What Comes to Mind When You Think About AI?
For some, Artificial Intelligence is a chatbot. For others, it is an answer machine that provides instant solutions. But my journey with AI has been very different.
For me, AI was never a replacement, nor a machine that simply gives answers. It has always been a thinking partner and a second pair of eyes. It helps me review ideas, uncover blind spots, and look at problems from different perspectives. More importantly, it helps me improve my thinking rather than replace it.
For years, whenever I needed information, I would search different sources and try to understand multiple perspectives. Even after AI became widely available, I never treated it as an answer machine. Instead, I used it as a collaborator to organize ideas, structure information, and challenge my own assumptions.
How I Started Using AI
My initial interactions with AI were simple. I would discuss activities and projects with it to understand the concepts involved. Many times, I would start with one learning objective in mind, only to realize that the same activity could be used to introduce additional concepts. Over time, AI became useful in creating worksheets, generating examples, preparing presentations, and converting rough notes into structured reports.
While this certainly saved time, what helped me most was that it allowed me to spend more time thinking about learning experiences instead of routine documentation.
Designing Better Learning Experiences
Breaking Down Complexity
One experience that changed my perspective involved designing a curriculum around a six-degree-of-freedom robotic arm. The topic itself was complex, and introducing it directly to students would have been overwhelming. My challenge was not understanding the concept, but designing a learning journey that students could easily follow.
Through my discussions with AI, I explored different ways to sequence the learning. Instead of beginning with a complete robotic arm, the journey could start with understanding how a servo motor works. Students could then learn to control a single axis before moving to a two-degree-of-freedom arm. This gave me a natural way to introduce mathematical concepts and coordinate systems. Gradually, learners could progress to three degrees of freedom and eventually understand the basics of kinematics.
What impressed me most was not the answers, but how AI helped me think through the learning journey. It suggested analogies, highlighted concepts I had overlooked, and helped me structure the curriculum in a way that students could easily follow.
Building a Framework for STEM Project Classification
Another memorable experience came while developing a framework to classify STEM projects according to age groups. As educators, we often rely on experience and intuition to decide whether a project is suitable for a particular learner. I wanted to create a more systematic approach.
During my discussions with AI, I explored factors such as learner readiness, complexity, and developmental stages. In the process, I came across the idea of effort scores, which encouraged me to think differently about project complexity.
The discussions didn’t give me a ready-made framework, and I certainly didn’t accept every suggestion as it was. Instead, they pushed me to study research papers, understand learner attention spans, and combine different perspectives. Eventually, these interactions helped me build a framework based on both experience and evidence.
What AI Has Taught Me
Perhaps the biggest value of AI is not speed, but perspective. Whenever I prepare content or develop a framework, I use AI to review my ideas and identify things that I may have missed. These interactions have made me more creative, more systematic, and more aware of different possibilities.
At the same time, AI has reminded me of the importance of human judgment. It can provide incomplete information, overlook context, or occasionally generate inaccurate responses. Blindly accepting every suggestion can weaken critical thinking and create a false sense of confidence. My experience with effort scores taught me this lesson clearly. While the concept itself was useful, the values and classifications had to be adapted to real-world conditions. Human judgment, experience, and understanding the context still matter.
A Message to Fellow Educators
If I had one message for educators who are hesitant about AI, it would be this: start with your own thoughts. Do not ask AI to think instead of you. Ask it to think with you. Treat it as a collaborator rather than an authority. Use it to challenge assumptions, explore different perspectives, and refine your ideas. Verify information, question outputs, and adapt them to your own context.
Final Thoughts
AI is not an answer machine. It is a thinking partner and a second pair of eyes that helps educators see beyond what is immediately visible. It does not replace our ideas. It enriches them, sharpens our thinking, and enables us to create learning experiences with greater meaning and impact.
Today, it may be AI. Tomorrow, it may be something entirely different. As educators, our responsibility is not merely to adopt new tools, but to remain curious, continue learning, and adapt. Technology will continue to evolve, but our willingness to learn, adapt, and grow as educators should remain constant.
About the Author
A Senior Project Management Officer at Lab of Future with over seven years of experience in STEM education and project management, she specializes in designing, implementing, and scaling educational programs that combine hands-on learning with real-world applications. Through workshops, science shows, and curriculum initiatives, she has made a meaningful impact by reaching more than 100 educators and 10,000 students. Passionate about inspiring curiosity and fostering deep understanding, she seamlessly blends traditional teaching methods with practical, experiential learning to create engaging and impactful educational experiences.