Introduction
Artificial intelligence (AI) continues to permeate educational contexts globally, notably impacting English Language Teaching (ELT) by introducing AI-driven methods to enhance learning accessibility and adaptability (Szabó & Szoke, 2024). By employing a dialogic framework, this paper examines the potential of generative AI (GenAI) to foster inclusivity and learner autonomy. While AI-driven applications in language learning have garnered enthusiasm, they have also raised concerns, particularly around accessibility and equitable technology distribution. This article critically assesses the benefits of GenAI in ELT, including promoting personalized learning and catering to diverse learning needs, while acknowledging the significant barriers imposed by the digital divide. The dialogue presented here underscores a balanced approach to GenAI integration in education, advocating for its use as a tool to bridge rather than exacerbate educational inequities.
Theoretical Background and Scope
Historically, AI’s potential to transform various sectors, including education, has been realized through advancements in machine learning and neural network technologies. GenAI, a specialized subset of AI, is notable for its ability to produce creative content such as text, images, and sound. In ELT, GenAI applications are particularly appealing for their ability to generate human-like responses and provide interactive learning experiences tailored to individual student needs (Jeon et al., 2023). However, this emerging technology demands cautious adoption, given concerns about its accuracy and reliability (Benson, 2016). GenAI's capacity to create individualized learning pathways and assist learners with disabilities holds considerable promise for making language learning more accessible. Nonetheless, these tools are constrained by limited access in lower socio-economic regions, thus perpetuating a digital divide that remains a pressing issue (Lucendo-Monedero et al., 2019).
AI’s Role in Fostering Autonomy and Personalized Learning
The concept of learner autonomy, defined as students' ability to direct their own educational experience, aligns closely with constructivist learning theories that emphasize the student’s central role in knowledge acquisition (Holec, 1981). GenAI’s utility in fostering autonomy is seen in its ability to create personalized learning plans and provide immediate feedback. Tools like ChatGPT and Khanmigo offer adaptive scaffolding that supports self-directed study, allowing learners to develop critical skills independently (Cambridge Life Competencies Framework, 2020). Through features like inquiry-based prompts, GenAI encourages students to ask questions and engage with material on a deeper level, reinforcing the principles of constructivism by adapting instruction to the learner’s current knowledge and needs (Szabó & Csépes, 2023).
However, the relationship between GenAI tools and learner autonomy is not without complications. Excessive reliance on automated responses can stifle critical thinking and problem-solving skills, as students may begin to depend heavily on AI for guidance rather than cultivating their analytical abilities (Anthonysamy et al., 2020). This potential pitfall raises questions about the true extent of autonomy that GenAI can offer and suggests a need for educators to balance AI-assisted learning with traditional teaching methods that foster self-regulated learning and critical reflection.
Inclusivity and Accessibility: GenAI as a Tool for Differentiation
Inclusivity in education emphasizes equal access to learning resources for all students, regardless of background or ability (United Nations, 2016). GenAI can support inclusivity by offering tailored solutions for students with disabilities. For example, text-to-speech and speech-to-text technologies assist visually impaired students and those with dyslexia, creating a more inclusive classroom environment. Tools like Microsoft’s Immersive Reader provide adjustable text options, including background colors and font adaptations, which help students with reading difficulties engage with content at their own pace (Edmett et al., 2023). These features exemplify how GenAI can empower educators to implement differentiated instruction effectively, allowing students to interact with material in ways that best support their individual learning needs.
Nonetheless, the assumption that GenAI is universally accessible overlooks significant disparities in technological access, particularly in the Global South. In countries where internet connectivity is limited, students are often unable to leverage GenAI tools effectively, thus widening the educational gap between socio-economic groups (Ashrani, 2021). The digital divide remains a significant barrier to inclusive learning, as unequal access to AI tools means that only certain populations benefit from the personalized learning opportunities that GenAI can provide (Anderson & Perrin, 2018).
Digital Divide and Socioeconomic Challenges
The digital divide represents a critical limitation in the adoption of AI in education, as students without consistent access to high-speed internet and digital devices are left at a disadvantage (Dakakni & Safa, 2023). This inequity is especially pronounced in rural areas and low-income communities, where access to advanced digital tools is often limited or non-existent (Lucendo-Monedero et al., 2019). As a result, GenAI's potential to foster inclusivity and personalized learning cannot be fully realized for all students, creating a widening gap between those who can and cannot leverage these technologies in their education.
This divide has implications not only for students’ immediate learning outcomes but also for their long-term educational and career opportunities. Students with limited access to GenAI tools are likely to experience lower levels of engagement and motivation in their studies, further entrenching socio-economic disparities. Addressing this divide requires systemic changes at both governmental and institutional levels to ensure equitable access to technology across diverse regions (Hockley, 2014).
Potential for Adaptive Learning and Critical Limitations of GenAI
The adaptability of GenAI is often cited as one of its greatest strengths, as it can analyze individual learning behaviors and provide tailored recommendations for improvement. However, GenAI’s reliance on algorithms raises questions about its capacity to support meaningful and nuanced interactions, which are essential for language learning. Unlike human instructors, AI lacks the ability to interpret non-verbal cues or provide culturally responsive feedback, elements that are crucial for fostering communicative competence in language learners (Bartle, 2015). Thus, while GenAI can offer personalized recommendations based on learning data, it remains limited in its ability to replicate the dynamic and interactive nature of human instruction.
Additionally, GenAI tools like ChatGPT, which often “hallucinate” by generating false or misleading information, necessitate a high level of digital literacy from students and educators alike. Without critical digital literacy skills, students may struggle to discern reliable information from inaccuracies, potentially undermining their trust in educational resources and their ability to navigate digital learning environments effectively (Cambridge Life Competencies Framework, 2020). This underscores the importance of incorporating digital literacy education alongside GenAI, ensuring that students can engage with these tools critically and responsibly.
The Way Forward: Balancing Technology and Human-Centric Learning
As educational institutions increasingly integrate GenAI tools into language learning, it is crucial to adopt a balanced approach that emphasizes both the benefits and limitations of this technology. While GenAI can undoubtedly enhance accessibility and personalized learning, educators must remain vigilant about the potential risks associated with over-reliance on these tools. Supporting students in developing digital literacy and critical thinking skills is essential for fostering true learner autonomy and ensuring that AI serves as a complement rather than a replacement for human-centered education (Anthonysamy et al., 2020).
In conclusion, GenAI holds substantial potential to promote autonomy and inclusivity in language teaching, but its efficacy is closely tied to equitable access and responsible usage. Policymakers and educators must collaborate to bridge the digital divide and establish frameworks that support inclusive and adaptive learning environments. By combining GenAI with a commitment to critical pedagogy and digital literacy, educational institutions can help prepare students for a technologically advanced future that is both inclusive and empowering.
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