ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 12, Issue 3, October 2024 https://journal.uniku.ac.id/index.php/ERJEE 1251 LECTURERS’ READINESS AND INTENTIONS FOR AI INTEGRATION IN INDONESIAN AND INDIAN ELL CLASSROOM Ni Wayan Adi Priantini English Language Education Study Program, Faculty of Teacher Training and Education, Universitas Mahasaraswati Denpasar, Kamboja Street No 11.A Denpasar, Indonesia Email: adipriantini02@gmail.com Dewa Ayu Alit Riska Dewi English Language Education Study Program, Faculty of Teacher Training and Education, Universitas Mahasaraswati Denpasar, Kamboja Street No 11.A Denpasar, Indonesia Email: Ayuriskadewi32@gmail.com Anak Agung Putri Maharani English Language Education Study Program, Faculty of Teacher Training and Education, Universitas Mahasaraswati Denpasar, Kamboja Street No 11.A Denpasar, Indonesia Email: aamaharani@unmas.ac.id I Komang Budiarta English Language Education Study Program, Faculty of Teacher Training and Education, Universitas Mahasaraswati Denpasar, Kamboja Street No 11.A Denpasar, Indonesia Email: mrbudi@unmas.ac.id Ni Luh Putu Dian Sawitri English Language Education Study Program, Faculty of Teacher Training and Education, Universitas Mahasaraswati Denpasar, Kamboja Street No 11.A Denpasar, Indonesia Email: diansawitri@unmas.ac.id Harvinder Kumar Negi Department of English, GLA University Mathura, India Email: harvinder.negi@gla.ac.in APA sCitation:. Priantini, N. W. A., Dewi, D. A. A. R., Maharani, A. A. P., Budiarta, I. K., Sawitri, N. L. P. D., & Negi, H. K. (2024). Lecturers’ readiness and intentions for ai integration in Indonesian and Indian ELL classroom. English sReview: sJournal sof sEnglish sEducation, s12(3), 1251-1260. https://doi.org/10.25134/ erjee.v12i3.10034 Received: 25-06-2024 Accepted: 23-08-2024 Published: 30-10-2024 INTRODUCTION Since the beginning of the 21st century, a multitude of novel instruments have emerged and developed within artificial intelligence (hereafter, AI) scope. To give one example, the strength of AI algorithms is the foundation for online platforms’ capacity to provide users with tailored recommendations. It can be said that AI is among the most notable Abstract: Investigating the readiness and intention of the lecturers for the use of artificial intelligence (AI) in English language learning is the goal of this research. The questionnaire, online interview, and focus group discussion were all used in this mixed-methods designed research to collect data. Finding out the lecturers’ readiness and their intentions on the AI applications into their English classrooms are the main points of emphasis. As the participants of the study, 29 English Department lecturers were involved, 11 Indonesia lecturers (5 males and 6 females) and 18 Indian lecturers (6 males and 12 females). It was identified that the lecturers have high readiness in infusing AI into the English language learning classroom. Their readiness was supported by the identified efforts that the lecturers had performed. Then, it was also figured out that the lecturers have positive intention to infuse AI into their English class. These findings bring profound implications. The AI integration into ELL can streamline administrative tasks which allows the lecturers to focus more on quality of instruction and interaction. The lecturers also can leverage AI technology effectively into their teaching through adapting their teaching strategy. This requires ongoing professional training and development for the lecturers to remain adept in utilizing AI. Keywords: Artificial Intelligence; English language learning; intention; readiness . Ni Wayan Adi Priantini, Dewa Ayu Alit Riska Dewi, Anak Agung Putri Maharani, I Komang Budiarta, Ni Luh Putu Dian Sawitri, & Harvinder Kumar Negi Lecturers’ readiness and intentions for ai integration in Indonesian and Indian ELL classroom 1252 innovations in the field of education brought about by the digital transformation (Ferikoğlu & Akgün, 2022; Lazzat, 2024). With its many advantages, including individualized learning, better educational results, and increased administrative efficiency (Chen et al., 2020; Ifenthaler et al., 2024), AI offers possibility to revolutionize activity of the lecturers when it comes to the subject of knowledge delivery and student educating. In relation to English language learning (hereafter ELL) context, with AI being incorporated into it more and more, lecturers must be ready to use it within their teaching practices. AI has the capacity to enhance the overall teaching and learning process quality (Khan, 2023; Sun et al., 2020), thus lecturers must build readiness to use it while teaching English. AI-based teaching methods can help teachers teach English more easily (Yu & Nazir, 2021). AI technology can enhance English language skills while giving teachers and students a more individualized learning experience (Ayotunde et al., 2023; Muslimin et al., 2024). The readiness of the lecturers to adopt AI in ELL classroom is gradually becoming important in determining the success of the implementation. It is encouraging to note that AI technologies are possible to revolutionize the teaching of English with quality and quantity improvement of teaching (Gyawali & Mehandroo, 2022). Successful language teaching and learning need the development of learner autonomy, which may be achieved by lecturers who are ready to include AI technology (Khalymon & Shevchenko, 2017; Syafryadin et al., 2022). This change requires that lecturers have not only a conceptual comprehension and appreciation of those tools but also practical competence in applying them across the learning-teaching process. However, the next factor is pedagogical readiness which is also imperative when the lecturer is willing to incorporate AI into ELL classroom. Whereas, it has been claimed that AI exclusively offers learners with individual, dynamic learning experiences, but the process entails that lecturers have to reconsider their stances and approaches to ELL (Akbarani, 2023) and their acceptance of the technology (Liu, 2023). Furthermore, another study also presents brief overview of the existing AI applications that have been reported to have been effectively adopted for enhancing EFL settings and the level of teaching impact that has been brought about by these technologies (Jiang, 2022). Zhao, Wu, & Luo (2022) concentrated on increasing teachers’ AI literacy to improve teaching efficacy. These studies underscore the need for lecturers to be well- versed in AI to navigate its implications on ELL class. Furthermore, the study by Ferikoğlu & Akgün (2022) focused on comprehending teachers’ readiness and propensity towards AI, underscoring the need of investigating lecturers’ knowledge of AI integration in ELL context. Consequently, the successful incorporation of AI in ELL largely relies on lecturers’ readiness to utilize it effectively. Lecturers are more likely to accept and successfully apply AI in ELL if they have a good attitude about the technology, see it as an improvement to their performance, and think it is user-friendly (Gao et al., 2023). The results of AI integration in ELL can be significantly impacted by the lecturers, especially their intentions toward its use (Chacón, 2005). The intentions of the lecturers in incorporating AI to the learning processes are important in delivering personalized learning experiences such as adaptive learning where the educational material is chosen according to the needs of the specific learner (Alharbi, 2023; S. Kumar et al., 2023), and it is further explored in regard to the adaptive approaches as critical for the students’ engagement (Luo, 2024). If the lecturers are committed to an AI-driven instruction, they are more likely to help the students due to differences in learning needs and desires, hence enhancing their achievement of the intended foreign language. Moreover, lecturers’ intention to integrate AI in ELL can affect its educational climate of context variables and support. In cases where lecturers demonstrate a good attitude and concern towards using AI in their class, it will force to put down infrastructure, training, and other forms of professional development (Idham et al., 2024). From this perspective, it is clear that AI technologies must be integrated into ELL classroom and lecturers need to be empowered with the right tools to do so. However, there is the need to realize that with the many benefits that AI can bring to ELL there are also associated challenges when it comes to integration of the technology into the ELL environment. These are the following issues have been raised about the overuse of AI tools such as human isolation, and the negations in critical thinking (Xuyen, 2024) as well as uncertainty regarding the pedagogical use of AI (Kranz & Abele, 2024). Thus, intentions of lecturers should ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 12, Issue 3, October 2024 https://journal.uniku.ac.id/index.php/ERJEE 1253 go beyond the implementation of AI and should include ensuring an adequate and ethical use of AI (Eden et al., 2024) that will include human- centered educational models as well. Research on readiness and intention to integrate AI into ELL class is essential to conduct because it involves English department lecturers from Indonesian and Indian universities. This is significant despite the frequent studies already conducted on the use of AI in ELL. Aligned with the background, the following are the research questions: (1) How are the readiness of the lecturers from Indonesia and India in infusing AI into ELL classrooms? (2) What are the intentions of the lecturers from Indonesia and India in integrating AI into ELL classrooms? METHOD The current research engaged 29 English Department lecturers as the respondents. The participants may be divided into two groups: the 18 Indian lecturers (6 males and 12 females) and the 11 Indonesian lecturers (5 males and 6 females). They represented the English departments of the two universities in India and Indonesia wherein the sample size has been carefully chosen to reflect a manageable and balanced number of Indonesian and Indian lecturers. Furthermore, the selection of 29 participants with an emphasis on ELL in AI helps to reach participants who have professional background as both language lecturers and AI specialists. A questionnaire was distributed online to the lecturers from both universities in Indonesia and India to obtain quantitative data on their responses regarding the readiness and intention of using AI in ELL context. Furthermore, focus group discussion (henceforth, FGD) and interview had been designed and carried out in order to ascertain the readiness and intention of the respondents about the implementation of AI in relation to ELL in Indonesia and India. The questionnaire on AI readiness that the respondents could access online was used to collect the quantitative data. The theory of Chai et al., (2021) about self-efficacy in learning English assisted by AI and AI readiness indicators was the basis for this online questionnaire’s adaptation and modification. A total of ten items made up the online AI readiness questionnaire: each indicator had been developed into five items. Each item had been assessed using a 5-point Likert scale, ranging from 1 (strongly disagree, SD) to 5 (strongly agree, SA). Moreover, AI intention questionnaire covers 5 items which adapted from the theory of Chai et al., (2021) about intention. Concurrently, interview and FGD were used to gather qualitative data. The FGD topic and interview protocols were created to guide the data collection process. The purpose of these instruments, which were modified and adapted from Celik, Dindar, Muukkonen, & Järvelä (2022), was to gain a thorough knowledge of the respondents’ readiness and intention of using AI in ELL. Technical knowledge served as the foundation for both the FGD and the interview. The instruments’ validity and reliability were evaluated by a panel of two specialists. The expert judges are PhD holders who specialize at technology in education and ELL. The instruments were evaluated based on the degree to which the items aligned with the theoretical frameworks of the research. Feedback on the items’ suitability for the goals was provided after it was emphasized how well-suited they were. In collecting the research data, first of all, the questionnaire was delivered by means of Google Form, and the respondents filled them out. Google Form was used to provide flexibility for all participants across two countries. Then, the findings gauged by the questionnaire were sorted and scrutinized by utilizing the descriptive statistic formula such as standard deviation and mean score. To collect more profounder and deeper research data, the participants consented to participate in the virtual interview. Particularly about the time and day of the interview, the participants and the researchers scheduled a meeting. Finally, a Zoom meeting was used to have the respondent representatives participate in the focus group discussion at the same time virtually. Zoom was utilised \due to providing accessibility which allows all participants to join the interview from various locations, eliminating geographical and time barriers that hinder participation. The collected data were analyzed both descriptively and qualitatively. The quantitative analysis yielded means and standard deviations to ascertain the lecturers’ level of readiness and intention on implementing AI within ELL. Concurrently, the data analysis was conducted on the qualitative data which were obtained from interview and FGD to delve deeper about the lecturers’ readiness and intentions in relation to the integration of AI into their English classrooms. RESULTS AND DISCUSSION After garnering a rich set of research data and analysing them, the findings encompass the Ni Wayan Adi Priantini, Dewa Ayu Alit Riska Dewi, Anak Agung Putri Maharani, I Komang Budiarta, Ni Luh Putu Dian Sawitri, & Harvinder Kumar Negi Lecturers’ readiness and intentions for ai integration in Indonesian and Indian ELL classroom 1254 readiness and intentions of the lecturers from Indonesia and India in relation to infusing AI- based apps within ELL classroom context. The lecturers’ readiness level of infusing AI-based apps within ELL classroom context Table 1. The lecturers’ readiness level A AI Readiness Means SD 1. AI technology in English language learning provides people greater control over their everyday life. 3.5 1.1 2. The latest AI technologies- based products and services are much more convenient to use in English language learning. 3.9 0.8 3. I would rather use the most cutting- edge AI technology for learning English. 3.6 1.1 4. When it comes to learning English, I enjoy AI technology since it lets me customize things to meet my needs. 4.0 0.9 5. I feel confident that AI technologies in English language learning will run smoothly. 3.8 1.0 B Self-efficacy in learning English assisted by AI Means SD 6. I have no doubt that I will perform well in ELL- assisted AI. 3.7 1.1 7. I think that if I put in enough effort in the English- assisted AI class, I can succeed. 3.7 1.0 8. I am confident that I can comprehend the most challenging content covered in the English- 3.5 1.1 assisted AI course. 9. I am sure I can pick up the fundamental ideas covered in the English-assisted AI course. 4.0 0.8 10. I am certain that AI usage in English class supports me in searching learning materials and answers which are not provided by the lecturer. 4.0 0,8 Based on table 1, the average means of the items (5 items) which belong to AI Readiness ranged from 3.5 (SD=1.1) to 4.0 (SD=0.9). The average means of the total 5 items which belong to Self- efficacy in learning English Assisted by AI ranged from 3.5 (SD=1.1) to 4.0 (SD=0.8). The average mean reveals that the lecturers are identified to possess high level of readiness in infusing AI into English classroom. Further, the SDs reveal rather high standard deviation values, for instance, 1.1 and 0.9 which means that the participants’ readiness differ greatly. This variation means that for while some of the participants are perceived as readily participate in AI integration, there are others who are not. These quantitative findings were confirmed by the interview findings. Specifically, the readiness level of the lecturers were supported by their efforts in infusing AI into their English class. The interviews with the lecturers the representatives from Indonesia and India, revealed various efforts to integrate AI into English classes were figured out. First of all, the effort is following comprehensive training to develop professionalism. The lecturers try to get access to seminars, online courses, and learning resources that can further their expertise in AI. This finding can be proven by the following interview scripts: “Lecturers should have access to workshops, online courses, and resources, such as educational materials, designed to support the development of their AI skills.” L1. “Lecturers need to attend training and courses which emphasize AI application in ELL.” L4. The above interview data were supported by the following FGD finding. ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 12, Issue 3, October 2024 https://journal.uniku.ac.id/index.php/ERJEE 1255 “Specifically to me, the effort that I usually made before implementing AI into my classroom is, of course, I need to watch the tutorial or only read the tutorial because I need to know the feature or the special menu.”L3 The abovementioned interview and FGD data had proven that it is imperative that the lecturers take part in training courses and programs that are explicitly intended to assist them learn about and comprehend the application of the AI usage in educational contexts, specifically within ELL. To achieve this, lecturers attend workshops, take online courses, and have access to educational materials aimed at improving their AI skills (Belda-Medina & Goddard, 2024). They also participate in training programs and courses on AI in ELL to equip themselves with knowledge and capabilities necessitated for effective classroom integration. Moreover, the lecturers frequently watch or read tutorials to become familiar with AI features and functions before applying AI in the class (Paranjape et al., 2019). These attempts highlight the value of participating in training programs aimed at helping them understand and implement AI in educational contexts, particularly in teaching English. The second effort is staying updated on AI developments in English teaching and learning. To prove the intended subject matter that the lecturers want to continue being successful lecturers in a discipline that is dynamic, the best thing that they have to do is to educate themselves with the current advanced knowledge in AI and its implementations in the English classroom. This can be proven by the following excerpts. “It is important to continue learning on the newest trends in AI implementation together with their likely impact on our careers as lecturers.” L1 “A crucial step is ensuring the lecturers have a clear understanding of how AI can augment the English learning experience.” L5. Based on the aforesaid excerpts, it is significant for the lecturers to understand the basic ideas and principles of AI as well as its prospective uses in the fields of English education. The interview data were supported by the following FGD data. The lecturer tried to find out what AI apps that the students use in learning English, as well as wanted to guide proper usage and prevent overreliance on AI. This can be proven by the following FGD data. “Yeah, so we are very familiar with AI nowadays. Like we can use PDF AI to read or compare some articles. So we don’t need to spend much time to read all of the articles to compare.” L2. “You know, actually, our course books, they have some limitations. But then what AI does to the they provide you more options. They provide you with more accessible material.” L5. To successfully fulfil their roles in the constantly evolving field of education, particularly in ELL, lecturers need to stay updated about the recent expansions in AI and its applications (Vall & Araya, 2023). Lecturers need to comprehend the concepts and relevant applications of AI to improve the English learning process (Ulfa, 2023). The third effort is embracing adaptability and flexibility. It is recommended that the lecturers investigate novel AI techniques and technologies as they become accessible, modifying their pedagogical approaches to keep up with the field’s fast evolution. This can be validated by the following interview data. “Adaptability and flexibility are essential qualities for the lecturers when dealing with AI, as the field is constantly evolving. They should be encouraged to explore new AI technologies and methods as they become available, adapting their teaching strategies accordingly.” L6. In line with the above statement, the lecturers should familiarize themselves with many AI- powered platforms that can be used in English lectures. Besides the interview data, the following FGD data also highlight adaptability of the lecturers from traditional approach to the AI implementation in English classroom. “At the same time, I’d also acknowledge the fact that it is helping us a lot, like being the lecturer at times of the language learning tools that students, that help students to give feedback and also helps in training their speaking skills, their oratory skills.”L6 The above FGD data shows that the lecturers require to acknowledge need to find balance between AI and traditional approaches. Given the field’s rapid change, the lecturers must possess adaptability and flexibility, Ni Wayan Adi Priantini, Dewa Ayu Alit Riska Dewi, Anak Agung Putri Maharani, I Komang Budiarta, Ni Luh Putu Dian Sawitri, & Harvinder Kumar Negi Lecturers’ readiness and intentions for ai integration in Indonesian and Indian ELL classroom 1256 particularly in the context of AI in ELL. The data emphasize the need for the lecturers to continually research new AI tools and techniques in order to improve their pedagogical approaches (Akintayo et al., 2024), and it is essential for maintaining relevance in education field (Kuleto et al., 2021). The fourth effort is aligning assessment methods wherein in order to maintain alignment with the intended learning objectives and outcomes, the lecturers create evaluation criteria that take the usage of AI technologies into consideration. This can be validated by the following interview data. “The lecturers should develop evaluation criteria that account for AI tools usage while ensuring they align with the learning objectives and outcomes desired.” L7. It is critical for the lecturers to create evaluation criteria that not only take into account AI tools but also make sure that they are in accordance with the intended learning objectives and outcomes when it comes to coordinating assessment methods with AI application in education (Akgun & Greenhow, 2022). It is imperative that lecturers focus on creating realistic exams that support higher-order cognitive capabilities, problem-solving, creativity, and teamwork that are elemental in the 21st century (Liang, 2023). Students can receive real-time feedback from AI-powered assessment systems, which enables them to track their progress and adjust their learning approach as necessary (Liu, 2023; Rathore et al., 2023; Zheng et al., 2022). The last identified effort is fostering collaboration and knowledge sharing amongst the lecturers. To foster an innovative and knowledge- sharing culture in AI-assisted teaching, lecturers are encouraged to work together with colleagues, exchange experiences, and build support systems (Rangel-de Lázaro & Duart, 2023) which allow lecturers to be innovative in incorporating AI into their teaching methods (Opesemowo & Adekomaya, 2024). This can be validated through the following interview excerpt. “The lecturers should be encouraged to collaborate, share experiences, and establish peer support networks which can accelerate the effective AI tools in the class.” L8. In line with the above excerpt, the cooperation and knowledge exchange amongst the lecturers are essential to innovate the English class which is assisted by AI. This partnership has the potential to accelerate the efficient application of AI in English language learning (Sapci & Sapci, 2020). These efforts demonstrate a comprehensive approach to integrating AI into English classes, covering various aspects such as training, collaboration, adaptability, and assessment alignment. The lecturers’ intention level of infusing AI-based apps within ELL classroom context Table 2. The lecturers’ intention level No Intentions Means SD 1. I will continue to learn AI. 3.9 0.7 2. I will stay informed about the latest AI applications. 3.9 0.7 3. I will keep updated to AI- related information. 3.8 0.8 4. I will use AI to strengthen my learning. 4.1 0.8 5. I will use AI to encourage my students in learning English. 3.9 0.8 The table 2 shows the average means of the items (5 items) which belong to Intentions ranged from 3.8 (SD=0.8) to 4.1 (SD=0.8). It can be interpreted that the lecturers are identified to have positive intention. It is echoed by Hazaymeh et al., (2024) that English lecturers heavily relied on AI applications as tools to enable tasks and enhance methods of instruction, which revealed a positive relationship with experience and intention of AI integration. The mean score and standard deviation data above were empowered by the interview data. The first intention is to use AI to provide the students with adaptive and personalize learning within English class. This can be proven by the following excerpt. “AI-powered adaptive learning piques my attention. The AI may customize the English class based on analysis of each student’s strength and weakness.” L3. Based on the excerpt, it can be wrapped up that the intention was to enhance adaptive learning which assisted and built by AI in English class. ENGLISH REVIEW: Journal of English Education p-ISSN 2301-7554, e-ISSN 2541-3643 Volume 12, Issue 3, October 2024 https://journal.uniku.ac.id/index.php/ERJEE 1257 Enhancing students' flexible learning experiences is a key objective. Lecturers can utilize AI to customize English class according to each student’s strengths and areas for improvement (Bai, 2022; Yu & Nazir, 2021). By adjusting to each student’s unique speed and learning style, this tailored approach not only meets the different demands of learners but also maximizes the learning process (George & Wooden, 2023; Pratama & Hastuti, 2024). The next identified intention is the lecturers want to use AI to automate the development of materials and texts. It can be validated by the following data. “I’m quite enthused about AI’s potential for content production such as learning materials.” L6. AI’s ability to automate the creation of instructional texts and resources has enormous potential to improve student learning and completely transform teaching methods. Studies by Emenike & Emenike, (2023) and Kasneci et al., (2023) found out that AI system has reduced the manual labor for educators and given students access to interactive learning resources. Therefore, it is projected to transform how courses are taught and how they are created (Vafadar & Amani, 2024). Further, the lecturers’ intention is using AI for English class support and facilitate the students to grow understanding and competency. This can be validated by the following excerpts. “AI language translation tools will be huge for translating instructions and explanations in real- time.” L5. “AI is what I want to utilize pronunciation practice. My students can videotape themselves and receive immediate pronunciation corrections from AI.” L2. The abovementioned interview data highlights that the lecturers’ intention is to apply powerful and valuable AI based applications to support the students in learning English. The interview data are supported by the findings which yielded through conducting FGD. The lecturers’ interest is to help the students in mastering English especially the specific skill of it such as the practice and feedback on spoken English. This can be proven by the following excerpt. “Using AI for spoken practice and feedback is my intention. In order to improve the students’ pronunciation, fluency, and other skills, they might converse with the AI.” L3. AI is integrated to enhance students’ English language skills and meet their specific learning requirements. For example, Chingakham & Tamuk (2024) argue that AI enriches vocabulary and also Huang (2021) posits that AI technologies foster memory to gain deeper understanding of contextual meaning of the language. Thus, AI integration has demonstrated great potential in improving the educational process in the field of ELL. CONCLUSION Drawing from the research findings, it is wrapped up that infusing AI into ELL classroom requires the lecturers’ readiness and intention to accomplish a meaningful and successful English environment for the students. The lecturers are suggested to focus on improving their technological abilities, adopting innovative teaching strategies, using technology to build engaging learning environments, and customizing learning experiences using AI apps in order to successfully integrate AI into English classes. It is also recommended for policy makers to establish collaborate learning community amongst the lecturers to facilitate the sharing best practices about AI integration. It is also essential to formulate and establish ethical parameters for the use of AI in ELL class which address the prominence of sustaining human supervision within AI-assisted ELL classroom, data privacy and confidentiality and so forth. ACKNOWLEDGEMENT This manuscript was made possible by the funding by Universitas Mahasaraswati Denpasar under the program of Internal Research Grant 2023. Our appreciation also goes out to all of the esteemed reviewers for their input which improved the quality and rigor of this research. They provided feedbacks on the clarity and coherence on specific sections such as, introduction, literature review, method used and so forth. Furthermore, we also like to thank all of the research participants from Universitas Mahasaraswati Denpasar and GLA University Mathura India for their shared responses, efforts and time throughout this research endeavour. 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