The Changing Landscape of ELT: Past Lessons, Future Visions

The Changing Landscape of ELT: Past Lessons, Future Visions

The Changing Landscape of ELT: Past Lessons, Future Visions

Willy A Renandya & Flora D Floris

Renandya, W. & Floris, F. D. (2024). The changing landscape of ELT: Past lessons, future visions. PASAA, 69, 40‒61.

Abstract

The landscape of English Language Teaching (ELT) has evolved significantly over the past 75 years, marked by major shifts in theoretical, technological, and sociocultural approaches to language teaching and learning. From the dominance of behaviorist methods in the mid-20th century to today’s innovations in digital, tech-mediated language learning, these transformations have created both opportunities and challenges for teachers. The rapid growth of technology, along with the changing status of English as a global language and the evolving goals of language learning, has further reshaped how languages are taught and learned. Yet, amidst these profound changes, the role of teachers remains central. Teachers are tasked not only with adapting evidence-based methods to address the diverse needs of students but also with fostering meaningful interactions, encouraging critical thinking, and maintaining high levels of student engagement. As ELT continues to advance, teachers are called upon to continually reflect on their practices, adopt new evidence-based approaches, and adjust their teaching methods to meet the evolving needs of their students.

1. Introduction

            Over the span of the last seven and a half decades, the landscape of second language teaching and learning has undergone a profound development, characterized by a series of distinct eras that have shaped our pedagogical approaches. Each era has introduced novel theories, methodologies, and technologies that have not only revolutionized the way we teach languages but have also redefined our understanding of the learning process itself. From the grammar-translation method to the communicative approach, and from behaviorism to constructivism, the evolution of language pedagogy highlights the continuous interaction between theory, practice, and the socio-cultural dynamics within the language classroom. These dynamics encompass the diverse social and cultural backgrounds of both learners and teachers, influencing how they approach and engage with the language learning process.

These changes have not only influenced classroom dynamics but have also extended to broader societal and technological shifts, such as the advent of online learning platforms, immersive virtual environments, and the effects of globalization. Social changes, including increased migration, multiculturalism, and the growing demand for English as a global language, have fostered diverse, multilingual learning environments. At the same time, the integration of digital tools has expanded access to language learning beyond traditional classrooms, enabling learners to engage with content from anywhere in the world. As we reflect on the past and present trends in English Language Teaching (ELT), it becomes evident that our understanding of language acquisition continues to evolve, driven by ongoing research, pedagogical experimentation, and adaptation to new technologies and global realities.Bottom of Form

The purpose of this article is to reflect on some of the most distinct eras that many of us have witnessed in the past 75 years and share our thoughts on how key ideas from these eras have contributed to our understanding of what seems to work well (and what does not) in ELT. We also offer a glimpse into the exciting future where the use of technological tools can potentially transform the way English is taught in the classroom.

We begin by examining five distinct eras that have influenced the landscape of ELT, each with its own unique characteristics and contributions. We then discuss the current era, known as the era of digital learning, at greater length because despite the fast-growing research in tech-enhanced language learning, not much is known about its impact on ELT. This is especially true with the latest developments on the use of AI-powered tools in language education, where there is still limited understanding of their long-term effects on teaching practices, student outcomes, and the overall language learning process.

2. The Era of Controlled Language Learning

During the era when controlled learning was in the spotlight, B.F. Skinner emerged as a significant figure, known for his bold statement, “Give me a child and I’ll shape him into anything.” At the core of Skinner’s philosophy was the conviction that learning was primarily influenced by external factors rather than internal learning mechanisms. In Skinner’s view, the child was like a blank page, awaiting the imprint of environmental stimuli to propel their cognitive and linguistic development. Skinner’s theories revolutionized educational psychology, laying the groundwork for behaviorist approaches that dominated pedagogical discourse during his time.

Not surprisingly, this period was characterized by a strong emphasis on behaviorist principles, with methods such as memorization, repetitive drills, and practice characterizing language learning during this period of time. The audio-lingual method, widely employed during the 1960s and 1970s, was one such approach, focusing on rote learning and mechanical repetition to foster language proficiency. While traces of this method still linger in contemporary language classrooms, language educators increasingly recognize the limitations of solely relying on memorization and mechanical practice. Instead, there is a growing emphasis on fostering genuine communication and understanding within meaningful contexts, reflecting a shift towards communicative competence as the primary goal of language learning (Nguyen & Renandya, forthcoming).

Is Skinner’s behaviourist theory still applicable in language learning? While contemporary language educators tend to veer away from embracing Skinner’s theory entirely, we believe that certain aspects of his propositions remain pertinent to language learning. Take repetition, for instance; its significance continues to be universally acknowledged across various learning domains, including language acquisition. However, unlike the rote and mechanical drills associated with Skinnerian practices, today’s language teachers advocate for repetition imbued with mindfulness and significance. Hence, rather than tasking students with mindlessly memorizing lists of isolated words, teachers now advocate for embedding these words within meaningful texts. Through repeated exposure to these words within contextualized settings, learners are more likely to attain a deeper understanding and retention of vocabulary.

3. The Era of Innate Learning

Two prominent linguists in this context are Noam Chomsky and Stephen Krashen. They held the views that humans possess an innate ability to acquire language. When exposed to a linguistically rich context and a motivating language learning environment, language acquisition occurs naturally and seamlessly (Chomsky, 1975; Krashen & Terrell, 1983).  For language teachers, the primary role involves immersing students in engaging and comprehensible target language materials, offering support as necessary, and nurturing students’ intrinsic motivation (Krashen, 1982). This approach emphasizes the importance of creating an atmosphere where learners feel comfortable experimenting with language and making mistakes. Language errors are typically not corrected, as these are considered a natural part of learners’ language learning trajectory.  In addition, the approach recommends incorporating authentic cultural elements into language instruction, believed to be important in enhancing students’ understanding and appreciation of the language they are learning.

Krashen and Terrell’s (1983) Natural Approach aimed to bring innate learning theory into the language classroom. However, its implementation encountered significant challenges from the outset (Terrell, 1982). Firstly, teachers were unaccustomed to an approach that minimized explicit language rule instruction. Secondly, achieving full immersion in the target language posed difficulties, especially in EFL contexts where English exposure is limited. The Natural Approach stressed the importance of providing learners with comprehensible input, advocating for the exposure to vast amounts of meaningful language that they can comprehend.

Yet, striking the right balance between theory and classroom realities proved challenging. Teachers grappled with the shift from traditional grammar-focused teaching to a more holistic, context-driven approach. In EFL settings, where English language instruction occur primarily within classrooms, achieving total immersion akin to natural language environments remains elusive. Teachers navigated this challenge by creating authentic language experiences, leveraging technology, and fostering communication beyond the classroom walls. But with little success. In short, the Natural Approach’s noble intentions encountered practical hurdles, but its core principles continue to influence language teaching methodologies.

In recent times, for example, certain aspects of Krashen’s Input Theory have made their presence felt in language education. Teachers increasingly appreciate the importance of providing students with ample, engaging reading and listening materials that are comprehensible (e.g., Robb & Ewert, 2024). As a result, extensive reading and listening techniques are gaining popularity among instructors. These methods immerse students in the target language environment, offering them opportunities to reap the diverse benefits of such approaches in language acquisition. This transition marks a crucial point in second language instruction, where the focus is shifting towards more holistic language immersion methodologies.

It is worth noting that comprehensible input alone is insufficient to propel language learning (Swain, 1985) . ELT experts such as Schmidt (1990) believe that for language acquisition to flourish, students’ attention needs to be directed towards non-salient features present in the English language (e.g., the tenses, count and uncountable nouns and subjunctive clauses). The rule governing subject-verb agreements, for example, is not easily acquired because this rule may not be present in the native language of the students. Without deliberate focus on this grammatical feature, students may encounter challenges in fully internalizing and integrating it into their linguistic repertoire. Therefore, a targeted emphasis on this rule and other non-salient linguistic features is crucial to facilitate comprehensive language acquisition.

4. The Era of Information Processing

John Anderson’s (1980) ground-breaking information processing theory revolutionized the landscape of language education by offering profound insights into how our brains process linguistic information. The three steps involved in information processing, i.e., encoding, storage, and retrieval became popular during this time. Anderson’s theory paved the way for a significant shift in teaching methodologies, aimed at optimizing language acquisition and retention. His theory prompted language educators to rethink traditional instructional strategies, placing a newfound emphasis on activities that fostered deeper cognitive engagement.

The practical implications of the information processing theory extend to both language and non-language educational settings. In ELT, for example, the theory suggests that students grasp and retain new vocabulary more effectively when they engage in a deeper level of cognitive processing (Anderson, 2013). This involves linking the meanings of unfamiliar words with ones they have already learned, creating mental images through visualization, and consistently applying target words in diverse, meaningful contexts. Similarly, in a reading lesson, teachers can start the session by prompting students to predict the contents of the text based on their existing knowledge. Subsequently, students are encouraged to engage in active inference-making about how various segments of the reading material relate to one another, relate to themselves and to others in the community.

5. The Era of Socio-Cultural Learning

The central figure in this era is Lev Vygotsky (2012), the Russian psychologist, who maintained that learning occurs most effectively within social and cultural contexts, especially when students receive appropriate guidance from more knowledgeable individuals, namely teachers and peers who are more capable. This period saw the term ZPD (Zone of Proximal Development) gain prominence, emphasizing that students thrive in environments where they are surrounded by supportive peers and nurturing educators. These environments, according to Vygotsky and proponents of social learning theories, facilitate students’ optimal learning experiences. Vygotsky’s ideas continue to shape educational practices not only in ELT but also in other educational domains.

Using Vygotsky’s theory in language classrooms is a practical and beneficial approach. Teachers employ a range of group-based learning tasks, such as cooperative activities or collaborative projects, to establish a supportive social learning environment where students can actively learn from their peers. In addition, ELT scholars (e.g., Jacobs & Renandya, 2019) have emphasized the importance of adopting collaborative learning methods to promote diversity and inclusivity in classrooms with students from various ethnic and linguistic backgrounds. For instance, by implementing heterogeneous grouping techniques, students from diverse social and cultural contexts can work together, offering mutual support and enhancing their language learning experiences.

Though feasible, according to Baloche and Brody (2017) and Chakyarkandiyil and Prakasha (2023) implementing student-centered collaborative learning activities presents several challenges for some teachers. Firstly, the shift to the more student-oriented teaching approach might encounter resistance from both the teachers and students who may be more accustomed to more passive, teacher-centred learning approaches. Secondly, facilitating effective collaboration among students demands careful planning and management to ensure that all participants are engaged and contributing meaningfully. Thirdly, accommodating diverse learning styles, personalities, and skill levels within collaborative groups can pose logistical challenges, requiring instructors to employ strategies for differentiation and equitable participation. Overcoming these challenges necessitates a commitment to ongoing professional development, a supportive learning environment, and flexible instructional practices tailored to meet the needs of diverse learners.

6. The Era of Engaged Learning

This is an exciting era that encompasses many of the most beneficial elements from the earlier periods in language education. Engagement, as Mercer and Dörnyei (2020) noted, is key to successful language learning. Language learning is most effective when students are fully engaged on multiple levels—physically, emotionally, intellectually, and socially.

It is not hard to confirm their observation about the importance of learner engagement. Experience tells us that one of the key characteristics of a good language teacher is their ability to engage most, if not all, of their students during a given lesson. In other words, there is very little downtime during the lesson, as students remain actively involved through various tasks, discussions, and activities that sustain their interest and encourage participation. The good language teacher believes that when students are engaged, they are more likely to develop a more positive learning experience, more inclined to put in more efforts in the learning process, and more willing to invest more time doing autonomous learning beyond the classroom. Repeated observations show that engaged students shine in the language classroom and are more successful in developing a higher level of proficiency in the target language (Mercer & Dörnyei, 2020).

7. The Era of Digital Learning

This era is still at its infancy but language teachers are already embracing tech-mediated learning approaches. Tech tools such as Google Translate, Text-to-Speech apps, automated feedback technologies, online extensive reading and listening programmes, for example, have made their inroads in the language classroom.

Modern classrooms today include a wide range of technological tools and resources, which have altered the dynamics of language learning. Teachers have embraced the digital revolution to better engage students, track their progress, and improve overall learning results. One notable development in recent years has been the incorporation of Artificial Intelligence (AI)-powered systems that provide individualized teaching materials, automated feedback, and targeted instruction, which could potentially increase the impact of technology on language education.

The impact of adding technology into language training is currently being closely examined by educational and ELT academics (Kessler, 2022; Zhao & Lai, 2023). Some studies have looked at how technology affects classroom dynamics (for example, how it can boost the amount and quality of student interaction), levels of student motivation, access to authentic language learning materials and tasks, and access to more engaging and comprehensible languages. While the research findings are far from clear, most experts appear to agree that technology-enabled training can provide various benefits

7.1 Benefits of Tech-Enhanced Learning

In the following section, we discuss a range of educational benefits that have been well-documented in academic research and literature (e.g., Hamilton, 2022):

A.     Lightening Teacher Workload and Enhancing Teaching Quality

Technology helps teachers streamline administrative tasks, giving them more time to focus on effective instruction. For instance, instead of manually recording attendance, teachers can utilize digital attendance systems integrated into Learning Management Systems (LMS) such as Google Classroom, Canvas, Blackboard, Moodle, or Microsoft Teams, which automatically track and log student participation. Beyond attendance, features such as online grade books, automated quizzes, and assignment trackers allow teachers to effortlessly assign, grade, organize, and offer feedback on students’ work. In addition, tools such as plagiarism checkers (e.g. Turnitin) and collaborative platforms (e.g., Google Docs) enable more efficient evaluation and classroom collaboration. All this data can be easily shared with parents and school administrators, allowing teachers to dedicate more energy to teaching and interacting with students.

B.     Increasing Student Motivation and Engagement

Technology-based activities naturally resonate with students because they match the digital habits and preferences of today’s learners. For example, students generally find multimedia and interactive teaching materials much more captivating than traditional printed texts. By integrating game-like learning tools such as Kahoot, Quizlet, Quizizz, and Mentimeter, teachers can create a more dynamic and lively classroom atmosphere. Additionally, using virtual simulations, videos, and interactive quizzes can further encourage student participation. This enhanced tech-driven engagement can lead to greater motivation and a more enjoyable, immersive language learning experience, making lessons more emotionally appealing and memorable.

C.     Enhancing Student Engagement with Interactive Tools

Interactive tools can promote active participation, boosting student engagement and improving comprehension and retention of language concepts. Tools like Padlet, Mentimeter, and Poll Everywhere students to share their thoughts before, during, and after lessons, creating a more dynamic classroom environment. Additionally, platforms such as Peardeck, Nearpod, Slidesgo, and Genial.ly offer interactive slide presentations that engage learners, making lessons more interactive than traditional teacher-led presentations.

Technology also allows teachers to create tailored texts and tasks that meet individual student needs, ensuring instruction aligns with their proficiency levels, learning pace, and preferred styles. AI-powered tools like Twee and MyLessonPal support differentiated instruction by helping teachers plan, deliver, and assess customized lessons, ensuring individual students can receive targeted support.

D.     Providing Immediate, Personalized Feedback

Tech tools also provide instant feedback on student work, enabling targeted improvements and individualized support. This real-time feedback accelerates language acquisition and proficiency development. Popular tools like Grammarly help students with writing corrections. Similarly, speech analysis apps like Stimuler and ELSA Speak improve pronunciation, intonation, vocabulary, grammar, and fluency.

 7.2 Principles for Evaluating Tech Tools

With hundreds of tech tools available and new ones emerging daily, language educators must stay informed and select tools that genuinely support language teaching and enhance language learning. But how can educators determine which tools are best suited for teaching, learning, and assessing students?

We suggest consideration of two sets of principles in language teaching. The first set is derived from general education principles, which are broad, well-established guidelines applicable across various subjects and disciplines. These principles include fostering adaptive teaching and learning, nurturing critical thinking, promoting student engagement, and encouraging collaborative learning. While valuable, these general education principles are not specifically tailored to the unique challenges of language learning.

The second set, however, is grounded in second language learning principles, which focus directly on the development of language proficiency. These principles address areas such as comprehensible input, interaction, feedback, and the role of meaningful context in language acquisition. They emphasize strategies like scaffolding, promoting communicative competence, and integrating language skills.

Although there is a certain degree of overlap between these two sets, language teachers should prioritize the second set of principles. This is because they have direct relevance to the development of students’ language proficiency and are specifically designed to support learners in acquiring, using, and mastering a new language. By focusing more on these principles, teachers can create more effective language learning environments that better meet the linguistic needs of their students.

A.     General Education Principles

The principles for evaluating technology tools in education include assessing whether the tool improves student participation, motivation, and engagement, while promoting deeper learning. It should facilitate interactions between students and teachers, help clarify difficult concepts, and enable monitoring and reflection on learning. The tool should also provide opportunities for students to use different intelligences, connect education with the real world, and increase teaching effectiveness. In addition, it is important to ensure that the necessary resources are available and the tool is user-friendly.

The questions listed below can be used to assess the suitability of a tech tool. If the responses to these questions are largely positive, the tech tool can be tried out in a controlled setting to see if it works well in practice. This trial phase allows teachers to observe how the tool performs in real classroom settings, assess its impact on student learning, and identify any potential challenges. Feedback from both students and teachers during this period can provide valuable insights, helping to refine the tool’s use or make necessary adjustments before wider implementation.

  • Does the tech tool improve student participation?
  • Does it increase learner motivation and engagement?
  • Does it promote deeper learning?
  • Does it facilitate student-student and student-teacher interactions?
  • Does it provide students with opportunities to utilize their full learning capacities?
  • Does it help clarify hard-to-explain concepts?
  • Does it allow teachers and students to monitor, evaluate, and reflect on students’ learning?
  • Does it support teachers in personalizing learning for individual students?
  • Does it help teachers save time on administrative tasks?
  • Does it support teachers’ professional development?
  • Does it link education with the world beyond?
  • Do students and schools have the necessary hardware, software, and bandwidth?

B.     Second Language Learning Principles

Second Language learning principles focus on how a tech tool supports the development of language skills (Renandya et al., 2023). It should provide students with rich, meaningful, and comprehensible language input, offering multiple exposures to target language features. The tool should encourage noticing of key language elements and provide frequent, meaningful practice of previously learned language. It should promote multimodal processing of language materials and encourage students to draw on abilities from other languages. In addition, the tool should improve communication skills across speaking, writing, reading, and listening, raise awareness of the social purposes of language use, and build skills for students to become self-directed, independent learners. Finally, it should expose students to a broader range of language varieties.

The following questions can be used to assess the suitability of a tech tool in supporting students’ language proficiency development. If the responses show the tool meets these criteria described above, it can be tested in a language learning setting. We encourage teachers to design a small-scale action research project to seek students’ views on whether the tool can actually enhance language proficiency. If the feedback is positive, the tool can be considered for broader adoption.

  • Does the tech tool provide students with rich, interesting, meaningful and comprehensible language input?
  • Does it provide students with multiple exposures to target language features?
  • Does it promote noticing of important target language features?
  • Does it provide students with frequent and meaningful practice of previously learned language?
  • Does it promote multimodal processing of target language materials?
  • Does it encourage students to access their abilities in other languages?
  • Does it improve students’ communication skills (i.e., speaking, writing, reading and listening)?
  • Does it create greater awareness of the social purposes of language use?
  • Does it build skills for greater student independence, or does language acquisition stop if the tool is not used?
  • Does it provide exposure to a wider range of language varieties?

7.3 AI-Supported Language Teaching and Learning

As noted earlier, there is considerable discussion in the ELT professional literature about the role of AI in language teaching and learning. However, many ELT practitioners are still grappling with the question of how to effectively implement these technologies in the classroom. While AI has great potential, its full impact on ELT is still poorly understood, and it will take time to fully understand its advantages and challenges. Below, we highlight several important implications of AI’s growing use for language teachers.

A.     AI Redefines the Role of Teachers

AI has significantly transformed the role of teachers in language education, shifting their focus from routine tasks to more strategic responsibilities. As noted by Adiguzel et al. (2023), AI automation reduces administrative workloads, such as grading and attendance, allowing teachers to spend more time on teaching, engaging with students, and creating tailored lesson plans that address individual needs. Additionally, the time saved enables teachers to explore innovative teaching methods and technologies, which can lead to the creation of more engaging and dynamic classrooms (Adiguzel et al., 2023).

AI tools also provide data-driven insights into learners’ progress, challenges, and preferences. To effectively use these insights, teachers must take on new roles as interpreters and managers of AI-generated data. AI-assisted presentation platform in Chen et al.’s study (2022), for example, offers detailed assessments on key components of oral presentations, such as pronunciation accuracy, fluency, vocal fillers, and facial emotions. Teachers, as interpreters of this data, play a crucial role in using these insights to identify areas for improvement and develop targeted learning materials and strategies. While AI automates repetitive tasks and initial feedback, teachers remain essential for contextualizing and integrating this information into meaningful, learner-centered instruction.

While AI improves efficiency and personalization in language learning, it is not a replacement for time-honored teaching methods. Instead, it should complement these methods by supporting teachers in creating effective learning environments. Language learning remains a fundamentally social process, relying on meaningful interactions—such as conversations and collaborative activities—to foster communication skills, cultural awareness, and emotional intelligence (van Lier, 2006). Teachers play a key role in facilitating these interactions by creating supportive environments that reduce anxiety, build confidence, and help students progress (Dörnyei, 2014). Their ability to adapt to emotional and situational needs ensures they remain indispensable for guiding students through language learning. Thus, thoughtful integration of AI and human instruction is crucial to maintaining the interactive and human-focused nature of education

B. AI Transforms Classroom Dynamics

AI tools have reshaped classroom dynamics, creating more interactive and engaging learning environments. Technologies such as chatbots and Embodied Conversational Agents (ECAs) enable students to practice language in realistic contexts, helping them build communicative competence, confidence, and fluency. For example, a study by Ericsson et al. (2024) involving 22 Swedish middle school students showed that using ECAs in everyday scenarios increased both satisfaction and emotional engagement. This demonstrates how AI can make language learning more motivating and enjoyable.

AI also enhances classroom interaction by providing real-time, individualized feedback. Unlike traditional methods, where feedback is often delayed, AI tools such as Pigai deliver diagnostic insights within 1.2 seconds, enabling students to quickly address writing errors and improve their skills (Yang et al., 2023). This immediacy fosters more efficient learning by allowing students to refine their work promptly.

Inclusivity and equity remain critical considerations in AI-enhanced classrooms. AI has the potential to bridge gaps in access to language learning resources by addressing diverse needs, including those of learners with special needs. For instance, LaMPost, a tool designed for adults with dyslexia, assists with written communication by outlining ideas, generating subject lines, and suggesting tone and style improvements (Goodman et al., 2024). Similarly, AI tools like ChatGPT cater to learners with varying levels of English proficiency. According to Wang (2024), non-native speakers found ChatGPT particularly effective in improving fluency and clarity, while native speakers benefited from enhanced writing efficiency and reduced stress through features that streamline idea organization. By accommodating diverse learner needs, these AI technologies promote greater participation and accessibility for all.

Despite its benefits, AI cannot replace the social and empathetic aspects of human interaction that are essential for language acquisition. Teachers remain indispensable in fostering meaningful connections, cultural understanding, and emotional support in the classroom (van Lier, 2006). Luckin and Cukurova (2019) for example stress that AI should complement human-centered teaching by, preserving, rather than replacing, the unique qualities of human thinking, emotions, and social skills.. These elements are particularly crucial in language learning, where thoughtful interactions and social skills play a central role in developing communicative competence.

C. AI Promotes Learner Autonomy

AI tools have become invaluable in fostering learner autonomy by enabling students to practice independently and tailor their learning experiences to their specific needs. Unlike general technologies, AI-driven applications adapt dynamically to individual learner progress, offering real-time adjustments to learning pathways. For example, tools like Duolingo analyze user performance to provide personalized exercises, helping students focus on areas for improvement (Munday, 2015). This adaptability empowers learners to take greater ownership of their learning process, choosing when, where, and how they engage with language tasks.

AI’s dynamic adaptability ensures an optimal balance between challenge and support, maintaining student motivation. Adaptive learning platforms like NoRedInk exemplify this by adjusting exercises based on students’ responses, aligning tasks with their individual needs and abilities (Snowe, 2017). By tailoring learning experiences in this way, such tools aim to keep learners within their Zone of Proximal Development (ZPD) where meaningful progress occurs when learners are challenged slightly beyond their current abilities while receiving the necessary support to succeed.

However, while AI tools foster autonomy, teachers must ensure that this independence does not lead to isolation. Collaborative, human-centered learning remains vital for developing social and communicative competence (van Lier, 2006). Teachers should guide students in using AI tools effectively as a supplement to classroom interaction and peer collaboration, reinforcing the human connection that is essential for meaningful language learning.

D. AI Introduces New Challenges

While AI offers substantial benefits in language education, it also presents significant challenges that teachers must address. These challenges span pedagogical, ethical, and linguistic dimensions, requiring critical evaluation and thoughtful integration into ELT.

Over-reliance on AI poses significant challenges, particularly for developing critical thinking and spontaneous language production. Liu et al. (2024) point out that generative AI tools often provide pre-formulated responses, which lack the depth and originality needed for reflective thinking or novel ideas. Heavy dependence on AI for tasks like text generation can limit students’ ability to form their own ideas and arguments, hindering the development of essential cognitive skills. The convenience of AI-generated solutions may discourage deeper analysis and critical engagement. Additionally, relying on AI reduces opportunities for practicing spontaneous language production, making it harder for students to express their thoughts fluently and independently. Effective speaking requires critical and creative thinking, and overuse of AI may weaken these skills,  as students may become dependent on AI-generated content instead of developing their own ideas.

AI’s reliance on extensive learner data raises ethical concerns, particularly around data privacy and inclusivity (Nguyen et al., 2023). Many AI tools collect and analyze performance data to deliver personalized feedback, creating risks of data misuse or breaches.  Inclusivity is another challenge, as many AI algorithms are based on limited datasets that may not represent the full range of cultural and linguistic diversity. This can result in biases in tasks such as speech recognition, question generation, and essay grading, potentially leading to inaccurate or unfair outcomes for certain linguistic groups.

Addressing these challenges requires a balanced approach that makes the most of AI’s strengths while mitigating its limitations. Teachers must evaluate AI tools carefully, promote ethical practices, and complement AI-driven learning with human-centered teaching to create an effective language learning environment.

E. Calls for Balanced Integration in ELT

The integration of AI into ELT demands careful planning and implementation. To ensure AI enhances learning without replacing human interaction, teachers must balance AI-driven tools with communicative teaching approaches. AI can handle repetitive tasks, provide real-time feedback, and adapt to individual learner needs, but it cannot replace the role of teachers.

For example, AI systems are good at correcting errors and giving general feedback in writing tasks, but they often fail to provide suggestions that consider the different contexts or purposes of writing. Teachers can address this limitation by providing detailed explanations and examples, enabling students to understand how to apply feedback more effectively across different contexts. Additionally, while AI focuses primarily on correcting mechanical errors, such as grammar and syntax, teachers play a crucial role in guiding students in broader aspects of writing, including organization, coherence, and argumentation. These are key aspects of advanced language development that AI tools often cannot fully address.

Equipping teachers with the skills to use AI tools effectively is also crucial for successful integration in language education. Professional development programs should introduce teachers to relevant AI technologies, emphasizing their practical applications in enhancing teaching and learning. Showcasing tools like AI-supported features in Google Docs, for example, can demonstrate how AI complements existing workflows, helping teachers see AI as a valuable addition rather than a replacement for traditional methods. Additionally, tailoring these programs to the specific needs and contexts of teachers can help them effectively integrate AI into lesson plans while maintaining the importance of human interaction in language teaching.

Teachers need clear evaluation frameworks to effectively and ethically integrate AI tools into their teaching practices. Several frameworks already exist to guide teachers in assessing AI technologies and their alignment with educational goals. For instance, the AI-TPACK framework provides a structured approach for aligning AI technologies with pedagogical and content knowledge (Ning et al., 2024). Similarly, UNESCO’s AI Competency Framework outlines key competencies for teachers to evaluate and use AI responsibly, ensuring these tools support pedagogical and ethical standards (Mutlu et al., 2024). These frameworks help teachers assess how AI can effectively support teaching and learning.

As AI technologies continue to evolve, it is important to regularly reassess their impact on language learning to ensure they remain effective and aligned with educational goals. Regular evaluation helps teachers to monitor student progress, gather feedback, and adapt the use of AI tools to meet diverse and changing needs. It also enables them to adapt their teaching strategies, ensuring relevance with the fast-paced advancements in AI technologies.

By taking a balanced approach, providing teachers with professional development program, and regularly evaluating AI tools, teachers can use AI in ELT to improve learning outcomes while keeping the human connection central to language development. Thoughtful and balanced integrations allow AI to support education, benefiting both students and teachers.

8. Conclusion

            As we prepare for the next phase of change in language education, it is essential to keep reflecting on our teaching philosophy and pedagogical practices. Are our teaching methods rooted in outdated pedagogical principles from previous eras? Are we regularly revising our teaching approaches based on recent developments in second language education research? Are we open to making significant changes in how we teach and assess students? Have we been utilizing digital technology to meet the diverse needs and interests of our students? These are critical questions that contemporary language educators must consider.

About the Author

Willy A. Renandya is a language teacher educator with extensive teaching experience in Asia. His research focuses on L2 pedagogy with a special interest in extensive reading and listening. He currently teaches language education courses at the National Institute of Education, Nanyang Technological University, SEAMEO RELC and SUSS. He is also a visiting professor at Wuhan University and serves as a research fellow at the University of Economics H Chi Minh City.

Flora Debora Floris is a senior lecturer at the English Department of Petra Christian University, Indonesia. Her research interests include language teacher professional development, the integration of technology in language learning, and the study of English as an international language. Her publications reflect her commitment to bridging theory and practice in language education.

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