The Next Generation of Problem-Solving
Introduction: In a world accustomed to instant solutions, what does it fundamentally mean to solve a problem? It is not simply about having or finding an answer instantly. It means first understanding what the problem actually is, asking questions, checking existing evidence and assumptions, considering various possibilities, deciding which approach to take, and continuing to work when the first idea fails. This is where critical thinking, creativity, innovation, and resilience come into play.
According to Facione (2015), critical thinking involves being open-minded, asking questions, and being willing to reconsider our own ideas. Trilling and Fadel (2009) connect these abilities with the demands of a changing world.
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Methodological Thinking: A Systematic Approach
Furthermore, a good problem-solving approach also needs a method. Methodological thinking means giving our thinking a structure or a step-by-step framework instead of simply hoping for one brilliant idea to appear.
Looking at Avicenna, a pivotal figure in the history of medicine, gives us a useful example. His approach to medical diagnosis involved carefully observing information, organising it, testing possible explanations, and learning from the results. His contribution was important because it made difficult reasoning more systematic and encouraged a step-by-step approach to examination and diagnosis.
Ignaz Semmelweis and the Power of Persistence
Another important problem-solver was Ignaz Semmelweis. He proposed handwashing to reduce infections in hospitals, but his idea was initially rejected. Later, research supported the importance of hand hygiene.
His story shows something important: a correct idea may still face resistance simply because it is new. This is where mistakes become important. A mistake can show us what does not work, helping us understand when and where to adopt or look for a new approach.
If students are punished every time they get something wrong, they may learn to avoid difficult questions altogether. A 2026 perspective by Araújo-Pereira and Andrade in Frontiers in Psychology suggests that students can learn better when they are allowed to experiment, make mistakes, and keep trying instead of simply memorising and following fixed methods.
Google, AI and Technological Tools
Today, however, the pressure for quick answers is stronger than ever. Google and other technological tools give us information instantly. AI can produce an answer in seconds. These tools are useful, but depending too heavily on easy answers can reduce the effort individuals put into thinking for themselves. Learning requires effort, and that effort can contribute to deeper learning and understanding.
Learning Through Inquiry and Experimentation
So, here is the bigger question: while we are training AI to solve problems better, are we training the next generation to think, analyse, and solve problems better?
Dewey emphasised learning through doing and inquiry. Similarly, STEM education and project-based learning give students opportunities to experiment, test ideas, and improve them. Such approaches encourage students to become active learners rather than passive receivers of information.
Conclusion
At the core of this discussion, the next generation does not need to be perfect. It needs to be curious enough to ask questions, brave enough to be wrong, disciplined enough to test ideas, and resilient enough to try again. AI can give us answers. But the future still needs people who are curious enough to ask questions, disciplined enough to investigate them, and resilient enough to keep searching when the answer is not obvious. That is how we can build a stronger culture of research, innovation, and problem-solving.
