When I completed my PhD on critical thinking and problem-solving in student-centred eLearning, one of my strongest takeaways was this: technology must never remove the learner's agency. The goal of educational design is not to do the thinking for the student, but to scaffold thinking in ways that build confidence and independence.
Now, as we stand at the threshold of the AI revolution in education, this principle has never been more critical. The choices we make today about how AI integrates into learning will shape how an entire generation develops their capacity to think, question, and solve problems.
The Risk of Replacing, Not Empowering
Too many digital tools—even in eLearning before AI—fell into the trap of "shortcuts." They aimed to deliver content faster but often bypassed the very process of grappling, questioning, and reflecting that develops true critical thinkers.
I observed this pattern repeatedly in my research: well-intentioned educational technology that optimized for efficiency over agency. Students could complete assignments faster, but they weren't developing the metacognitive skills needed to tackle novel problems independently.
The Shortcut Trap in AI Education
Now with AI, the stakes are even higher. If we aren't careful, we risk handing students perfectly packaged answers that discourage curiosity. Consider these emerging patterns:
- • AI that writes entire essays, bypassing the thinking process
- • Tools that provide immediate answers without encouraging exploration
- • Systems that optimize for task completion over understanding
- • Platforms that reduce complex problems to simple prompts
"The goal of education is not to produce students who can complete assignments quickly, but students who can think through problems they've never seen before. This requires preserving the productive struggle that builds cognitive muscle." - From my PhD dissertation
What My Research Revealed
Through extensive observation and analysis of student-centred eLearning environments, my research identified key principles that support the development of critical thinking skills. These findings directly inform how we approach AI tool design at Zaza Technologies.
Evidence-Based Design Principles
My research showed that student-centred design works best when tools:
- • Scaffold rather than spoon-feed: Provide structure that supports thinking without doing the thinking
- • Encourage inquiry instead of dictating outcomes: Prompt questions rather than providing answers
- • Reduce unnecessary friction without removing productive struggle: Eliminate barriers to learning while preserving challenge
- • Support metacognition: Help students understand how they learn and think
- • Preserve student agency: Ensure learners maintain control over their learning process
These lessons apply directly to how we must build AI for education. The most effective educational AI won't be the tools that provide the best answers—it will be the tools that help students ask better questions and develop stronger thinking processes.
How Zaza Applies These Principles
Zaza's teacher-first AI is grounded in this research-based philosophy. Every feature we design is evaluated against a simple question: Does this enhance human capability or replace it?
Zaza Teach: Scaffolding, Not Scripting
Zaza Teach generates standards-aligned plans but leaves room for the teacher to adjust, adapt, and add creativity. The AI provides a strong foundation—curriculum alignment, age-appropriate activities, assessment ideas—but the teacher maintains agency over how these elements come together in their unique classroom context.
AutoPlanner: Structure with Flexibility
AutoPlanner doesn't just spit out units—it scaffolds them, aligning to curriculum and offering differentiated options, while leaving final judgment in the teacher's hands. Teachers can see the reasoning behind suggestions, modify approaches for their students, and maintain their pedagogical voice.
Promptly: Reducing Friction, Preserving Relationships
Promptly relieves the burden of drafting stressful parent emails, so teachers can focus on the human side of relationships. The AI handles the mechanical aspects of communication while ensuring the teacher's voice and care come through clearly.
The Zaza Difference
The point is never to remove the teacher, but to free them to do what they do best: nurture thinking, creativity, and confidence in their students. Our AI handles the administrative load so teachers can invest their energy in the irreplaceable human elements of education.
From Research to Practice: The Implementation Challenge
Translating research insights into practical tools is never straightforward. The gap between what we know works in theory and what actually improves daily practice is often wide. My experience building educational technology has taught me that the best research-informed tools are those that teachers barely notice—they simply make good teaching easier.
This is why Zaza's AI is designed to be invisible when it's working well. Teachers don't think about the AI; they think about their students. The technology recedes into the background, enabling rather than commanding attention.
Looking Ahead: Critical Tools for Critical Thinking
The future of AI in education will be defined not by who can generate the most content, but by who can design critical tools—tools that empower teachers and students to think more deeply, not less.
This requires AI developers to understand not just what artificial intelligence can do, but what human intelligence needs to flourish. It means designing from a foundation of learning science rather than technological capability.
The Questions That Guide Our Development
As we continue building AI tools for education, we constantly return to these research-informed questions:
- Does this tool make teachers more effective at developing critical thinking in their students?
- Does it preserve or enhance student agency in the learning process?
- Does it reduce cognitive load for teachers without reducing cognitive challenge for students?
- Does it support metacognitive development—helping students understand how they learn?
- Does it scaffold productive struggle rather than eliminating it?
The AI revolution in education is just beginning. The choices we make now—whether to prioritize efficiency over agency, answers over questions, completion over understanding—will shape how an entire generation develops their capacity to think critically about an increasingly complex world.
My PhD research convinced me that the goal isn't to make learning easier—it's to make learners more capable. The best AI tools will be those that honor this distinction, supporting the beautiful complexity of human learning rather than trying to simplify it away.