Leveraging ChatGPT as a Personal Tutor, According to Andrew Bolis

In a recent LinkedIn post, Andrew Bolis explores a novel approach to accelerating learning by utilizing ChatGPT as a personalized educational tool. Bolis outlines a detailed prompt designed to transform the AI into an expert tutor, capable of guiding users through complex topics with a structured, interactive, and adaptive learning process.

Transforming AI into a Personal Educator

Andrew Bolis presents a comprehensive prompt that aims to harness ChatGPT’s capabilities for deep learning. The core of his strategy lies in instructing the AI to act as an “expert tutor.” This persona is tasked with creating a learning journey that mirrors a real course, progressing from foundational concepts to advanced material.

Bolis highlights the interactive nature of this learning method. He writes:

“Act as an expert tutor who guides me to master any topic through an interactive, question-based learning process. The method should be personalized, adaptive, and recursive, just like a real course.”

According to Bolis, the AI’s role extends beyond mere information delivery. It is engineered to actively engage the learner through Socratic questioning, practical exercises, and thoughtful reviews. This method is designed to ensure comprehension and retention, rather than passive consumption of information.

A Structured, Question-Based Learning Framework

The prompt detailed by Andrew Bolis emphasizes a step-by-step instructional design. The AI is instructed to first inquire about the desired learning topic. Following this, it must construct a clear, structured learning plan, meticulously building each lesson upon the previous one, moving from beginner to advanced levels.

For each lesson, Bolis specifies a multi-faceted approach for the AI:

• Explain concepts simply with real-world examples or analogies.
• Pose Socratic-style questions to test and deepen understanding.
• Provide short, practical exercises or thought experiments.
• Check for readiness to proceed or need for clarification.

As Bolis notes, the AI should adapt its explanation if the user requires more guidance:

“If I say no, rephrase the explanation, add examples, and guide me until I understand.”

This adaptive capability is crucial for ensuring that no learner is left behind, making the AI a truly personalized tutor.

Reinforcement and Application

Beyond initial explanations and checks, Andrew Bolis’s proposed prompt includes mechanisms for reinforcement and practical application. After major sections are covered, the AI is directed to provide summaries or short quizzes to review learned material. Upon completion of the entire topic, a final challenge is recommended to consolidate knowledge.

Bolis believes in the importance of connecting learning to real-world scenarios. He states:

“Finally, encourage me to reflect on what I’ve learned and suggest practical ways I can apply it to real-world projects or situations.”

This final step aims to bridge the gap between theoretical knowledge and practical implementation, empowering users to leverage their new understanding effectively. Bolis also provides a link to an advanced ChatGPT guide and encourages sharing of his post to help others benefit from this AI-driven learning strategy.