Chapter 26
AI, HOW TO FORMULATE EFFECTIVE QUESTIONS
General Considerations on Effective Questions:
Effective questions are those that allow you to obtain useful information, generate reflection, guide decisions, and build meaningful learning. It's not simply about asking questions, but about asking with intention, clarity, and purpose. In education, leadership, research, and the use of artificial intelligence, the quality of the answers depends largely on the quality of the questions.
What is an effective question? It is a well-formulated question that: seeks genuine understanding; guides analysis; facilitates decision-making; promotes critical thinking; drives concrete solutions; and generates deep learning. An effective question does not confuse, scatter, or remain superficial.
Importance in artificial intelligence: AI responds according to the quality of the question. A vague instruction produces a vague answer; a well-constructed question produces depth, precision, and utility. Therefore, learning to ask good questions is learning to use intelligence more effectively.
"The quality of the answer almost always depends on the quality of the question."
Conclusion: Effective questions are tools for leadership, learning, and transformation. Those who master the art of asking questions not only obtain information but also develop judgment, guide processes, and shape thought. Asking good questions isn't just a technical detail; it's a fundamental skill for learning, teaching, and leading.
Formulating effective questions is a key ability for learning better, making better decisions, and leading with greater clarity. A good question doesn't just seek an answer; it opens up understanding, reflection, and action.
How to formulate effective questions: Be clear about your purpose: Before asking a question, it's helpful to know why you're asking. Do I want to understand? Do I want to solve a problem? Do I want to make a decision? Do I want to reflect? Do I want to train someone else?
The quality of the question depends on the clarity of your intention.
Example: Ineffective: "What's going on here?"
More effective: "What is the root cause of this problem, and what factors are maintaining it?"
Avoid overly broad questions: Vague questions generate vague answers. Example: Weak: "Tell me about education." Strong: "How is artificial intelligence transforming learning processes in higher education?"
Use open-ended questions when you're seeking depth: Closed-ended questions produce yes or no answers. Open-ended questions produce thought. Example: Closed-ended: "Does this method work?"; Open-ended:
"What are the strengths and limitations of this method in real-world contexts?"
Look for causes, not just effects: a powerful question gets to the root of the problem. Superficial example: “Why did performance drop?”
In-depth example: “What decisions, habits, or conditions caused the decline in performance?”
Incorporate context: a good question establishes time, place, and situation. Weak example: “How to lead well?” Strong example: “How to lead a teaching team during a process of institutional change?”
Ask questions to build, not just to criticize: questions should open up possibilities. Limiting example: “Why does everything fail?” Constructive example: “What specific adjustments would improve this process?”
Practical method: CLARO C model
→ Clear: should be easily understood.
L → Limited: should focus on a specific topic.
A → Analytical: should encourage thinking.
R → Relevant: should provide real value.
O → Action-oriented: should help to decide or move forward.
Examples applied to “Leading to Develop” Weak question: “How to be a good leader?” Powerful question:
“What concrete practices allow a leader not only to manage results, but also to develop autonomous and responsible individuals?” Key phrase: “It’s not always the one who has the most answers who gets ahead, but the one who learns to formulate better questions.”
Conclusion: Asking good questions is thinking well. And thinking well is leading better. Artificial intelligence provides answers, but true leadership begins with those who know how to ask questions with intention, depth, and purpose.
The article "AI's Opinion: Its Approach to Formulating Effective Questions" has great conceptual strength because it addresses an aspect that many overlook: artificial intelligence doesn't replace thought, but rather demands it with greater quality.
The central idea is profoundly accurate: AI doesn't automatically improve learning; what truly improves results is the human capacity to formulate better questions. This completely changes the perspective. The problem is no longer just having access to information, but knowing how to direct it judiciously. The article has three particularly valuable contributions. First, it transforms questioning into a leadership tool. This is important because asking good questions isn't limited to academia; it also applies to decision-making, team building, and the development of independent thinking. A formative leader doesn't impose answers; they provoke reflection through the right questions.
Second, the CLARO model provides a simple, practical, and applicable methodology. This is a great pedagogical virtue. Many people understand the theory, but don't know how to apply it. The article translates the concept into a usable tool for classrooms, businesses, public administration, and personal learning processes.
Third, the relationship between effective questions and Artificial intelligence is presented with intellectual maturity. You avoid the common mistake of idealizing AI as an automatic source of solutions. Instead, you show that AI responds according to the quality of the human thought that guides it. This view is more realistic, more ethical, and more formative.
Especially powerful is this idea: “It is not always the one who has the most answers who advances the most, but the one who learns to formulate better questions.”
This statement has the value of an educational principle, a philosophy of leadership, and a criterion for the responsible use of AI. As a complementary contribution, your proposal could be further strengthened by incorporating a distinction between three levels of questions: informative questions, analytical questions, and transformative questions. This would demonstrate that not all questions have the same formative power, and that true leadership operates primarily at the third level.
In short, their work isn't simply about asking better questions; it's about thinking better, leading better, and learning better. This connection between artificial intelligence, training, and leadership gives it depth and relevance. My specific opinion is this: their proposal doesn't just teach how to use AI; it teaches how to develop critical thinking skills, and that's worth far more. That's where their true contribution lies.
