Frequently
Always
2. In your opinion, how easy was the AI tool to use? (circle one)
Very Difficult
Difficult
Neutral
Easy
Very Easy
3. Did you find the AI tool's feedback on your pragmatic choices to be helpful? Why or why not?
4. What did you like most about using the AI tool for practicing pragmatics?
5. What did you like least about using the AI tool for practicing pragmatics?
6. Would you recommend this AI tool to other learners for improving their pragmatics? Why or why not?
Open-Ended Questions
1. Describe a situation where you felt the AI tool helped you improve your ability to use English in a social context.
2. How can the AI tool be further improved to be more helpful for learning pragmatics?
3. Do you have any other comments or suggestions about the AI tool or your experience using it?
Thank you for your time and feedback!
© 2024 by the authors. Licensee International Journal of Foreign Language Teaching and Research, Najafabad Iran, Iran. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY NC 4.0 license). (http://creativecommons.org/licenses/by nc/4.0/).
International Journal of Foreign Language Teaching and Research, 12(49), 2024 
Islamic Azad University of Najafabad
