From Chalkboards to Chatbots: Insights from My Journey into the AI Future of Education

From Chalkboards to Chatbots: Insights from My Journey into the AI Future of Education

By Farhad Reyazat – PhD in Risk Management

Author’s Profile as a Fintech Entrepreneur and Academic

Citation: F. Reyazat (2025) “From Chalkboards to Chatbots: Insights from My Journey into the AI Future of Education.” Dr. Farhad Reyazat, REYAZAT.COM, May 2025, www.reyazat.com/2025/05/21/insights-from-my-journey-into-the-ai-future-of-education/.

In today’s rapidly evolving technological landscape, the intersection of artificial intelligence (AI) and education is not just a future possibility—it is already here, reshaping how we teach, learn, and think about learning itself.

As someone who has had a long academic life at different universities, including the University of Oxford, and spent 20 years lecturing at universities across Europe and the Middle East, and who has also been a tech entrepreneur for more than two decades, I have witnessed the tectonic shifts in education from multiple vantage points. Today, as the founder of an AI company, I find myself at the very heart of this educational transformation.

In recent years, I’ve spoken with professors at MIT, Oxford, Southampton, and Cambridge, as well as with many AI entrepreneurs building the future of learning. These conversations and my experiences as a teacher and innovator have convinced me that we are on the brink of an unprecedented revolution in education.

From Fear to Opportunity: The AI-Education Paradox

Public discourse around AI in education often starts with fear, concerns that students will cheat, write essays with ChatGPT, or skip the learning process altogether. But this is a narrow view.

Yes, AI brings challenges. But used responsibly, it offers a once-in-a-century opportunity to build the most personalized, equitable, and effective education system humanity has ever known.

Imagine a world where:

• Every student has access to a personal tutor, tailored to their pace, style, interests, and cultural context.
• Teachers are relieved from repetitive tasks, allowing more focus on mentoring, empathy, and creativity.
• Students in rural Kenya or small towns in Iran receive the same learning support as those in New York or London.

This vision is no longer theoretical. It is taking shape now.

The Two Sigma Problem Solved?

Benjamin Bloom’s famous Two Sigma Problem (1984) revealed that students who received one-on-one tutoring performed two standard deviations better than those in standard classrooms. In other words, personal instruction could turn an average student into an exceptional one.

But the problem was always scale. How do you give every student a personal tutor?

Thanks to recent breakthroughs in AI, huge language models (LLMs), multimodal systems, and adaptive learning engines, this once unsolvable problem may finally have an answer.

AI in Action: Beyond Buzzwords

Several AI-driven platforms are already transforming how students learn:

• Squirrel AI (China): Analyzing student responses in real-time generates fully personalized learning paths, adapting difficulty and content dynamically. In pilot studies, test scores improved by 20–40%.
• Century Tech (UK): Built with cognitive science at its core, Century’s AI engine continuously tailors resources to student needs and provides teachers with actionable insights. UK schools using Century report a 30% reduction in teacher workload and significant performance improvements.
• Querium (USA): Focused on STEM education, Querium uses predictive AI to detect mistakes before they happen, enabling real-time intervention. It has helped underperforming students complete courses 20% faster than national averages.
• School AI & Eduaide.AI: These tools empower teachers by creating lesson plans, suggesting differentiated content for neurodiverse learners, and automating administrative burdens.
• Character.AI, Replika, and other conversational tools allow students to interact with virtual historical figures, collaborate on creative writing, or simulate real-world debates, enhancing confidence and expression.

These tools are more than just chatbots or digital textbooks. They begin a paradigm shift: from rigid curricula to responsive, inclusive, student-led learning experiences.

Contextual Learning: Localized, Individualized

One of AI’s most profound capabilities is its ability to adapt to individual students and their cultural, geographic, and socio-economic contexts.

A student in rural India may need AI-driven English language support, while a refugee child in Lebanon may benefit from trauma-sensitive learning interventions. AI can support early numeracy in Ghana and may enhance bilingual STEM instruction in Sweden.

Each country, community, and classroom faces unique educational challenges. AI can tailor content and delivery style accordingly, preparing students not just to pass exams, but to navigate the specific challenges of their local environments—climate adaptation, digital economies, political literacy, or health education.

Bridging the Digital Divide

Despite rising global connectivity, education inequality remains a persistent barrier. According to UNESCO, over 244 million children and adolescents are still out of school globally, many due to a lack of access, resources, or qualified teachers.

AI can help bridge this gap by:

• Offering low-cost, multilingual learning experiences via mobile devices.
• Assisting teachers in low-resource settings with lesson planning and student analytics.
• Creating inclusive education models for students with disabilities, learning disorders, or special needs.

However, this vision can only become real if equity is embedded at the design level.

We must ensure AI tools are co-developed with educators, parents, and local communities. We must avoid reinforcing biases by building diverse datasets, and prioritize accessibility, both technological and linguistic.

Teaching About AI: Not Just Using It

If AI is to become a pillar of education, we must go beyond using it—we must teach it.

Students should not only learn with AI but also learn about AI:

              •            How it works.

              •            How it makes decisions.

              •            How can it be not very objective, manipulated, or misused?

              •            How to ethically develop, deploy, and audit AI systems.

This is critical for digital citizenship in the 21st century. AI literacy must become a core curriculum, alongside reading, writing, and arithmetic.

Human + Machine = A New Pedagogical Era

Critically, AI should enhance, not replace, human teaching.

Teachers are irreplaceable. They provide emotional support, cultural relevance, mentorship, and moral reasoning—traits AI cannot replicate. However, AI can:

              •            Handle routine admin.

              •            Provide instant feedback.

              •            Diagnose knowledge gaps.

              •            Suggest strategies for differentiation.

This frees educators to do what they do best: inspire, empathize, and lead.

According to the World Economic Forum (2023), teachers using AI tools report 50% more time spent on high-impact teaching tasks, while student engagement and emotional connection with learning increased by 30%.

The Moral Imperative of Leadership

AI in education is no longer just a technological question—it is ethical.

We, as educators, policymakers, and entrepreneurs, must fight to ensure AI:

              •            Expands access, not inequality.

              •            Supports students’ purpose, not just performance.

              •            Enhances human intelligence, not replaces it.

The worst-case scenario is not that AI dominates education. Only a small group of students and schools benefit, while the rest are left behind. This is a call to action—to build frameworks, guardrails, and global partnerships that democratize this powerful technology.

A Personal Reflection

I think of the hundreds of students I’ve taught—some brilliant, some struggling, all unique. Traditional methods underserved many. Some never reached their potential, not due to lack of intelligence, but lack of support.

What if those students had access to an AI tutor that adapted to their strengths, explained concepts patiently, encouraged curiosity, and respected their cultural identity?

What if that AI also helped their teachers focus on them, not just paperwork?

That future is now within reach.

Conclusion: From Two Sigma to One Global Standard

We began with Bloom’s Two Sigma Problem—the idea that 1:1 tutoring is powerful, but unscalable. AI challenges that assumption.

What was once impossible—scaling excellence—is now possible, if we act.

We have a moral and strategic responsibility to responsibly, inclusively, and intelligently shape this transformation.

Because the real promise of AI is not just artificial intelligence.

It is an amplified human purpose.

It is equity, access, and excellence—at scale.

And it is our chance to make quality education not a privilege, but a global standard.