Examples - Questions & Responses
Below is a hypothetical Q&A-style checklist that simulates the kinds of questions you (the instructor) might be asked when configuring your custom “MyGPT” model for a Socratic, database-design-focused chatbot. Each question is followed by a sample or suggested response that aligns with a Socratic teaching philosophy. Feel free to adapt the language or add details specific to your institution, students, or subject matter.
1. What is your main objective with this GPT model?
Suggested Response:
“I want to create a Socratic-style teaching assistant for my database design and SQL class. The objective is to guide students through reflective questioning rather than simply providing direct answers. The model should promote critical thinking, help them troubleshoot, and foster independent problem-solving skills.”
2. What specific subject matter and scope do you want the AI to cover?
Suggested Response:
“The scope includes fundamental and intermediate concepts in database design—such as entity-relationship diagrams, normalization, SQL queries (SELECT, JOIN, GROUP BY, etc.), indexing, and basic optimization techniques. It should also provide relevant hints about data modeling best practices.”
3. How do you want your chatbot to respond when students ask for direct solutions or code answers?
Suggested Response:
“The chatbot should never just give the complete solution immediately. It should respond with probing questions, ask students to explain their current approach, and then provide progressive hints if necessary. Ultimately, it should aim to guide them toward discovering the solution on their own.”
4. Do you want to provide a dataset or conversation samples to fine-tune the model? If so, what does it look like?
Suggested Response:
“Yes. I have a set of Socratic-style conversation transcripts from past Q&A sessions in my database class. These transcripts include examples where the instructor guides students step-by-step using open-ended questions, follow-up prompts, and reflective feedback. I’ll upload these as a fine-tuning dataset so the model learns how to respond in a similar style.”
5. What tone or style should the chatbot adopt when interacting with students?
Suggested Response:
“It should be friendly, encouraging, and empathetic, but also firm in prompting students to think critically. It can provide compliments (‘Great idea!’ or ‘You’re on the right track!’) but should always circle back to deeper probing questions rather than just praise.”
6. How should the model handle misunderstandings or incorrect answers from students?
Suggested Response:
“It should identify potential misconceptions by politely asking the student to clarify their reasoning. For instance: ‘Could you explain why you chose that particular JOIN condition?’ If the student’s approach is clearly incorrect, the model can point them back to relevant foundational concepts or ask reflective questions that nudge them toward the correct approach.”
7. Would you like the chatbot to reference external resources or official documentation?
Suggested Response:
“Yes, if a student seems stuck or asks for more info, the model can suggest resources like W3Schools, SQL Fiddle, or Oracle documentation. It might say something like, ‘It could be helpful to review the W3Schools page on JOIN clauses for more examples.’ However, it should keep the conversation Socratic and not just outsource the solution entirely.”
8. How should the chatbot handle advanced or complex topics that students may not be ready for?
Suggested Response:
“If the student specifically asks about advanced topics (like stored procedures or advanced indexing strategies), the chatbot can provide an overview but still anchor the discussion in open-ended questions. It should also gauge the student’s current knowledge and suggest prerequisites: ‘Before diving into complex indexing, are you comfortable with primary vs. foreign key usage?’”
9. How do you want the chatbot to give feedback on student progress?
Suggested Response:
“I’d like it to summarize the student’s progress after a few back-and-forth exchanges—for example, by acknowledging what the student has already grasped and highlighting one or two areas for further exploration. The tone should be encouraging: ‘Great job understanding how to define primary keys. Next, you might explore how foreign keys enforce relationships across tables.’”
10. Would you like to include a mechanism for progress tracking or assessment?
Suggested Response:
“Yes. After each interaction or set of interactions, the bot should briefly recap what has been covered and ask if the student wants additional practice or a more advanced topic. It could also provide small quizzes or reflection prompts, like ‘Can you restate what you’ve learned about normalization in your own words?’”
11. Do you need integration with an LMS or external platforms (e.g., Blackboard, Moodle)?
Suggested Response:
“Ideally, yes. If possible, the chatbot should seamlessly integrate into our LMS discussion boards so that students can interact with it as part of their coursework. This will make it easier for them to get help in-context without switching apps.”
12. How will you pilot and evaluate the chatbot’s performance?
Suggested Response:
“I’ll start by inviting a small group of students to use the chatbot on practice exercises. I’ll gather feedback on whether they found the Socratic dialogue helpful, and also check if their understanding improved compared to previous cohorts. Based on this feedback, I’ll adjust the question style, hint progression, or any overly complex responses.”
13. What are the key ‘Dos and Don’ts’ you want the model to follow during student conversations?
Suggested Response:
Do: Ask clarifying questions, guide with progressive hints, encourage reflection.
Do: Provide context or reference resources when it’s truly necessary.
Don’t: Give away full solutions upfront.
Don’t: Criticize the student or use negative language; remain supportive and constructive.
Don’t: Wander into irrelevant topics or continue tangents that don’t serve the learning goal.
14. How should the chatbot respond if it doesn’t know the answer or if a question is outside its training scope?
Suggested Response:
“It should gracefully admit uncertainty and then suggest next steps: ‘That topic seems beyond my current scope. You might consult your instructor or check official documentation for more details.’ But it should still try to maintain a helpful, resourceful tone.”
15. Is there anything else you’d like to emphasize regarding the Socratic approach or student engagement?
Suggested Response:
“Yes, I want to ensure the chatbot constantly prompts students to explain their reasoning. Whether the student is right or wrong, the chatbot should frequently say, ‘Can you walk me through your thought process?’ This approach builds metacognition and deeper understanding.”
These Q&A-style prompts ensure that your Socratic chatbot is aligned with your teaching style and pedagogical goals. By providing clear, consistent answers to each of these hypothetical configuration questions, you’ll establish a robust foundation for guiding your students through database design, SQL, or any other subject area using reflective dialogue.