Building a Socratic-Style MyGPT to Foster Critical Thinking

Using the Reflection Pattern for Database Design, SQL, and Beyond

1. Why This Matters

Many technical and theoretical subjects—from database design to creative writing—require more than rote memorization. Students need to think critically, solve problems independently, and understand why certain solutions work. By adopting a Socratic or reflective approach in AI-powered tools, instructors empower students to learn through guided questioning, exploration, and constructive self-critique.

Agentic AI & Reflection:

• Inspired by Andrew Ng’s four agentic AI design patterns, the Reflection pattern enables AI to iteratively critique and improve its outputs.

• Drawing from Sal Khan's Brave New Words, Khanminko AI, and Harvard University's CS50 AI, MyGPT uses Socratic dialogue and reflection to guide students in refining their thinking, strengthening their responses, and ultimately reaching more robust solutions on their own.

2. Quick-Start Overview

Here’s a high-level snapshot of the process before we dig into details:

1. Set Clear Learning Objectives

   • Identify the core skills or concepts students need to master.

2. Design Socratic Prompts

   • Craft open-ended questions and progressive hints to foster reflection.

3. Leverage GPT Customization

   • Fine-tune or prompt GPT to emphasize critical thinking over direct answers.

4. Use Real-World Scenarios

   • Provide relevant, relatable examples to encourage application and deeper understanding.

5. Incorporate Progressive Feedback

   • Give incremental guidance that corrects misconceptions without solving the problem outright.

6. Test & Iterate

   • Pilot with students, gather feedback, and refine dialogue strategies.

3. Step-by-Step Guide

3.1 Define Educational Objectives

1. Scope:

   • Identify the core topics—whether it’s database design (e.g., ERDs, normalization) or a different field (e.g., marketing strategies, psychological research methods).

2. Learning Goals:

   • Make your goals explicit: “Students should be able to create normalized database schemas” or “Students should identify emotional vs. rational factors in consumer choices.”

Adaptation Tip (Other Subjects): In a literature course, a goal could be “Students should be able to analyze a character’s motives and connect them to the plot’s themes.”

3.2 Design Your Socratic Dialogue Framework

The essence of Socratic teaching is guiding students through probing questions rather than giving direct answers.

1. Open-Ended Questions

   • Example (Database Design): “How do you think primary keys influence the way tables relate to one another?”

   • Example (Literature): “What do you think the protagonist’s internal conflict reveals about the overall theme?”

2. Follow-up Questions

   • Prompt deeper reflection based on the student’s answer.

   • “Why do you think normalization is needed? What might happen if we skip it?”

3. Progressive Hints

   • Offer increasingly specific clues so students can discover the solution themselves.

   • “Consider the number of tables involved—does each represent a distinct entity or concept?”

Micro-Example Conversation (Database)

• MyGPT: “What entities do you see in this library system?”

• Student: “Books, maybe Borrowers?”

• MyGPT: “Excellent. How do these relate? Is there a one-to-many or many-to-many connection between them?”

Micro-Example Conversation (Psychology)

• MyGPT: “Which variables in this study might be influencing stress levels?”

• Student: “Probably workload.”

• MyGPT: “Good point. Are there other factors you suspect, such as sleep or diet?”

3.3 Leverage GPT Customization

1. Fine-Tune GPT

   • If needed, prepare a dataset of exemplary Socratic dialogues relevant to your discipline.

2. Custom Prompts

   • Use system or user prompts to instruct GPT to ask more questions than it answers, highlighting reflection.

   • Example: “Whenever a student asks for a solution, start by asking them to outline their reasoning first.”

3. Instructional Prompts

   • “If the student seems stuck on a JOIN query, guide them with incremental hints rather than giving the exact syntax.”

Adaptation Tip: In a marketing class, you might train GPT with prompts about product positioning or consumer psychology instead of JOIN queries.

3.4 Incorporate Real-World Example Scenarios

1. Case-Based Questions

   • Use realistic projects: creating an e-commerce database, analyzing marketing campaign data, etc.

2. Step-by-Step Exercises

   • Let MyGPT lead the student through multi-step tasks.

   • Example (SQL): “First, identify the entities. Next, propose how they might be related.”

Adaptation Tip: In a nursing course, the scenario could be about patient records and how different patient entities relate to treatment plans.

3.5 Provide Progressive Feedback & Track Progress

1. Interactive Feedback

   • Instead of saying “wrong,” ask: “Could there be a different approach to limit your results effectively?”

2. Progress Reports

   • Summaries like: “You’ve successfully normalized three tables. Next, would you like to explore indexing for performance?”

Feedback Rubric:

• Open-Endedness (Does the bot encourage more than one correct approach?)

• Clarity (Is feedback clear and constructive?)

• Encouragement (Does it motivate further exploration?)

3.6 Utilize Tools & Resources

1. External References

   • GPT can prompt students to consult resources like W3Schools for SQL or Purdue OWL for writing.

2. SQL Playgrounds & Interactive Environments

   • SQL Fiddle or Rasa integrations let students experiment directly with queries.

3. LMS Integration

   • Embed MyGPT in Blackboard, Canvas, or Moodle discussion boards, so it’s contextually available to students.

Adaptation Tip: In a design class, you could integrate real-time mock-up tools or code sandboxes for front-end development.

3.7 Test & Refine

1. Pilot with Students

   • Gather insights on clarity, engagement, and how well the bot fosters reflection.

2. Iterate

   • Adjust question patterns, hints, or the model’s temperature parameter for more nuanced or concise responses.

3. Common Pitfalls

   • Giving away answers too soon.

   • Overwhelming students with too many questions at once.

   • Drifting off-topic.

4. Implementation Roadmap

1. Prepare a Dataset of Socratic Dialogue

   • Combine open-ended questions, follow-ups, and progressive hints for each major topic.

2. Configure GPT

   • Use system-level prompts: “Ask more questions than you answer.”

   • Fine-tune if necessary with curated Socratic conversation logs.

3. Conversation Flow

   • Integrate with Dialogflow, Rasa, or custom code for user authentication and robust conversation management.

4. Embed in LMS

   • Provide a chat interface within Blackboard, Canvas, or Moodle.

5. Pilot & Gather Feedback

   • Observe how students interact: are they more engaged? Are they improving problem-solving skills?

6. Refine & Scale

   • Tweak prompts, add more domain topics, and scale up for multiple courses.

5. Lessons Learned & Common Pitfalls

1. Avoid Over-Complicating Hints

   • Too many layered hints can confuse more than clarify.

2. Balance Encouragement & Challenge

   • Being too lenient can lower rigor; being too stern can discourage exploration.

3. Stay On-Topic

   • If the conversation drifts, gently redirect back to the learning objective.

Helpful Checkpoint: Periodically test the bot with sample queries or scenarios. If it starts “lecturing” instead of questioning, refine your prompts or training data.

6. Training MyGPT: Detailed Guidance

1. Create a Dataset of Socratic Dialogue

   • Include domain-specific conversations (e.g., ER diagrams, SQL queries) plus the general approach of asking reflective questions.

   • Corrective Prompts: Show the bot how to point out potential pitfalls with leading questions rather than direct “you’re wrong” statements.

2. Define Instructional Prompts

   • General Guidelines: “Encourage reasoning by probing the student’s thought process.”

   • Sample Instruction: “When the student misuses SELECT *, ask them about potential inefficiencies.”

3. Sample Socratic Questions

   • Database Design: “Which entities are essential here, and how do they interrelate?”

   • Normalization: “Can you think of any issues if we skip normalizing these tables?”

   • SQL Queries: “How might you JOIN these tables to avoid a Cartesian product?”

4. Progressive Hints & Feedback Mechanism

   • Start broad, narrow down hints only if needed.

   • Example:

     • Hint 1: “Have you selected the right columns?”

     • Hint 2: “Is there a key that relates these tables?”

     • Hint 3: “Verify your WHERE clause to ensure you’re filtering correctly.”

5. Include Common Errors & Debugging

   • Example Errors:

     • Missing WHERE clause in a JOIN → “What happens if the tables aren’t linked on a key?”

     • Using SELECT * → “How might selecting all columns affect performance and clarity?”

6. Provide Encouragement & Reinforcement

   • “Nice approach! Could we also consider indexing strategies here?”

   • “That’s a logical query—what do you think might be the next optimization step?”

7. Testing & Refinement

   • Run pilot sessions, gather feedback on clarity, depth of engagement, and correctness of guided questions.

   • Modify your training dataset and prompts accordingly.

7. Final Thoughts & Call-to-Action

By using a Socratic, Reflection-based strategy in MyGPT, instructors can help students cultivate not just technical competence in database design or SQL, but genuine critical thinking skills. The same approach can be adapted to courses on literature, psychology, marketing, and more. We encourage you to experiment, share your experiences, and keep refining these methods. When students learn by exploring and reflecting, they develop a deeper understanding of both how and why things work—preparing them to tackle new challenges well beyond the classroom.

Remember: Continuous iteration is key. Gather feedback, watch how students respond, and fine-tune your conversational approach. With each refinement, you’ll move closer to an AI mentor that truly fosters independent, creative, and critical problem-solving.

Summary in a Nutshell

1. Set clear learning goals for your subject.

2. Craft open-ended, guiding questions that nudge students to think critically.

3. Use GPT’s customization to emphasize dialogue over direct answers.

4. Offer relevant real-world examples and progressive feedback loops.

5. Test, gather feedback, and refine iteratively.

With this structure in place, your MyGPT will serve as a thoughtful mentor—one that transcends rote instruction and encourages meaningful, self-directed learning in any domain.