ChatGPT for Teaching and Learning: An Experience from Data Science
Education
- URL: http://arxiv.org/abs/2307.16650v1
- Date: Mon, 31 Jul 2023 13:31:19 GMT
- Title: ChatGPT for Teaching and Learning: An Experience from Data Science
Education
- Authors: Yong Zheng
- Abstract summary: ChatGPT, an implementation and application of large language models, has gained significant popularity since its initial release.
This paper aims to bridge that gap by utilizing ChatGPT in a data science course, gathering perspectives from students, and presenting our experiences and feedback on using ChatGPT for teaching and learning in data science education.
- Score: 5.406386303264086
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: ChatGPT, an implementation and application of large language models, has
gained significant popularity since its initial release. Researchers have been
exploring ways to harness the practical benefits of ChatGPT in real-world
scenarios. Educational researchers have investigated its potential in various
subjects, e.g., programming, mathematics, finance, clinical decision support,
etc. However, there has been limited attention given to its application in data
science education. This paper aims to bridge that gap by utilizing ChatGPT in a
data science course, gathering perspectives from students, and presenting our
experiences and feedback on using ChatGPT for teaching and learning in data
science education. The findings not only distinguish data science education
from other disciplines but also uncover new opportunities and challenges
associated with incorporating ChatGPT into the data science curriculum.
Related papers
- ChatGPT in Research and Education: Exploring Benefits and Threats [1.9466452723529557]
ChatGPT is a powerful language model developed by OpenAI.
It offers personalized feedback, enhances accessibility, enables interactive conversations, assists with lesson preparation and evaluation, and introduces new methods for teaching complex subjects.
ChatGPT also poses challenges to traditional education and research systems.
These challenges include the risk of cheating on online exams, the generation of human-like text that may compromise academic integrity, and difficulties in assessing the reliability of information generated by AI.
arXiv Detail & Related papers (2024-11-05T05:29:00Z) - Adoption and Impact of ChatGPT in Computer Science Education: A Case Study on a Database Administration Course [0.46040036610482665]
This contribution presents an exploratory and correlational study conducted with 37 students who used ChatGPT as a support tool to learn database administration.
The usage and perceived utility of ChatGPT were moderate, but positive correlations between student grade and ChatGPT usage were found.
arXiv Detail & Related papers (2024-05-26T20:51:28Z) - Enhancing Programming Education with ChatGPT: A Case Study on Student Perceptions and Interactions in a Python Course [7.182952031323369]
This paper explores ChatGPT's impact on learning in a Python programming course tailored for first-year students over eight weeks.
By analyzing responses from surveys, open-ended questions, and student-ChatGPT dialog data, we aim to provide a comprehensive view of ChatGPT's utility.
Our study uncovers a generally positive reception toward ChatGPT and offers insights into its role in enhancing the programming education experience.
arXiv Detail & Related papers (2024-03-20T15:47:28Z) - Integrating ChatGPT in a Computer Science Course: Students Perceptions
and Suggestions [0.0]
This experience report explores students' perceptions and suggestions for integrating ChatGPT in a computer science course.
Findings show the importance of carefully balancing using ChatGPT in computer science courses.
arXiv Detail & Related papers (2023-12-22T10:48:34Z) - Exploring ChatGPT's Capabilities on Vulnerability Management [56.4403395100589]
We explore ChatGPT's capabilities on 6 tasks involving the complete vulnerability management process with a large-scale dataset containing 70,346 samples.
One notable example is ChatGPT's proficiency in tasks like generating titles for software bug reports.
Our findings reveal the difficulties encountered by ChatGPT and shed light on promising future directions.
arXiv Detail & Related papers (2023-11-11T11:01:13Z) - Transformative Effects of ChatGPT on Modern Education: Emerging Era of
AI Chatbots [36.760677949631514]
ChatGPT was released to provide coherent and useful replies based on analysis of large volumes of data.
Our preliminary evaluation concludes that ChatGPT performed differently in each subject area including finance, coding and maths.
There are clear drawbacks in its use, such as the possibility of producing inaccurate or false data.
Academic regulations and evaluation practices need to be updated, should ChatGPT be used as a tool in education.
arXiv Detail & Related papers (2023-05-25T17:35:57Z) - ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large
Language Models in Multilingual Learning [70.57126720079971]
Large language models (LLMs) have emerged as the most important breakthroughs in natural language processing (NLP)
This paper evaluates ChatGPT on 7 different tasks, covering 37 diverse languages with high, medium, low, and extremely low resources.
Compared to the performance of previous models, our extensive experimental results demonstrate a worse performance of ChatGPT for different NLP tasks and languages.
arXiv Detail & Related papers (2023-04-12T05:08:52Z) - To ChatGPT, or not to ChatGPT: That is the question! [78.407861566006]
This study provides a comprehensive and contemporary assessment of the most recent techniques in ChatGPT detection.
We have curated a benchmark dataset consisting of prompts from ChatGPT and humans, including diverse questions from medical, open Q&A, and finance domains.
Our evaluation results demonstrate that none of the existing methods can effectively detect ChatGPT-generated content.
arXiv Detail & Related papers (2023-04-04T03:04:28Z) - Does Synthetic Data Generation of LLMs Help Clinical Text Mining? [51.205078179427645]
We investigate the potential of OpenAI's ChatGPT to aid in clinical text mining.
We propose a new training paradigm that involves generating a vast quantity of high-quality synthetic data.
Our method has resulted in significant improvements in the performance of downstream tasks.
arXiv Detail & Related papers (2023-03-08T03:56:31Z) - Is ChatGPT a General-Purpose Natural Language Processing Task Solver? [113.22611481694825]
Large language models (LLMs) have demonstrated the ability to perform a variety of natural language processing (NLP) tasks zero-shot.
Recently, the debut of ChatGPT has drawn a great deal of attention from the natural language processing (NLP) community.
It is not yet known whether ChatGPT can serve as a generalist model that can perform many NLP tasks zero-shot.
arXiv Detail & Related papers (2023-02-08T09:44:51Z) - A Categorical Archive of ChatGPT Failures [47.64219291655723]
ChatGPT, developed by OpenAI, has been trained using massive amounts of data and simulates human conversation.
It has garnered significant attention due to its ability to effectively answer a broad range of human inquiries.
However, a comprehensive analysis of ChatGPT's failures is lacking, which is the focus of this study.
arXiv Detail & Related papers (2023-02-06T04:21:59Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.