Teaching Writing Across the Curriculum with AI
Writing Across the Curriculum Assignments, Classroom Activities, and Educational Resources for Higher Education
This lesson plan teaches students how AI is trained using data they share online. Through illustrations, discussions, and real-life examples, students learn the importance of data in AI development and enhance their critical thinking and writing skills.
Through discussions, definitions, and reflective activities, students develop a critical understanding of facial recognition and its impact on privacy, enhancing their analytical and writing skills.
Students conduct a rhetorical analysis of the outputs generated by ChatGPT, critically evaluating the AI’s responses and the effectiveness of their own writing in eliciting meaningful and accurate information.
Students analyze real-world case studies that illustrate the potential pitfalls and ethical considerations of AI applications, enhancing their understanding of AI’s impact on society.
This curriculum introduces the technical details of how AI systems generate content using context, allowing students to engage actively with the material.
Students transform theoretical concepts into practical solutions by using AI tools to generate software code. ChatGPT can provider guidance, explanations, and code generation support. This interactive learning approach encourages problem-solving and helps students create and test their software projects effectively.
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.
The assignment encourages students to engage with technology by creating interactive paper circuits, combining traditional paper-based materials with modern electronics to enhance learning.
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.
Students generate text using both analog cut-up techniques and a simple Markov procedure. This exercise introduces them to found art, encouraging them to critically examine issues of property and power in the context of generative text and its sources.
Students use the JavaScript library Tracery to create procedural texts that generate new content based on predefined rules and word banks. This approach explores the power of randomness and variability in text generation, akin to advanced Mad Libs.
This assignment helps students grasp core aspects of narrative theory by requiring them to generate multiple variations of an underlying story. Students use Curveship-js, a JavaScript framework, to implement their narrative variations.
Students engage in hands-on activities where they create prompts, analyze the outputs generated by LLMs, and reflect on the outcomes.
Students create “spells,” or poems based on a wish, and then use a large language model (LLM) to generate a corresponding AI-created spell.
Students manually apply an algorithm to generate a Markov Chain from a given text extract, providing a concrete and interactive way to understand probabilistic language generation.