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Decoding the Impact of Generative AI on Teaching and Learning at UNF

The advent of ChatGPT and other forms of Artificial Intelligence appears to have sparked an existential debate within the realm of higher education. What will this tool mean for students, faculty, administrators, and the very future of education?

The responses to this pivotal question are as diverse as they are intriguing. For some, this tool represents a potential threat to academic integrity and should be banned from learning environments, with firm restrictions implemented to prevent its use. Conversely, others see this technology as the inevitable future of many fields, viewing universities as the ideal places for students to learn how to utilize it for specific purposes. A third group may find themselves in the middle, grappling to fully understand what this tool is and the unique challenges and opportunities it presents.

This website has been developed with each of these perspectives in mind. We provide resources for those primarily focused on academic integrity and the establishment of clear guidelines; we offer tools for those eager to harness the power and potential of AI in their learning or teaching; we also cater to those simply wishing to expand their understanding of AI and its potential implications for education, aiding in the development of a more informed stance.

For those newly venturing into the realm of AI and its implications for education, a beneficial first step would be familiarizing themselves with key terms pertinent to this exploration. This list offers a foundational understanding of some of the most significant terms in this emerging landscape, along with examples of their applications.

Artificial Intelligence Definitions

We include several key terms important for developing a comprehensive understanding of Artificial Intelligence and the broad spectrum of tools and functions within this field.
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Suggested Syllabus Language

We've written suggested syllabus language for various perspectives, so there's something for instructors interested in using generative AI as part of their coursework and instructors looking to prohibit the use of generative AI.
Learn More...
A human hand reaches out to touch an artificial hand through the screen of a laptop
  • Using Generative AI Ethically
    We've written suggested syllabus language for various perspectives, so there's something for instructors interested in using generative AI as part of their coursework and instructors looking to prohibit the use of generative AI.

    You're welcome to use the language we've included on this page as part of your syllabus.
  • Identifying AI-Generated Content
    With recent advances in artificial intelligence, it's becoming increasingly difficult to distinguish between human-generated and AI-generated content. However, there are usually clues. 
    Here are some tips and tools for identifying AI-generated text:
     
    1. The Content is Inconsistent: AI-generated text might contain logical inconsistencies, abrupt topic changes, or an abnormal degree of repetition.

    2.  The Content Lacks Depth: While AI can generate relevant content, it often lacks depth and insight because our varied perspectives on complex topics come from lived experience and human expertise.

    3. Unusually Poor Grammar and Syntax: Keep an eye out for unusual phrasing, grammatical errors, or the misuse of common idioms because generative AI works by assuming the next word in a sentence according to observed patterns. This reality means artificial intelligence gets language wrong sometimes.

    4. Fails Fact-Checking: AI generates content based on its training data and doesn't fact-check the information it generates. So, confidently stated misinformation may indicate artificially generated content.

    5. Fails Plagiarism Checkers: Turnitin initially claimed to identify AI-generated content with 98% to 99% accuracy; however, third-party reviews have revealed higher rates of false positives. Additionally, OpenAI (the creators of ChatGPT) admitted that they could not reliably detect the use of their software. Learn More about UNF and AI-Detection
  • Examples of Generative AI
    1. Microsoft Copilot: Copilot currently generates text with OpenAI’s GPT-4 model and creates images using DALL-E 3. UNF is proud to offer Copilot with Data Protection, an enterprise-level AI tool from Microsoft for all UNF students, faculty, and staff.

    2. ChatGPT-4: A more powerful variant of GPT-3, ChatGPT-4 is used to generate responses and create conversational agents or chatbots that can interact with students for tutoring or customer service purposes.

    3. Artbreeder: This tool combines images to create new ones and can be helpful in fields like art, graphic design, and visual communications for generating unique visual content.

    4. Jukin Media: This is a music generation AI useful in music and entertainment education for creating new tunes and understanding music composition./p>

    5. Tensorflow Playground: A tool to understand and create neural networks. Although not strictly a generative AI, it’s a learning tool that offers hands-on learning about how AI works.

    6. MuseNet: Developed by OpenAI, MuseNet can generate 4-minute musical compositions with ten different instruments and combine styles from country to Mozart to The Beatles, creating a novel tool for music education.

    7. WriteWithTransformer: A tool by Hugging Face that can complete texts with the power of AI, offering a practical tool for writing and literature classes to generate ideas.

    8. Grammarly: While not purely a generative AI, Grammarly utilizes AI to provide writing assistance, from checking grammar and punctuation to suggesting better ways to frame sentences.

    9. Google’s Bard: Bard is a conversational generative artificial intelligence chatbot developed by Google, based initially on the LaMDA family of large language models and later the PaLM LLM.

    10. Copy.ai: Copy.ai is an AI-powered tool that helps generate creative content, such as blog posts, marketing copy, and more. It can be helpful in communication, marketing, and business courses, offering students a chance to see how AI can assist in drafting professional content.

    11. DALL-E: Created by OpenAI, DALL-E generates unique images from textual descriptions, providing a powerful tool for graphic design, art, and visual communication courses.

    12. DeepArt.io: This tool uses AI to transform photos into works of art, mimicking the styles of famous artists. It can be a valuable tool for art, design, and digital media studies.

    13. Runway ML: This creative toolkit uses machine learning models to aid in image creation, making it useful in a wide range of disciplines, from design to digital media.

    14. This Person Does Not Exist: This website uses AI to generate realistic human faces of people who do not exist. It could be useful in digital arts, psychology, and sociology for discussing perception and reality.

    15. Lobe.ai: This tool makes it easy to create machine learning models for visual recognition tasks, which can benefit computer science, data analysis, and engineering courses. 

Understanding Generative AI

 
Generative AI is a branch of artificial intelligence that uses machine learning models to generate new data from existing data sets. This technology is behind chatbots, personalized marketing emails, automatic content generators, and more. It can create human-like text, compose music, generate images, and provide a plethora of other creative outputs. For a more detailed introduction, please view our library of AI definitions.
 

Generative AI in Education

 
There are several ways Generative AI can be used in educational settings. The most common use is as a tutoring tool where AI can generate personalized content to assist students in their studies. For example, the use of AI in answering students' queries, offering additional learning resources based on their specific needs, and personalizing the learning process. With proper review and fact-checking, generative AI can also be used to speed up the process of grading assignments, providing feedback, and creating content for courses.
 

Benefits and Challenges of Generative AI

 
As with all technology, generative AI comes with its own set of benefits and challenges. While it can enhance the learning experience through personalized content, we must consider data privacy, the ethical use of AI, and the potential for misuse. That's why we encourage our faculty and students to return to this page as necessary to guide their understanding of these aspects .
 

Generative AI at UNF

 
At UNF, we're excited about the potential of generative AI because we know that with proper care it can enhance our educational tools and resources. We know technology is a huge part of your life, so we're committed to actively exploring the implementation of this technology as it relates to higher-education.
 
Small people working with big technology to showcase ai integrations in communication and reporting
 

Partnering for the Future

 
Generative AI has the potential to revolutionize education, and at UNF, we're committed to staying ahead of the curve. That's why so many passionate voices from across the UNF community have joined together to create this resource and assist you in harnessing the power of AI to enhance the teaching and learning experience.
 
As we embrace this new era, we encourage our faculty and students to provide feedback and share their experiences with AI in education. Remember, we're all on this journey together, and your insights are invaluable in helping us shape our AI strategy.
 
For further reading and resources on Generative AI, we recommend checking out these additional resources.

Further Reading