How Poor Pedagogy Fuels the Very AI Misuse We Fear

Posted 21 Oct 2025

You have read the headlines. Artificial intelligence, they say, is a threat to student cognition. It encourages cheating. It creates dependency.

These warnings focus on the wrong problem. The greatest risk in education is not the technology. It is the absence of a strong instructional framework to guide its use. AI does not determine student outcomes. Pedagogy does. The tool is inert. The teaching brings it to life. We should not fear AI. We should fear introducing it without preparing our educators.

I saw this firsthand as a trainer in a recent pilot with the Philippine Alternative Learning System. We worked directly with 265 teachers. Our goal was not to make them AI experts. It was to show them how a pedagogical framework could guide technology. We demonstrated how to realign existing ALS modules with the Convergence Theory of Learning using an AI assistant. The results were clear. Teacher confidence in using AI tools increased significantly. Their satisfaction rating was 9.39 out of 10. This happened despite an average of 9.8 internet disconnections per teacher. Their engagement proves a point. When educators see a practical method for integrating AI, they will overcome obstacles to learn it.

The conversation must change. The question is no longer whether to use AI. The question is how to use it correctly. This requires a new approach from all of us.

How Poor Task Design Invites AI Misuse

When a student uses AI to complete an assignment, the common reaction is to blame the student. We call it cheating. We accuse them of laziness. This reaction is unfair. It is also a sign that our instruction has failed.

Consider this. If an assignment can be completed by an AI with a simple prompt, what was its real value? Was it a genuine test of skill? Or was it a routine exercise that valued the product over the process? An AI can easily produce a five paragraph essay on a novel. It cannot, however, lead a classroom debate about the novel's themes. It cannot connect the story to a student's personal struggles. It cannot work with a group to perform a key scene.

Blaming the student for using AI is like blaming a driver for using a GPS on a road with no signs. They are using the most efficient tool available to meet a demand we set. The problem is not the tool. The problem is the task.

In our ALS training, we did not focus on detecting AI misuse. We focused on instructional design. We showed teachers how to use AI to inject critical thinking into their existing lessons. This shift from policing to designing is the first step toward a solution.

The Convergence Theory of Learning: A Pedagogical Compass for AI

To prevent AI from causing cognitive atrophy, you must anchor it in a strong pedagogy. The Convergence Theory of Learning provides this anchor. CTL is a framework developed by Fr. Benigno Beltran, S.V.D. of the Sandiwaan Center for Learning, that prepares learners for real-world challenges. It moves beyond memorization to develop thoughtful, capable, and ethical individuals.

CTL is built on three core thinking skills, supported by essential habits and values.

The Three Core Thinking Skills:

• 1. Critical Thinking. This is the ability to question, analyze, and evaluate information. A student using critical thinking asks "Why is this true?" and "How do I know this is reliable?" They learn to spot bias and make reasoned judgments. It is the foundation of discernment.
• 2. Systems Thinking. This is the ability to see patterns, relationships, and the whole picture. A student using systems thinking understands that elements are interconnected. They learn that a change in one part creates changes elsewhere. It is the mindset for understanding complexity.
• 3. Design Thinking. This is the ability to imagine, create, and innovate. A student using design thinking identifies a problem, brainstorms creative solutions, and tests their ideas. It is the engine for practical invention and improvement.

The Supporting Habits and Values:

These thinking skills are brought to life through four key supports.

• • Metacognition: This is "thinking about your thinking." CTL teaches students to reflect on their own learning process.
• • Systems Thinking: CTL builds intrinsic motivation by connecting lessons to students' lives and fostering a love for learning.
• • Multimodal Mentoring: Learning happens through diverse methods like discussion, storytelling, and hands-on projects.
• • Core Values: CTL fosters growth in integrity, solidarity, and creativity, developing ethical and collaborative individuals.

CTL’s core principle is simple but powerful. Technology should help learners reflect, not do the thinking for them.

From Theory to Practice: Transforming a Standard Lesson with CTL

Consider a standard Lower Elementary module on "Proper Nutrition: A Basic Need." The original outline focuses on knowledge: defining nutrition, listing food groups, and identifying healthy meals.

This is where the DIWA Virtual Teacher's Assistant becomes a catalyst for change. DIWA is an AI tool designed to operationalize the Convergence Theory of Learning. A teacher can input this basic module outline into DIWA, and it instantly generates a suite of CTL-aligned learning activities and assessments. It automates old tasks and provides the building blocks for a new kind of pedagogy.

Here is what that transformation looks like in practice:

• • From Recitation to Systems Thinking: Instead of just memorizing the food groups, DIWA suggests the "Meal Clock Builder Game." In this activity, students use a digital clock tool to design a balanced daily meal schedule, placing food icons at correct times. This requires them to think about how food choices fit together throughout a day and why timing and variety matter, seeing nutrition as an interconnected system rather than a static list.
• • From Listening to Critical & Design Thinking: Instead of passively hearing a story, DIWA generates an interactive narrative outline for "Eat Smart: Mang Simon’s Adventure Game." Students guide a character through a branching story where each choice has consequences. They must analyze the outcomes of his meal options and design a path for his well-being. This builds critical judgment and creative problem-solving as they actively construct a healthy outcome.
• • From Identification to Metacognition & Values: DIWA proposes an "Emoji Mood Tracker and Food Log." This shifts the focus from external facts to internal reflection. Students record their meals and match them with emojis representing their energy and mood, then review the log to identify personal patterns. This promotes metacognition about their own habits and connects to the core value of integrity towards one's own body.

The accompanying assessments are similarly transformed. For instance, instead of a multiple-choice test on the food groups, DIWA helps create a "Comic Strip Evaluation."In this assessment, students use a digital tool to create a comic showing a character's day with proper nutrition versus a day without it. They must illustrate the consequences-like energy levels, mood, and health-demonstrating their ability to synthesize information and creatively communicate their understanding of nutritional cause and effect, rather than simply recalling facts.

This realignment process is powerful. It moves the student's role from passive recipient to active investigator. The lesson becomes AI-proof because the value is no longer in the retrieved answer. The value is in the thinking process the student must undertake. The AI-powered DIWA tool simply helps the teacher design this richer learning experience efficiently.

A Strategic Roadmap for Education Leaders

You can apply these lessons. The process requires focusing on pedagogy first, then technology.

Start with a pedagogical audit. Define the cognitive skills you want students to develop. The Convergence Theory of Learning offers one model. Your institution may use another. The key is to establish a clear standard.

Invest in practical teacher training. Do not host theoretical seminars. Run workshops where teachers bring their own modules and learn to realign them. Our pilot proved that even a short, practical session can build significant confidence and readiness.

Build a library of examples. Create a shared repository where teachers can see how others have transformed standard lessons into thinking-centered experiences. This makes the pedagogy tangible.

Choose tools that support this realignment. The DIWA tool was built for this purpose. When evaluating any AI tool, ask a simple question. Does this help teachers design better learning experiences, or does it just help students find answers faster?

Design for equity. Our ALS teachers faced major connectivity issues. Your implementation must prioritize offline functionality and low-bandwidth use. AI must not become a privilege for well-resourced schools.

The Choice Is Ours: Cognitive Empowerment or Atrophy

The future of AI in education will be written by those who act now. The Philippine ALS pilot provides a model. The teachers proved they are ready. The method proved it is practical.

You can start today. Convene your team and define your instructional non-negotiables. Audit your professional development to ensure it is practical, not just theoretical. Evaluate every technology decision through the lens of your pedagogical framework.

The complete report, "Rethinking AI for Equity and Cognition," provides the full data and context. You can access it to inform your strategy.

The path is clear. We must stop blaming students and start leading. We must equip teachers with a practical method for integrating technology. We must build systems that reward human thinking. The teachers in the most challenging environments have shown us it is possible. It is now our turn to act.

Keywords:

artificial intelligence, ai, edtech, education, pedagogy, ctl, convergence theory of learning, philippine education, als, alternative learning system



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