Ameliorating AI-driven pressures in educational settings: evidence-based strategies for ELT managers, teachers, and students in a digital learning ecosystem

• In Event: Navigating the Intersection of Politics, Technology, and Education in the Middle East and North Africa Region

Proposal

In an era marked by rapid technological advancements, integrating Artificial Intelligence (AI) into educational environments is transforming the landscape of English Language Teaching (ELT). While AI offers promising opportunities for enhancing pedagogical practices, it simultaneously introduces new pressures for students, teachers, and administrators. AI pressures in educational settings refer to the stress, anxiety, and tension experienced by educators, students, and administrators due to the pervasive influence of AI systems on performance expectations, ethical considerations, adaptation to new technologies, and economic constraints. Addressing these pressures is critical as they can undermine the positive potential of AI and exacerbate inequalities within the educational system. AI pressure manifests in various ways, including the strain to meet AI-driven benchmarks, navigate the moral dilemmas posed by algorithmic decision-making, adapt to rapidly evolving technological tools, and manage the financial implications of implementing AI systems. The paper critically examines AI-driven pressures, and suggests evidence-based strategies to alleviate their impacts on the digital learning ecosystem, emphasizing equity and inclusive educational practices.
The study is relevant to the theme of the CIES 2025 conference: "Envisioning Education in a Digital Society," while focusing on the junction of AI with education in a context more characterized by technological innovation and digital transformation. These findings suggest the need to develop strategies to deal with the pressures and strains of AI. When considering ELT, language acquisition becomes very much implicated in the cultural and socio-economic parameters underpinning the very framework of language teaching.
According to the regional survey conducted as part of this study across five countries involving 300 ELT professionals, 78% reported increased stress due to the rapid introduction of AI technologies, with 62% expressing concern over a deepening digital divide in their classrooms. These statistics underscore the urgency of devising mechanisms that address the challenges associated with AI technologies. These challenges are particularly pertinent in ELT environments where language acquisition is culturally and socio-economically rooted.
The theoretical framework described in the study draws on critical pedagogy and sociocultural theories, arguing that technology mediates educational experiences and outcomes. The study's overarching context for the discussion on AI-driven challenge is the conversation on digitization in education and the literature—present debates around its ethical, social, and pedagogical effects related to AI integration. In particular, the study focuses on "AI pressures". The critical probing of the tension places the study within ELT's linguistic and geopolitical context to address the problems present for language educators and learners within various educational environments.
The research follows a mixed-method design to understand what pressures these AI technologies can pose to various stakeholders. The instruments include qualitative interviews with 50 ELT managers and teachers across different regions of the Middle East and North Africa (MENA), alongside the quantitative analysis of student performance data from 10 AI-enhanced classrooms in various institutions regionally. Together, these methods provide a robust triangulation of data, ensuring a comprehensive understanding of the impact of AI technologies in diverse educational contexts. While AI-enhanced assessments improve efficiency and personalized learning, 45% of students reported increased anxiety, highlighting a trade-off between academic performance and emotional well-being. Teachers identified job insecurity and upskilling demands as the critical pressures, and the challenge of balancing AI integration with human oversight for managers. The study offers strategies to mitigate these pressures, promoting a balanced approach to AI adoption in education.
A key finding of the study is to identify strategies that ELT professionals use to address AI-related challenges. Following the training on AI literacy, teachers enhanced their confidence by 30%, used AI for differentiated instruction, and created peer-support networks. Managers balanced AI automation with human oversight, implemented ongoing AI training, and maintained feedback loops with system developers. Students harnessed assessment adaptive learning technologies, which reduced the achievement gap by 22%, in managing AI-enhanced assessments through time and a growth mindset. Implementing collaborative digital platforms yielded 35% increases in student engagement, where students can engage their peers collaboratively with minimal chances of being marginalized.
The significance of the study is in the scholarly contribution: it sheds light on original insights about how AI-driven technologies are reconfiguring the ELT landscape. It challenges the current assumptions of unqualified benefits for AI in education on a broader basis, considering the opportunities and risks these technologies entail. Teacher training in AI literacy, adaptability technologies to foster personalization in student learning, and the combination of AI as a support tool in diversified educational contexts are some of the evidence-based strategies focused on which can enhance the theoretical understanding of AI in education.
Further, it aligns with the agenda on sustainable development goals by the United Nations, especially in its mission themes and imperatives that engage equity and inclusion. On the other side, the study addresses AI leaving more gaps in terms of access to education and learning. The strategies mentioned entail a balanced approach to AI integration, ensuring all learners benefit equally from technological advances. The study recommends boosting AI literacy through professional development, including adaptive technologies to leverage achievement gaps, and balancing AI through the human gaze. Limitations exist in that the focus of the study is within specific contexts; thus, the generalizability of the findings may be challenged. The future area of research should expand these strategies across diverse educational environments to validate their applicability.
The researchers are further developing an AI system/robot mobile application for students, teachers, and education administrators to alleviate these AI pressures. The robot will provide personalized support to individual students, reduce pressure, and try to devise adaptive learning environments. This solution will integrate AI in a supportive role, thus aiming to balance between human oversight and technological advancement. The prime motto is to increase student engagement, teacher effectiveness, and administrator efficiency. The researchers and the scholars are patenting this robot; it is highly optimistic that this will be a remarkable invention and help substantially ease the challenges and strains of artificial intelligence in learning.

Authors

• SYED NAEEM AHMED, Royal Commission Colleges & Institutes

• Shafiq ur Rehman, University of Doha for Science & Technology

• Heena Amjad, Al Khaleej Training and Education @ King Saud University

• Najia Nazir, Yanbu Industrial College