AI Evolving within Educational Landscape

 

 

AI: Friend or Foe in the World of Education

The Great Educational Turning Point

Across classrooms around the world, a quiet revolution is occurring. Artificial intelligence (AI) is gradually integrating into the fabric of teaching and learning sometimes subtly, through tools like adaptive quizzes, and other times more boldly with fully AI-driven tutoring systems. Whether we realise it or not, education is on the brink of a digital transformation that could redefine how we learn, teach, and connect with one another.

For neurodiverse learners those who think, learn, and interact differently due to variations such as autism, ADHD, dyslexia, or dyspraxia, this revolution presents both opportunities and challenges. AI-powered tools are often praised for their ability to personalise learning experiences, but the key question remains: Can they genuinely honour the diversity of the human mind? The real challenge lies not in whether AI should be part of education, but in how we can shape it to support every learner while preserving the essential elements of teaching empathy, creativity, and connection.

The Promise of AI: Empowering Neurodiverse Learners

AI’s greatest strength lies in its ability to personalise learning. For decades, educators have sought to tailor lessons to meet students' diverse needs, but time, resources, and class-size constraints have hindered this goal. However, AI is starting to bridge that gap. With adaptive learning platforms, real-time analytics, and speech-recognition technology, teachers can now gain valuable insights into how each learner absorbs and applies knowledge.

For neurodiverse learners, personalisation can be life-changing. Students with dyslexia can benefit from text-to-speech and predictive spelling tools, which reduce cognitive load and allow them to focus on understanding rather than decoding words. Learners with ADHD can utilise AI-driven focus assistants that break tasks into manageable steps, help track progress, and provide gentle reminders to stay on task. Additionally, emotion-aware tutoring systems can interpret facial expressions and adjust feedback to prevent feelings of frustration or withdrawal.

Research supports the promise of inclusivity in education. Al-Hendawi (2025) found that AI-enhanced teaching strategies lead to improved engagement and autonomy for students with special educational needs. Virtual tools like VRAILEXIA (Tzafilkou & Perifanou, 2024) integrate AI and virtual reality to help dyslexic students through immersive reading environments that adapt to their sensory profiles. Therefore, AI becomes not just a technology, but an ally for accessibility, opening new avenues for learning for students who have often been misunderstood by traditional, one-size-fits-all schooling.

Teachers as Designers of Human-Centred AI

AI can process data, but it cannot love, inspire, or understand human potential. This is where teachers remain irreplaceable. As AI becomes more integrated into classrooms, educators must assume the role of ethical designers, shaping how technology interacts with students. The role of a teacher is evolving from merely transmitting knowledge to creating learning ecosystems where AI acts as a support system rather than a replacement.

In this changing environment, it is essential to establish teacher-friendly structures. Educators need clear frameworks to select, evaluate, and adapt AI tools for inclusive practices. One such foundation is the Universal Design for Learning (UDL) principles developed by CAST in 2018. UDL emphasises multiple means of engagement, representation, and expression, which aligns seamlessly with the inclusive potential of AI. By adopting a human-centred AI approach informed by UDL, we can ensure that neurodiverse learners are not just accommodated but empowered.

Consider Ms Rina, a middle school science teacher in Phnom Penh. She uses an AI writing assistant to help her neurodiverse students craft their research reflections. The AI provides structural support and vocabulary assistance, while Rina adds empathy, feedback, and cultural context. In her classroom, technology enhances rather than replaces her humanity. 

When Algorithms Misunderstand Difference

The same systems that empower individuals can also lead to exclusion. AI decisions are only as unbiased as the data they learn from. If algorithms are trained on limited views of "typical learning," they may pathologise differences. For instance, a neurodiverse child who avoids eye contact might be labelled as disengaged, while a student who needs to move to focus may be seen as off-task.

These algorithmic blind spots underscore the urgent need for ethical guidelines. Armstrong (2017) emphasises that neurodiversity should not be viewed as a deficit, but rather as a valuable form of human variation. When AI fails to recognise this, it can unintentionally reinforce stigma. Additionally, privacy risks are significant; systems that gather behavioural data on neurodiverse learners may inadvertently expose sensitive information about cognitive profiles or diagnoses.

UNESCO (2023) emphasises that schools should view AI as a tool for inclusion rather than a means of surveillance. The future of education relies on our capacity to critically examine AI to ensure that its principles align with human rights, dignity, and diversity.

Stories from the Classroom: Small Shifts, Big Impact

The most profound evidence of AI’s impact often comes not from laboratories, but from classrooms. Take Leo, a 10-year-old student with ADHD. Writing assignments once brought tears and frustration. With an AI planning app, he now breaks essays into colour-coded chunks and uses voice-to-text to capture ideas before they vanish. His teacher reports newfound confidence and creativity — not because the AI taught him differently, but because it gave him space to think differently.

Or Maya, a dyslexic student in secondary school, who uses an AI summarisation tool to distil complex texts. Instead of feeling overwhelmed, she can now discuss themes with peers and engage critically. For her, AI acts as a literacy bridge, not a crutch.

Such stories reveal a critical insight: inclusion does not mean standardisation. It means designing systems that honour the rhythm, pace, and style of every learner’s mind.

The Human Equation: Empathy in the Age of AI

Inclusive education is grounded in empathy through the teacher’s ability to notice struggles and curiosity that technology cannot fully detect.  While AI can analyse patterns, it cannot grasp purpose; it can predict behaviour, but it cannot recognise potential.

The challenge, therefore, is finding a balance. As AI tools become more advanced, educators must be more intentional in their approach. The goal is to build AI-empowered communities that use technology to enrich learning, not replace human experiences.

Empathy also extends to teacher training. Professional development should not focus solely on technical skills but should also include ethical awareness: the ability to question AI decisions, interpret outputs, and involve students, especially those who are neurodiverse, in co-designing solutions. In this way, AI literacy serves as an inclusive pedagogy.

The Way Forward: Building Inclusive AI Literacy

To ensure AI remains a friend, education systems must prioritise AI literacy for inclusion. This literacy involves three interlocking dimensions:

1.    Critical understanding – Teachers and students must grasp how AI systems make decisions and where biases arise.

2.    Creative application – Educators should experiment with AI to enhance flexibility, not conformity, in learning design.

3.    Ethical reflection – Schools must uphold transparency, privacy, and dignity, ensuring that no learner’s data is treated as a commodity.

Governments and teacher education institutions can play a transformative role by embedding inclusive AI ethics and neurodiversity awareness into curriculum frameworks. Educators, technologists, and neurodiverse advocates can collaborate on AI design that incorporates student input.

As CAST (2018) advocates, universal design is not just an educational method but a moral stance: a belief that learning should adapt to people, not the other way around.

Conclusion: The Heart of the Matter

Is AI a friend or foe in education? The answer depends on how we use it. AI is neither a saviour nor a villain; it reflects the intentions of those who control it. When guided by empathy, ethics, and inclusion, AI can serve as a bridge to opportunity, especially for neurodiverse learners whose talents may not be measured by traditional standards.

However, if used carelessly, AI can deepen existing divides, turning data into labels and students into profiles. The challenge ahead is not technological; it is human. We must ensure that every algorithm in the classroom serves a greater purpose: to cultivate curiosity, compassion, and connection. The future of education will not be shaped by code alone, but by the courage of teachers and students to envision a more inclusive world.

 References

Al-Hendawi, M. (2025). Artificial intelligence applications in special education: A systematic literature review (2019–2024). Social Sciences, 14(5), 288. https://doi.org/10.3390/socsci14050288

Armstrong, T. (2017). The power of neurodiversity: Unleashing the advantages of your differently wired brain. Da Capo Lifelong Books.

CAST. (2018). Universal Design for Learning guidelines version 2.2. CAST. https://udlguidelines.cast.org

Tzafilkou, K., & Perifanou, M. (2024). VRAIlexia: A VR and AI system to support dyslexic higher education students. arXiv preprint. https://arxiv.org/abs/2402.01668

UNESCO. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org