The integration of digital technologies into education has transformed language teaching, particularly after the COVID-19 pandemic. One of the most impactful advancements is Generative Artificial Intelligence (GenAI), which presents both opportunities and challenges for English teachers. This article, derived from a study published in Entornos & Contornos, an academic collection produced through a collaboration between CNA and Cambridge, provides a critical overview of the implications of GenAI in English teaching.
THE ROLE OF TECHNOLOGY IN ENGLISH LANGUAGE TEACHING
Before discussing GenAI specifically, it is necessary to contextualize the broader role of digital technologies in language education. Digital tools like interactive whiteboards and educational apps were already playing an increasing role in classrooms before the pandemic. However, the transition to remote teaching accelerated digital adoption, requiring educators to adapt briskly (Pereira et al., 2020).
This shift highlighted the urgent need for teachers to develop digital literacy, including the ability to critically evaluate and integrate technology into pedagogy (Almeida & Alves, 2020).
Despite these advances, many educators initially viewed technology instrumentally, focusing on mastering basic functionalities (Cardoso & Santo, 2020). As integration deepened, concerns emerged regarding ethical implications, particularly in relation to AI. This transition led to a reevaluation of pedagogical frameworks, incorporating models such as Technological Pedagogical Content Knowledge (TPACK) (Mishra & Koehler, 2006) and its evolution into Intelligent-TPACK, which includes AI knowledge as a fundamental aspect of teacher expertise (Celik, 2023).
UNDERSTANDING GENERATIVE AI IN EDUCATION
Generative AI refers to systems capable of generating new content–text, images, music, or code–based on patterns identified in vast datasets (UNESCO, 2023). A prominent example is ChatGPT, which provides personalized learning experiences through chatbots, automated feedback, and simulated conversations.
AI-driven chatbots assess students’ responses in comprehension exercises and suggest tailored learning materials. Similarly, AI-powered writing assistants provide instant feedback on grammar, coherence, and organization. Another advantage is AI’s ability to simulate real-life conversations, allowing students to engage in interactive exchanges. However, while these applications offer valuable support, human interaction remains essential for language development, particularly in cultural competence and pragmatic communication.
NAVIGATING ETHICAL AND PEDADGOGICAL CHALLENGES
Despite its potential, GenAI integration in English teaching presents challenges. One key concern is AI-generated content reliability. AI models produce fluent text but lack true understanding and may generate inaccuracies (OpenAI, 2023). This raises questions about how educators can ensure students critically engage with AI-generated content rather than accepting it as authoritative.
There is also debate about GenAI’s role in assessment. Some educators worry that students may misuse AI to complete assignments without developing writing and analytical skills. This has led to discussions about redesigning assessment methods to focus on higher-order thinking skills–such as creativity, problem-solving, and ethical reasoning–that AI cannot replicate (UNESCO, 2023).
SOCIECONOMIC BARRIERS TO AI ADOPTION IN BRAZIL
While GenAI has pedagogical potential, its implementation in Brazil must be analyzed within a broader socioeconomic context. Despite Brazil’s notable engagement with AI, digital inequalities persist. Approximately 29.4 million Brazilians still lack internet access, with 35.71% of them residing in the Northeast. This digital exclusion poses a major barrier to equitable AI-enhanced education.
The disparity extends to infrastructure and digital literacy.
Schools in wealthier urban centers are more likely to integrate AI tools effectively, while those in disadvantaged areas may struggle with outdated technology and insufficient training. Without targeted policies and investments, the benefits of AI in education risk being concentrated among privileged students, exacerbating inequalities.
To address these challenges, policymakers must prioritize digital inclusion, expanding internet access, providing AI training programs for educators, and integrating AI literacy into curricula. These measures align with the recommendations outlined by UNESCO (2022), which advocate for policies that promote equitable AI access while ensuring ethical and responsible usage.
CULTIVATING TEACHER´S READINESS AND PROFESSIONAL DEVELOPMENT
A crucial factor in AI implementation is teachers’ readiness and willingness to engage with these technologies. Many educators express concerns about AI’s impact on their roles, fearing automation may diminish their authority or lead to student disengagement (Tlili et al., 2023). Resistance often stems from a lack of familiarity with AI’s pedagogical applications and ethical considerations.
The Intelligent-TPACK framework (Celik, 2023) expands on TPACK (Mishra & Koehler, 2006) by incorporating AI-specific knowledge. These domains emphasize that teachers must not only understand AI’s capabilities but also assess its ethical implications, apply AI tools in lesson planning and assessment, and adapt teaching methods according to principles of accountability, transparency, fairness, and inclusiveness.
By fostering AI competency among educators, institutions can ensure AI enhances rather than replaces instruction. Well-trained teachers can act as mediators, guiding students in responsible AI use while reinforcing critical thinking and digital literacy.
AI AND STUDENT ENGAGEMENT
While much discourse on AI in education focuses on teachers, student engagement is equally important. A common assumption is that digital-native students will automatically embrace AI tools; however, some may find AI-powered platforms impersonal, while others may over-rely on AI-generated content without fully developing their language skills.
One key concern is AI potentially diminishing authentic human interaction in language learning. Language acquisition is deeply rooted in social exchange, and while AI can simulate conversations, it lacks spontaneity, cultural nuance, and emotional depth. Educators must balance AI-enhanced learning with peer interaction, classroom discussions, and real-world language practice.
Additionally, students must develop AI literacy to engage critically. Rather than viewing AI as infallible, students should question AI-generated responses, identify potential biases, and cross-reference information with reliable sources. This aligns with the UNESCO (2023) recommendation that AI education should prioritize transparency, fairness, and inclusiveness.
ETHICAL CONSIDERATIONS IN AI-DRIVEN EDUCATION AND A HUMAN-CENTERED APRROACH
Generative AI systems rely on vast datasets, often collecting user inputs for further training. However, ethical and legal dimensions of data collection remain unclear. Many AI models use internet-harvested data without explicit user consent, raising concerns about compliance with Brazil’s General Data Protection Law (LGPD).
AI models storing sensitive student data without adequate security measures could lead to breaches of confidentiality. To mitigate risks, educational institutions must establish guidelines on AI usage, ensuring student and teacher data protection.
Another significant challenge in AI-driven education is algorithmic bias, which occurs when AI-generated content reflects societal stereotypes and systemic inequalities. Since AI models are trained on existing digital content, they often replicate dominant cultural narratives, sometimes at the expense of marginalized perspectives. For instance, AI-generated language examples might favor standard English while underrepresenting non-native speaker usage or regional dialects.
That is why educators must recognize these biases and teach students to critically engage with AI-generated content, promoting diverse linguistic exposure and encouraging critical analysis of AI-generated materials.
SOME LAST WORDS
The integration of Generative AI in English teaching presents opportunities for personalized learning, instant feedback, and simulated language practice. However, its adoption must address ethical concerns such as data privacy, algorithmic bias, and equitable access.
Ultimately, AI should enhance human intelligence rather than replace it. Language learning thrives on human interaction, cultural exchange, and meaningful communication. The future of AI in education lies in its ability to work alongside educators, empowering them to create richer, more inclusive, and ethically sound learning environments.
REFERENCES
Almeida, B. O., & Alves, L. R. G. (2020). Letramento digital em tempos de COVID-19: uma análise da educação no contexto atual. Debates em Educação, 12(28), 1-18. Available at: https://doi.org/10.28998/2175-6600.2020v12n28p1-18 (Accessed on Mar 14, 2025)
Cardoso, A. L.; Santo, E. E. (2020). Literacia digital: um mosaico de experiências do contexto da formação docente. In: Trindade, Sara Dias; Moreira, J. António; Ferreira, António Gomes. Pedagogias Digitais no Ensino Superior. Vol. 8. Coimbra: Edições Almedina.
Celik, I. (2023). Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior, 138, 107468. Available at: https://doi.org/10.1016/j.chb.2022.107468 (Accessed on Mar 14, 2025)
Mishra, T. J., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054.
OpenAI. 2023. Educator considerations for ChatGPT. San Francisco, OpenAI. Available at: https://platform.openai.com/docs/chatgpt-education (Accessed on Mar 14, 2025)
Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4-14.
Tlili, A., Shehata, B., Agyemang Adarkwah, M., Bozkurt, A., Hickey, D. T., Huang, R. and Agyemang, B. What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, Vol. 10, No. 15. Berlin, Springer. Available at: https://doi.org/10.1186/s40561-023-00237-x (Accessed on Mar 14, 2025)
UNESCO. (2022). AI and education: Guidance for policymakers. Paris: UNESCO. Available at: https://unesdoc.unesco.org/ark:/48223/pf0000376709 (Accessed on Mar 14, 2025)
UNESCO. (2023). Guidance for generative AI in education and research. Paris: UNESCO. Available at: https://unesdoc.unesco.org/ark:/48223/pf0000386693_eng (Accessed on Mar 14, 2025)
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