What is ChatGPT? Exploring AI Tools and Their Relationship with Education

Artificial Intelligence (AI) and machine-generated content have become prominent in educational discussions. Amidst technical jargon and concerns about the impact of traditional writing and learning, understanding these topics can be overwhelming. This toolbox guide simplifies the generative AI landscape, providing clear definitions and insights into some commonly used generative AI tools.

What is Generative AI?

To provide an introduction to generative AI, CATL has created an informative video presentation. This video, paired with interactive PowerPoints slides, serves as a valuable resource for understanding how generative AI tools work, their capabilities, and limitations.

Introduction to Generative AI – CATL Presentation Slides (PDF)

Common Generative AI Tools

One of the most popular AI-powered text generators is ChatGPT by OpenAI. Since its November 2022 release, various companies have developed their own generative AI applications based on or in direct competitive with OpenAI’s framework. Learn more about common generative AI tools below.

Note: For UWGB faculty, staff, and students, we recommend using Microsoft Copilot and other tools that do not require users to provide personal information in the sign-up process.

What Can Generative AI Tools Do?

The generative AI tools we’ve discussed so far are all trained on large datasets that produce outputs based on patterns in that dataset. User prompts and feedback can be used to improve their outputs and models, so these tools are constantly evolving. Explore below to learn about general use cases for generative AI tools and their limitations.

Generative AI tools can be used in a multitude of ways. Some common uses cases for text-based generative AI tools include: 

  • Language generation: Users can ask them to create essays, poems, or code snippets on a given topic.  
  • Information retrieval: Users can ask them to answer simple non-academic questions like “explain the rules of football to me” or “what is the correct way to use a semicolon?”  
  • Language translation: Users can ask them to translate words or phrases into different languages.  
  • Text summarization: Users can ask them to condense notes from a lecture and or long texts, including entire books, into shorter summaries. 
  • Idea generation & editorial assistance: Users can ask them to brainstorm and generate ideas for a story or a research outline or provide feedback on writing to make it more concise or formal.  

However, these tools also have some limitations, including but not limited to:  

  • Lack of real-world understanding: They do not understand the context and/or logic of the real world. They do not understand sarcasm, analogies, jokes, and satire. For example, an output created by the technology may be grammatically correct, but semantically is nonsensical or contradictory.  
  • Dependent upon the data it is trained on: They may produce outputs that are not accurate, relevant, or current because they rely on the data they are trained on. 
  • False results or hallucinated responses: They may produce outputs that are false, misleading, or plagiarized from other sources, and are unable to verify the accuracy of their outputs.  
  • Machine learning bias: They may produce outputs that are discriminatory or harmful due to bias in the data they are trained on.  

The possibilities of tools like ChatGPT seem to be almost endless — writing complete essays, creating poetry, summarizing books and large texts, creating games, and translating languages and data. ChatGPT and its contemporaries can understand text and spoken words similar to how human beings can. These tools have become more conversational and corrective with each update, making it difficult to discern between what is generated by an AI and what is produced by a human. In addition, the data and algorithms they draw from imitate the way humans learn and can gradually improve their accuracy the more you interact with it. As explored above, they offer large potential in their use cases, yet they still come with their own set of limitations to consider.

What Does This Mean for Educators?

The existence of this technology raises questions about which tasks will be completed all or in part by machines in the future and what that means for our learning outcomes and assessments. Some experts are also discussing to what extent it should become part of the educational enterprise to teach students how to write effective AI prompts and use tools like ChatGPT thoughtfully to produce work that balances quality with efficiency.

One way to approach the conversation surrounding AI technology is to consider these applications as tools that educators can choose either to work with or without in their classes. Some may also consider teaching their students how to use these tools most effectively and/or integrating lessons on AI ethics into their teaching. With any teaching tool we look to incorporate, we must provide proper thought, scaffolding, and framing around what it can do and where it falls short so that students can use the tool responsibly.

Learn More

Explore even more CATL resources related to AI in education:

If you have questions, concerns, or ideas specific to generative AI tools in education and the classroom, please email us at catl@uwgb.edu or set up a consultation!

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