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--- |
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license: cc-by-nc-4.0 |
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language: |
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- en |
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tags: |
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- education |
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- programming |
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- student |
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- queries |
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pretty_name: Students Queries from AI Coding Assistant |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Dataset Documentation |
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## Overview |
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The `students-coding-questions-from-ai-assistant.csv` dataset contains 6776 questions asked by students from CodeAid, an AI coding assistant, during a C programming class over a 12-week semester from January to April 2023. The students had previously taken two Python programming courses. The course did not allow the use of ChatGPT, but CodeAid was permitted. CodeAid, powered by GPT-3, did not directly disclose code solutions even when requested by students. Instead, it functioned like a teaching assistant, providing scaffolded responses in natural language, generating interactive pseudo-codes, and suggesting fixes without directly showing the corrected code. |
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## Dataset Use Cases |
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1. **Query Classification**: The dataset can be used to develop models that classify queries into categories explained in the paper such as the ones we identified in the thematic analysis of our CHI'24 paper: **Code and Conceptual Clarification**, **Function-Specific Queries**, **Code Execution Probes**, **Buggy Code Resolution**, **Problem Source Identification**, **Error Message Interpretation**, **High-level Coding Guidance**, and **Direct Code Requests**. |
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2. **Building Scaffolded LLM Responses**: This dataset can be used to iteratively design and test LLM-powered interactive interfaces that display scaffolded responses other than those used in CodeAid. |
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3. **AI in Education Research**: Researchers can use this dataset to study the role and effectiveness of LLMs, in educational settings. This can provide insights into how AI can be integrated into classrooms to enhance learning outcomes. |
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4. **Performance Benchmarking**: Tool designers can benchmark the performance of their tools and even AI models against real-world student queries, helping them iterate and improve their tools and models. |
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## Dataset Structure |
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The dataset includes the following columns: |
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- **user_id**: Unique identifier for the user. Type: String. |
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- **time**: Timestamp of when the event occurred. Format: ISO 8601, Type: DateTime. |
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- **feature_type**: Describes the type of feature the row represents, e.g., 'Question from Code'. Type: String. |
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- **feature_version**: Version of the feature. Type: String. Values: 'v1' (used `code-davinci-002`), 'v2' (used `gpt-3.5-turbo-1106`) |
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- **input_question**: The question input by the user. This column exists when `feature_type` is either `"General Question"`, or `"Question from Code". |
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- **input_code**: The code snippet provided by the user. This column exists when `feature_type` is either `"General Question"`, `"Question from Code"`, `"Help Fix Code"`, or `"Explain Code"`. |
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- **input_intention**: A brief description of what the user intends to achieve with the code. This column exists when `feature_type` is `"Help Fix Code"`. |
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- **input_task_description**: Detailed description of the task for which the code is written. This column exists when `feature_type` is `"Help Write Code"`. |
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## Citation |
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If you use this dataset in your research, please cite our paper: |
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``` |
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@article{kazemitabaar2024codeaid, |
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title={CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needs}, |
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author={Kazemitabaar, Majeed and Ye, Runlong and Wang, Xiaoning and Henley, Austin Z and Denny, Paul and Craig, Michelle and Grossman, Tovi}, |
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booktitle={Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems}, |
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year={2024} |
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} |
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``` |
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## License |
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This dataset is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). You are free to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material) under the following terms: |
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- **Attribution**: You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. |
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- **NonCommercial**: You may not use the material for commercial purposes. |
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For more details, please visit [Creative Commons — Attribution-NonCommercial 4.0 International — CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/). |