Template repository for UC ITS capstone projects source code. For more information see the getting started.
Despite the burgeoning literature on prompt engineering techniques in natural language processing (NLP), a critical gap exists in understanding their applicability in the realm of tech education. This study aims to address this gap by investigating how various prompt engineering approaches can be leveraged to enhance large language models (LLMs) for educational purposes within the technology domain.
We built a framework that explores different prompt engineering techniques and how to craft them effectively to generate desired code generation outputs from the LLMs. By conducting the experiments using this framework, we can improve how LLMs generate code, making it more accurate and relevant to the task.
The ./docs folder contains the documentation to navigate through project information and experiment jupyter notebook files denoted in .ipynb
Getting started with coding and using Github.
| Name | Link |
|---|---|
| Github getting started | Github.com |
| Markdown cheatsheet | Markdownguide.org |
| What is Source Control | Atlassian.com |
| Recommended Development Tools | Visual Studio Code |