Prompt Engineering: Length
The assignment teaches students to specify the desired length of ChatGPT responses, enabling them to receive information in various formats, from concise summaries to detailed essays, depending on their needs.
Undergraduate
Prompt Engineering: Sophistication
The assignment encourages students to specify the level of sophistication in their prompts, allowing them to receive responses that match their desired depth and complexity, whether for beginner or advanced understanding.
Prompt Engineering: Specified Style
The assignment encourages students to engage creatively by asking ChatGPT to deliver explanations or summaries in the style of famous authors or artists, making learning more enjoyable and memorable.
Prompt Engineering: Tone
The assignment allows students to explore and understand different tones by having them generate responses in various styles, such as playful, sarcastic, or authoritative, helping them recognize how tone impacts communication.
Prompt Engineering: Context and Specific Requests
The assignment teaches students to use graduated prompts, starting with broad inquiries and progressively adding more details, helping them understand how specificity impacts the quality and accuracy of ChatGPT’s responses.
Prompt Engineering: Rephrase Prompts
By rephrasing prompts, students learn how different wording can elicit varied responses, leading to a deeper and more nuanced understanding of the subject matter as they explore different angles and perspectives.
Prompt Engineering: Regenerate a Response
Students learn to generate and compare multiple responses from a single prompt, which helps them understand how different approaches and wordings can convey varying perspectives and nuances on the same topic.
Prompt Engineering: Conversation
The assignment introduces students to the technique of prompt chaining, teaching them how to build on previous prompts to extract more detailed and precise information, thereby enhancing their query formulation skills.
AI Classroom Activity: Machine Learning
The assignment provides students with practical experience in machine learning by engaging them in activities that involve training algorithms and analyzing data, making complex concepts more accessible through hands-on application.
AI Classroom Activity: Facial Recognition
Students gain practical knowledge of how facial recognition systems work, including the technical aspects of image processing and machine learning algorithms. The assignment emphasizes the importance of discussing the ethical implications of facial recognition technology, encouraging students to think critically about privacy, consent, and bias issues.
The Intelligent Piece of Paper
The assignment encourages students to engage with technology by creating interactive paper circuits, combining traditional paper-based materials with modern electronics to enhance learning.
Generate and Enact a Writing Style: Examining Writing Style Though Generative AI
Students collaborate with peers from different disciplines, using AI text generators. The collaboration enhances their understanding of writing styles across various fields and fostering diverse perspectives in their work.
Using AI Text as Prompts for Critical Analysis
Students are provided with AI-generated texts relevant to the course topics and are asked to comment, review, and expand on these texts using text-editing software.
Writing Against the Machine: Debating with ChatGPT
Students use ChatGPT to generate counterclaims or alternative arguments to their initial thesis. This process helps them refine, extend, and evolve their argumentative skills by considering multiple perspectives.
Genre Generators
Students begin by collaboratively analyzing implementations of text generators, such as Christopher Strachey’s Love Letter Generator. Next, students work in groups to create non-executable conceptual programs designed to produce new instances of chosen genres.
Using LLMs as Peer Reviewers for Revising Essays
Students utilize Large Language Models (LLMs) such as ChatGPT to assist in the peer review process by generating responses to common peer review prompts.
Synthetic Metacognition: Iterating Prompts with GPTs
Students engage in prompt engineering by iteratively refining and tweaking the set of instructions given to a Large Language Model (LLM). Through a collaborative workshop format, students work in groups to analyze the AI’s output, discuss its strengths and weaknesses, and propose improvements.
Decoding an AI Bot’s Chatting Pattern: Text Generating Technology Analysis Assignment
Students engage in sustained conversations with AI chatbots like ChatGPT, analyzing the bots’ writing and thinking patterns. The assignment prompts students to consider the ethical implications of using AI chatbots, including issues related to plagiarism, authorship, and the potential displacement of human labor.
Repetition
This assignment serves as a beginner-level programming exercise that introduces students to the concept of iteration using for loops. By writing code that repeats a word or phrase 50,000 times, students gain a fundamental understanding of how loops work in programming.
AI in First Year Writing Courses
The assignment introduces an “AI Standards of Conduct” framework that differentiates between AI-assisted and AI-generated writing. The assignment encourages students to reflect on the ethical implications of using AI in writing.
Professor Bot: An Exercise in Algorithmic Accountability
Students explore and reflect on algorithmic accountability through a speculative scenario where an AI called Professor Bot grades entrance essays.
Teaching Social Identity and Cultural Bias Using AI Text Generation
Students reflect on their personal histories and preferences by participating in an interactive survey. These responses are then analyzed using text generation models to explore how AI interprets and predicts social identities, highlighting the biases and assumptions inherent in AI technology.
The Term Paper Turing Test
Students use accessible language models to generate parts of their term papers. This hands-on experiment helps students explore the capabilities and limitations of AI in writing, as well as the ethical dimensions of using such tools.
Promoting Ethical Artificial Intelligence Literacy
By comparing AI-generated outputs with their own work and reflecting on these comparisons, students develop enhanced metacognitive skills, which are crucial for their personal and professional growth.