Abstract: This article describes a gamified technical writing assignment inspired by the Hunt a Killer board games. Students solve a fictional mystery by analyzing AI-generated technical documents and are introduced to the most common deliverables and genres in the field of Technical and Professional Communication (TPC). Bolstered by research on gamification and rhetorical genre studies, this activity fosters experiential learning by using technical writing genres as structured and dynamic tools. In combining genre analysis with collaborative problem-solving, the assignment offers a novel approach to teaching genre in technical writing through its emphasis on flexibility and critical thinking.
Dear Investigator,
Dr. Harper has been found dead under mysterious circumstances, and the case has left the scientific community in disarray. As part of the investigation, you will step into the role of a technical writer tasked with uncovering hidden clues within technical documents that may point to the truth behind this untimely death.
These words begin the prompt for a semester-long assignment in my ENG 2135: Technical Writing course. But here’s the twist: the documents students analyze have been crafted using artificial intelligence. Their challenge is not only to solve the case but also to navigate the nuanced genres of technical communication and decipher the narrative woven into these texts. Will they untangle the clues, or will the mystery remain unsolved forever? The truth lies somewhere between AI and genre.
In technical writing classrooms, AI-generated documents can serve as models and puzzles—texts to be analyzed for genre conventions, rhetorical moves, and audience assumptions. Such documents are especially useful when scaffolding student learning outcomes focused on genre awareness and analysis.
My university’s ENG 2135: Technical Writing is a sophomore-level elective English course that introduces scientific and technical writing and officially belongs to the public and professional writing minor but draws students from across disciplines. It is populated mostly by humanities, communication, and STEM majors. This mixture of students (also at varying enrollment levels) makes for an interesting space in which I must toe the lines between introductory and advanced material and humanities and science-based epistemologies.
This assignment—a murder mystery game based on the Hunt a Killer board games—asks students to solve an AI-generated mystery from clues embedded in standard technical writing documents. Students investigate abbreviated versions of technical documentation and must work through/around/with the content and genre to decipher hidden elements and solve the mystery. I introduce this assignment on the first day of class, and we spend approximately two weeks analyzing the genres, documents, and hints to solve the mystery. While these documents originate from AI, I carefully revise, massage, and design them to fit my rhetorical needs (namely, enhanced clarity and cohesiveness). At the end of the semester, students create their own versions of these documents (entirely on their own—without the use of AI) for the next class of students to decipher. This essay will focus on the analysis that occurs during the first half of the semester.
Now, back to our specific case. Dr. Evelyn Harper is the fictional lead scientist for the Institute of Nuclear Semiotics, a group of scientists working to design and implement signage to communicate long-term nuclear waste warnings. She was found murdered in her laboratory under suspicious circumstances. The suspects include her fellow researchers, a mysterious hooded figure caught on security footage, and the security guard on duty. Students must work together to solve her murder, piecing together clues from technical documentation and then reflecting on their findings in nuanced and explicit language.
Teaching technical writing often requires a balance of creativity and clarity. This is never more evident than when discussing the nuances of genre in Technical and Professional Communication (TPC). Students need a framework for effective communication based on established conventions of the genre, but they also must see genres as dynamic and context-sensitive tools. The convergence of gamification, artificial intelligence, and rhetorical genre studies is one pathway for achieving this balance.1
Gamification usefully shifts the focus of learning by achieving traditional educational goals via a playful, competitive, and collaborative structure. Generally, games have been found to enhance students’ writing skills across various (Guo et al. 2023). In the technical writing classroom, games can also encourage student engagement and position genre as a tool for problem-solving, whether that be in real or imagined rhetorical contexts. Gerdes et al. (2020) illustrated how gamified projects such as writing video games allow students to confront genre conventions while experimenting with iterative design and usability—two concepts fundamental to technical writing/writers. Gamification invites students to inhabit the role of technical writers, immersing them in the lived experience of navigating genre conventions—tools that both guide and limit rhetorical action. This pedagogical approach aligns naturally with technical and professional communication (TPC), a field situated at the crossroads of precision and interpretation, where the technical meets the symbolic and where games can reflect both dimensions (deWinter and Vie 2016).
This tension pairs well with research on rhetorical genre studies. Carolyn Miller’s (1984) argument that genres are “typified rhetorical actions based in recurrent situations” (p. 159) allows us to resituate genres as dynamic and responsive rather than rigid and prescriptive (although it can sometimes read as the latter in technical writing situations), to help students negotiate the constraints and affordances of genre. Similarly, Miller argues that “if genre represents action, it must involve situation and motive” (p. 152). This perspective aligns seamlessly with game-based learning, especially the murder mystery genre requirements of motive, means, and opportunity. When students interact with genre through these kinds of creative assignments, such assignments highlight the adaptability of genres in balancing “stability and innovation, connecting theory and practice, agency and structure, form and substance” (Carolyn R. Miller, Devitt, and Gallagher 2018, 269). These game-based activities prompt students to identify motive and action within technical documents—elements often overlooked in genres typically perceived as rigid or formulaic.
To overcome Wardle’s (2009) now-famous critique of “mutt genres”— genres that exist to serve only the writing classroom in which they are embedded—students must be given interactions with genre that push the boundaries of usage and contextual flexibility. Closing this gap between the writing classroom and the professional workplace is especially frustrating for teachers of classes like technical writing, where there is often so much push to produce perfect genres that perform their professional functions. Although writing about genres specific to nonprofits, Gindlesparger (2019) rightfully argues that “disciplinary boundaries within professional education can discourage the risk-taking necessary to learn these rhetorical skills” (p. 56). It is precisely these disciplinary limitations that gamification can help to overcome, but not without explicit and specific application of transferrable skills—namely, the translation of information between diverse audiences.
Technical writing, generally seen as the go-between for specialized knowledge and readers (Killingsworth and Gilbertson 1992), has always benefited from new technologies such as Alternate Reality Games (ARGs) and AI. Johnson-Eilola (1996) argues that students need training, practice, and reinforcement in collaboration, abstraction, experimentation, and system thinking. Assignments like this achieve those goals by bringing students together to abstract important information, experiment with its logical arrangement, and place it within a system of thinking and doing. Another example of this theory at work is Balzotti and Hansen’s (2019) notion of playable case studies, which immerse students in simulated environments and narratives via ARGs to teach workplace literacies in technical communication courses. These playable case studies quite literally embody their rhetorical purpose and the generic purpose of most technical writing genres: information transfer.
These activities turn AI into a heuristic rather than a replacement for human creativity for navigating the genre constellation or ecology (Spinuzzi and Zachry 2000) of TPC settings. AI’s capacity to generate complex and nuanced texts under specific genre constraints allows students to engage with genre in ways that rhetorical genre studies ask us to, while also illuminating the impact that gamification can have in the classroom and overcoming some of the challenges in the field of technical and professional communication. Thus, in my murder mystery game assignment, students must decode the subtle interplay between language, structure, and rhetorical purpose.
It is crucial, though, to acknowledge that AI’s place in the writing classroom is contentious both within the field and outside of it. While some instructors disagree, I believe that AI–like many writing technologies before it—is here to stay. Restrictive policies and practices that ignore the reality of AI’s presence do not work, and large language models’ ability to generate complex texts that challenge students to analyze genre conventions, audience assumptions and expectations, and rhetorical strategies is worth the labor investment of integrating it into the classroom. Recent studies (such as Mehlenbacher, Balbon, and Mehlenbacher 2025) are taking up this work. They remind us that the interplay of generation and revision is most important (p. 182) in the same way that the interplay between genre and algorithms presents fruitful and dynamic discussion.
In my assignment, AI is the initial generator, yes, but it is also heavily edited to reflect the course’s needs, students’ learning levels, and my understanding of the genres I asked it to produce. This distinction of labor is elaborated by Knowles’ ((2024)) rhetorically precise distinction between humans-in-the-loop (HITL) and machine-in-the-loop (MITL) writing workflows. HITL writing encompasses any collaboration where humans retain some rhetorical load, but GenAI tools carry a significant portion of the invention, arrangement, or memory tasks. In contrast, MITL writing positions the machine as a subordinate assistant, with the human author retaining the majority of rhetorical labor. In my assignment, students take a MITL approach to direct and evaluate AI-generated content, using it to augment their own work rather than relying on it to generate ideas or structure. This approach ensures that AI complements, rather than replaces, teacher and student agency in the writing process. Similarly, the Modern Language Association–Conference on College Composition and Communication (MLA-CCCC) Joint Task Force on Writing and AI (2023) asserts that “policies should support the development of critical AI literacy” (p. 8), and a project where students analyze and reflect on AI-generated content does precisely that.
Certainly, non-AI alternatives exist in the form of pre-packaged sets (such as the Hunt a Killer board games) or freeware roleplaying script games like The Business of Murder or even compilation message boards and free resources like boardgamegeek.com. However, the integration of technical writing genre conventions with the actual mystery makes using AI to design these documents unique.
When applied to an academic context, gamification situates students within interactive, high-stakes scenarios where genre knowledge is interrogated and conventions are analyzed under pressure. At the same time, AI is the laboratory for generating and manipulating the texts they interact with. Rhetorical genre studies anchors these activities by ensuring students move past rigid understandings of genre. Students, at once, inhabit the roles of technical writers, detectives, and storytellers to uncover hidden meanings; analyze (and eventually create) genre-complimenting and conflicting texts; and advance the story’s narrative. Then, they reflect on the rhetorical strategies that guided their decisions.
My goal for this section of the essay is to share a brief daily breakdown of this project. In the ancillary materials files and in Table
1, you can also find a complete breakdown of materials for running the mystery at the Institute of Nuclear Semiotics and templates for making your own. Throughout the project, I make clear that this content was generated using AI and edited by me so that students are always/already aware of its origins. Typically, this disclosure leads to generative discussions of the veracity and reliability of AI in producing these documents. I show them the original AI outputs and compare those to the final edited versions. I also clarify that these documents are just some of the genres common to technical and professional communication, a representative sample of the field in some ways. I also explain that these documents are abbreviated versions of the longer-form documents they would likely encounter as technical writers. This design choice is to avoid burnout and to ease students into the genres without overwhelming them with entire white papers or user manuals, to name a few examples.
Day 1: As mentioned, the game begins on the first day of the course, where I give students a brief overview of the field of Nuclear Semiotics and a dramatic presentation on this fictional mystery. I introduce the characters (presented in personnel files) and the plot while distributing the initial documents: meeting minutes, a project plan, and a white paper (Table 1). These documents introduce the tension in the meeting (a report that something has gone wrong with the major project), details of the project’s timeline and budget, and the scientific criteria for testing the project (all crucial in the data analysis later). I then spend class time guiding students through the requirements of the technical writing chart, which is attached to their assignment sheet, for each document. I explain how each document we are analyzing meets the purpose, style, and tone of technical writing. I ask them to think through how these documents might have dual technical and public audiences, and we find fuller examples of these documents together online. Lastly, I walk students through the first clue analysis (namely, that the data report does not match the testing criteria established in the white paper—suggesting foul play). Before they leave, I remind them of the three big questions they will need to answer as they investigate:
Who killed Dr. Harper? What evidence do you have (including means, motive, and opportunity) that leads you to believe that?
What went wrong with the project? What evidence do you have that leads you to believe that?
Who is the mysterious hooded figure? What evidence do you have that leads you to believe that?
| Day | Materials Distributed | In-Class Activities |
|---|---|---|
| assignment overview-“Hello Investigator” introduction letter, personnel files, meeting minutes, project plan, abbreviated white paper |
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| user manual, test results, email screenshots, |
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| security incident report, access logs, interrogation transcript |
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| assignment overview-deliverables breakdown |
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Day 2: We establish groups at the beginning of the class. Students receive the user manual, test results, and email screenshots to add to their packets, and I set them on the task of finding clues and establishing the potential motive (tension between two of the characters) together. Toward the end of class, I focus on data interpretation, which also serves as a moment for them to check their analysis skills because I point out inconsistencies in the results. Importantly, I try to avoid language that directly tells them about the issues with the data and instead ask leading questions to help them discover the issues on their own. For example, instead of outright stating that some of the results are coded as a failure when they should be a pass, I ask them to compare the criteria for a passed test to specific lines of the data and then attend to the pass/fail indicator column. I also stop to demonstrate how email can be considered technical communication when the content is appropriate. We talk about tone, style, structure, and public vs. private audiences. We work through the chart in their assignment sheet for each document and slowly broaden our understanding of genre and technical writing by complicating the application with their prior knowledge of these genres. The goal here is to use discussion of these example documents (although fictional) to help students understand the rhetorical functions and recurrent features of genres.
Day 3: The security incident report, access logs for the lab, and interrogation transcript are distributed. We spend the majority of this day understanding the documents and reading the interrogation transcript together. Students eventually break off into groups to pull out clues, and I introduce a highlighting strategy wherein they use one color (or annotation symbol) to indicate what they believe to be critical clues and what they believe to be red herring clues. Toward the end of class, I redirect them to review their previous documents as a group and perform this annotation strategy on them. Returning to these artifacts and annotating them with all pieces of evidence in one place allows them to revisit and reevaluate their previous assumptions and begin to gather their answers to the big questions.
Day 4: We spend most of class time working through the reflection prompt and writing out the answers to the big questions. Before this, I also review what they have learned and how this project meets key student learning outcomes for the course. Specifically, I relate the work back to identifying/analyzing technical communication genres and engaging in critical/systems thinking. After this, we review the reflection questions and discuss where they might find evidence to answer them. I draw parallels between the fictional detective work they did to solve the case and the very real detective work of reflecting on their learning. Finally, students work independently on answering the big questions and writing their reflective memos. I do grade partially on the correctness of their deduction; however, after they turn in their reports, I reveal that any of the characters could be the culprit and that I will accept almost all answers so long as they are supported by relevant and sufficient evidence.
As mentioned, solving the mystery is but half of the assignment as I run it in my class. At the end of the semester, I also have students create their own versions of these documents independent of AI and complete with clues (both critical and red herring) so that they usefully frame the semester with reflections on genre, flexibility, and technical writing’s place in the world, a direct tie into the course’s learning objective for recognizing, analyzing, and contextualizing common TPC genres.
Playing with genre as actionable (Miller 1984), agential (Carolyn R. Miller, Devitt, and Gallagher 2018), and adaptable (Gindlesparger 2019; Wardle 2009) allows the technical communication educator to transgress genre boundaries but also bring new meaning to a field which students may misunderstand as static or “boring” in its adherence to these generic specifications.
Each time I run this assignment, I find new ways that students engage with the content and exercises. They’re often surprised by how engaging and rigorous technical writing can be. The mix of humanities, communication, and STEM students brings diverse approaches to the game.
Reflections often include initial confusion about the content and form of the documents, which is almost always resolved by the end of the project. They’re surprised by the range of genres considered to be technical writing and how their prior assumptions were challenged by analyzing documents as clues as opposed to decontextualized models of the genres. Some students are frustrated by the lack of black-and-white answers to the mystery. These students are often from science backgrounds, which stimulates another fruitful discussion about the value of nuance and rhetorical flexibility in STEM disciplines as well as technical writing.
Students also reflect critically on the role of AI in their educational experience and environment. They often comment that AI’s creation of these documents can fall flat without significant editing. They also see that while AI can be creative, it simply replicates the most generalized information about the subject area (i.e., technical writing happening in the most high-stakes contexts: nuclear safety signage). Students often ask to see the original outputs of the AI before my editing and will comment on the lack of sophistication and understanding of the rhetorical situation in the initial outputs. Although, all this work can be done without integrating AI adding this element to the game fosters discussion and establishes boundaries for students’ use of AI going forward in the course. For me, AI also saves significant time by allowing me to focus more closely on creative editing instead of generating a genre example from the ground up. Students and I reflect on GenAI’s shortcomings and strengths, always remembering that it is an imperfect writing tool, just like every tool that has come before it.
As I continue to refine this assignment, I find myself returning to Johnson-Eilola’s (1996) assertion that collaboration is not merely a pedagogical strategy but a foundational value of technical and professional communication. In this light, I remain uncertain about the necessity of the small group structure. While students submit their work individually, the shared investigative process—deciphering clues, debating interpretations, and negotiating genre conventions—mirrors the distributed authorship and collective problem-solving that define professional technical communication.
This tension between individual deliverables and collaborative process invites a broader reflection: how do we design assignments that honor the rhetorical complexity of TPC while also preparing students for its social realities? The murder mystery framework, with its layered documents and interdependent clues, offers one such model. It positions students not just as solitary analysts but as co-constructors of meaning, echoing the genre ecologies and networked authorship that Johnson-Eilola describes.
I want to end where I began and encourage you, dear reader, to take on the case of Dr. Harper (or create your own mystery) and let AI be a tool by which you do so.
Hello Investigator,
Today, we are embarking on an exciting and challenging mystery-solving activity inspired by the Hunt A Killer board games. The setting of our mystery is the Institute for Nuclear Semiotics (INS). This research facility is dedicated to creating signs and documentation to convey information about hazardous nuclear materials to future generations, ensuring safety and comprehension across language and cultural barriers.
The main character in our story, Dr. Evelyn Harper, a leading expert in nuclear semiotics, has been murdered. This incident coincides with a critical project milestone related to a new signage system and a mysterious hooded figure caught on security footage. Your task, as investigators, is to determine what happened to Dr. Harper and uncover any underlying issues within the project.
You will start by forming groups of four and analyzing the initial set of documents, which includes meeting minutes, a project plan, and a white paper. These documents will provide the background and context needed to begin your investigation.
As you progress through the sessions, you will receive additional documents such as user manuals, technological specifications, data sets, emails, security incident reports, access logs, and a security camera still image. Pay close attention to the details, as some documents contain critical clues while others may serve as red herrings designed to mislead you.
Remember, communication and collaboration within your group are key. Share your findings, discuss your theories, and piece together the puzzle. By the end of this activity, you will not only have solved the mystery but also gained valuable experience in exploring, analyzing, and synthesizing technical documents.
Happy Investigating!
You will submit two deliverables for this project: a solution to the mystery that answers our major questions and an informative reflection.
For this portion of the project, all I need from you is a paragraph answer for each of the big questions. You will be graded only partially on how accurate your deduction is, but mostly on how well you support your answers with evidence and reasoning.
Please answer the following questions:
Who killed Dr. Harper? What evidence do you have that leads you to believe that?
Don't forget to establish motive, means, and opportunity.
What went wrong with the project? What evidence do you have that leads you to believe that?
Who is the mysterious hooded figure? What evidence do you have that leads you to believe that?
Your job here is to reflect deeply on this game's impact on your learning. This is where most of your grade for this project will come from. Please answer all of the questions listed below. Stellar reflections do so by uniting answers under a common umbrella point instead of simply answering them in a row as they are listed.
Please answer the following questions:
How did this game reinforce what you already knew about technical documents/writing before entering the course?
How did this game challenge your previous understanding of technical documents/writing?
What documents did you find most enjoyable to analyze? Why?
What documents did you find most challenging to analyze? Why?
What was your process for identifying critical clues and distinguishing them from the red herrings?
How did this mystery game enhance your understanding of the role of technical writing in real-world contexts? You may discuss high-stakes situations like nuclear safety, but you can also think about more everyday applications of technical writing.
Return to one of the documents in the packet and explain how it specifically meets the definition of technical writing we have been working on. Use the chart below as a point of comparison.
Editors’ note: As part of this assignment, the author included a table describing the conventions of technical writing. This chart can viewed with the assignment in the Supplementary Material.
A number of scholar-teachers have explored the value of games and in the writing classroom. Along with those cited in this essay, I suggest the following: Caravella and Shivener (2020); Colby (2022); Colby (2025); Hernandez (2024); Sánchez, Dorpenyo, and Sano-Franchini (2021); and the special issue of Technical Communication Quarterly on Games in Technical Communication edited by Jennifer deWinter and Stephanie Vie, (2016).↩︎