This section presents assignments that enable students to understand how computational writing technologies might be integrated into workplace contexts. Unlike academic discourse, professional writing is not grounded in an ethos of truth-seeking and critical inquiry; it tends to be grounded in an ethos of efficacy as well as constraints of legality and workplace ethics.
Analeigh E. Horton
Fairleigh Dickinson University
This assignment asks researchers (most likely, graduate students, but anyone dealing with oral qualitative data) to explore traditional and modern methods of transcription. Students will learn how to work with different tools and consider the affordances and constraints of each, developing the ability to discern what approach is best for their specific study. This approach is particularly helpful for researchers who are unfamiliar with transcription processes and uncertain in determining the details they need to capture. This assignment can be modified to suit a range of transcription technologies to help students gain familiarity with various softwares.
Sara Large
Lasell University
This assignment asks students to engage with a large language model (LLM) such as ChatGPT 3.5 as part of their writing process to develop specific, accurate, and professional resume bullet points. After brainstorming work or community service experiences, students develop a list of tasks completed in these positions, along with the skills they would like to highlight for each task. Next, they ask ChatGPT to create bullet points for them based on this input, refine the input to tweak the responses, and revise the output to match their unique voice and skill set. Finally, students reflect on their experience using the LLM and revising its output. This assignment requires students to practice using generative AI as a tool to co-construct job application materials.