Introduction to Generative AI

Assignment created by David Hicks (School of Education), using prompts with ChatGPT

Other Assignments In This Series

This assignment is the first week of a five-week series on generative AI.

Rationale

This assignment introduces students to the basic concepts of generative AI, its capabilities, and limitations. It sets the foundation for understanding how AI can be a tool in their learning and professional development.

Objectives

  • Understand the basic principles of generative AI.
  • Identify the potential uses and limitations of AI in academic and professional settings.
  • Reflect on ethical considerations when using AI.

Activities

  1. Readings and Video:
  2. Comprehension Questions for Discussion or Homework:
    • What is generative AI, and how does it differ from other types of AI?
      Example response:
      Generative AI refers to AI systems that can generate new content, such as text, images, or music, based on training data. It differs from other types of AI, which may focus more on classification or prediction tasks.
    • List three applications of generative AI in different fields.
      Example response:
      Applications of generative AI include creating art (e.g., DALL-E), writing assistance (e.g., GPT-3), and drug discovery (e.g., AI-generated molecular structures).
    • What are some limitations of generative AI?

      Example response:
      Limitations of generative AI include potential biases in generated content, dependency on large datasets, and ethical concerns related to content creation and usage.
  3. Reflective Essay, assessed on understanding, critical thinking, and articulation of ideas:
    • Reflect on the readings, video, and classroom discussion.
    • Outline the essay, focusing on how AI might impact your field and ethical considerations.
    • Write the essay, incorporating personal reflections and examples.
    • Review and edit the essay for clarity and coherence.

Example Reflective Essay

Use the example essay below as a model or for class discussion of expectations.

The Role and Ethical Implications of Generative AI in Modern Education

Introduction

Generative AI represents a significant breakthrough in artificial intelligence, enabling machines to create new content, such as text, images, and music, based on the data they have been trained on. As an aspiring educator, understanding the potential and ethical implications of generative AI is crucial for leveraging this technology effectively in the classroom.

Understanding Generative AI

Generative AI systems, like GPT-3, are designed to produce human-like text by predicting subsequent words based on the input they receive. These systems have a broad range of applications, from writing assistance and content creation to enhancing virtual learning environments. The key to their functionality lies in large-scale neural networks trained on vast datasets, allowing them to generate contextually relevant and coherent content.

Applications in Education

In the educational sector, generative AI can transform teaching and learning experiences. Personalized learning is one of the most promising applications. By analyzing individual student performance, generative AI can create customized learning paths that address specific needs and learning paces, thereby improving educational outcomes. Additionally, AI-driven tutoring systems can provide real-time feedback and support, helping students grasp complex concepts outside the traditional classroom setting.

Ethical Considerations

While the benefits of generative AI are substantial, they come with significant ethical concerns. Data privacy is paramount; AI systems require access to extensive datasets, including personal student information, to function effectively. Ensuring this data is collected, stored, and utilized ethically is critical to protecting student privacy. Moreover, the potential biases embedded in AI models can perpetuate or even exacerbate existing inequalities. It is essential to implement measures to identify and mitigate these biases to promote fairness and inclusivity.

Conclusion

Generative AI offers exciting opportunities to enhance educational practices through personalized learning and intelligent tutoring systems. However, educators must remain vigilant about the ethical implications, particularly concerning data privacy and bias. By understanding and addressing these challenges, we can harness the power of generative AI to create more effective and equitable educational environments.

Reflective Essay Rubric

Table 1. Reflective Essay Rubric
Criteria Excellent
(A)		 Good
(B)		 Acceptable
(C)		 Needs Improvement
(D–F)
Reflection Depth Demonstrates thoughtful engagement with AI tools and ideas. Rich insights and original thinking about AI and its implications. Clear engagement with AI tools and some original insights. Basic reflection; some surface-level analysis or generalization. Lacks insight or connection to AI tools; minimal reflection.
Specificity of Examples Uses concrete examples from AI interactions. Detailed, relevant, and well-integrated examples of AI use. Several relevant examples, mostly well-integrated. Some examples, but vague or loosely connected. Few or no specific examples of AI interactions.
Structure & Organization Has a clear focus and logical development. Strong organization; ideas flow clearly with effective transitions. Good organization; mostly clear flow of ideas. Basic structure; ideas may jump or be loosely connected. Poor organization; lacks focus or logical flow.
Connection to Course Goals Links experiences to course learning outcomes. Strong connections to course themes and objectives. Clear connection to course themes, with some analysis. Some connection to course goals; may be underdeveloped. Little or no connection to course themes or outcomes.
Style, Grammar, & Mechanics Professional tone and careful proofreading. Polished writing; free from errors; engaging and clear. Minor errors; clear and appropriate tone. Several errors; occasionally unclear or awkward. Frequent errors; distracting or unclear writing.

 

Last Updated on July 7, 2025