ChatGPT, a Large Language Model (LLM) developed by OpenAI using the Generative Pre-trained Transformer (GPT) architecture, stands at the forefront of language generation technology. Designed to understand and respond in natural language text input, it allows seamless conversations with a machine. ChatGPT is a state-of-the-art language model that excels in generating human-like text. ChatGPT has been trained on a vast amount of data, allowing it to generate coherent and contextually appropriate responses to a wide range of prompts. The latest version, GPT-4, released in 2023, further enhances the model's capabilities. With a broader general knowledge and advanced reasoning abilities, GPT-4 demonstrates enhanced accuracy in solving complex problems.

This paper aims to identify the most effective prompt design techniques for generating high-quality answers from ChatGPT. It explores diverse strategies of prompt engineering that can be employed to achieve specific goals. By providing examples and insights into the combination of different prompt techniques, our objective is to demonstrate their potential in achieving nuanced outcomes. Emphasizing the importance of understanding how to frame questions to ChatGPT, we highlight the need for a tailored approach to get the desired high-quality outputs.

Specifically, the paper focuses on ChatGPT's effective usage in education. Concrete examples will be provided to illustrate how ChatGPT can be applied in various school subjects, highlighting its versatile nature. We explore the primary educational applications of ChatGPT, spanning from asking questions and acquiring information to conducting supplementary research and analyzing information sources. Through a detailed examination of prompt engineering techniques, we aim to equip students and teachers with the knowledge and strategies necessary to use ChatGPT effectively.

Keywords: ChatGPT, Large Language Model, education, problem-solving.