Sophia Koleno
Ohio University
Bilal Al-Zubaidi
University of South Carolina
Suggested Citation:
Koleno, S., & Al-Zubaidi, A. (2026). Prompting possibility: Teaching ethical AI brainstorming for relective topic development. Utah Journal of Communication, 4(1), 43-45. https://doi.org/10.5281/zenodo.20741790
Abstract
As generative artificial intelligence (AI) becomes increasingly common in higher education, students are already using these tools to brainstorm assignment topics, often without guidance or critical evaluation. This Great Idea for Teaching (GIFT) presents a structured classroom activity that teaches students to use AI ethically and reflectively during topic development. Consistent with the purpose of GIFT scholarship, which emphasizes innovative, classroom-tested activities that actively engage students in the learning process (Barton & Coombs, 2023), the activity uses guided prompting, iterative refinement, evaluation of AI-generated responses, and written reflection to help students develop stronger topic ideas. Students learn to treat AI as a tool for exploration rather than a source of answers, promoting topic ownership, critical AI literacy, and visible thinking. Adaptable across communication, political science, and related disciplines, this activity offers a practical framework for integrating AI into the invention process while maintaining student agency and intellectual engagement.
Keywords: generative artificial intelligence, topic development, critical AI literacy
Course Context
This activity is designed for courses that require students to generate and refine topics including, but not limited to: public speaking, rhetorical criticism, argumentation and debate, interpersonal communication, cross-cultural communication, political communication, political theory, and international relations. It is adaptable across in-person, online, and hybrid environments.
Learning Objectives
This activity enables students to:
- Generate and refine potential topics for course assignments
- Use generative AI as a tool for exploration
- Critically evaluate AI-generated ideas
- Develop ownership over topic selection
- Practice invention as an iterative, reflective process
Theoretical Rationale
As generative AI becomes increasingly embedded in students’ everyday academic practices, many are already using these tools for brainstorming in ways that are often private, inconsistent, and without guidance. While some institutions provide structured or “closed” AI environments such as PlayLab, students will also encounter open, public-facing tools such as ChatGPT among others. These open AI systems offer fewer builtin guardrails which increases the importance of critical engagement. Thus, this assignment responds through an intentional and transparent pedagogical choice that communicates to students that it is acceptable to use AI and provides structured support for using it thoughtfully. Rather than ignoring or prohibiting these tools, this assignment treats them as part of the contemporary learning environment (Baidoo-Anu & Ansah, 2023). In doing so, it reflects a broader responsibility within education to introduce new tools and to help students develop the judgment required to use them well (Kasneci, 2023).
A central feature of this assignment is that it makes the thinking process visible. Students are often already using AI, but that use tends to remain private and unexamined. By bringing that process into the classroom and structuring it through guided steps and reflection, the assignment creates space for students to see how ideas are generated, shaped, and revised. It also allows instructors to demonstrate how prompting, revision, and evaluation function as part of the thinking process. In this way, what is typically hidden becomes available for discussion, critique, and development (Ritchhart et al., 2011).
Time Required
This activity can be completed within a single 75–90 minute class session or divided across multiple shorter class periods (e.g., two 50-minute sessions).
Preparation
Before assigning the activity, the instructor should clarify its purpose by emphasizing that AI outputs must be evaluated, and identifying which tools students may use. Students should understand that AI is being used to generate possibilities, test angles, and narrow ideas.
Step 1: Introduce the Assignment to Students
The instructor begins by telling students that they will use AI to help brainstorm a topic for an upcoming assignment. At this stage, the instructor should explain that students are expected to do the following:
- Ask AI for several possible topic ideas
- Revise their prompts to get more specific or more useful results
- Identify one topic they may want to pursue
- Reflect on what the AI did well and where it fell short
Step 2: Model the Brainstorming Process
Next, the instructor should walk students through a short example so students can see how prompting changes the quality of results. For example, the instructor might begin with a broad prompt such as: “Give me some speech topics about mental health.” Then the instructor can show students why that prompt may produce overly broad or generic responses for the overall course assignment. From there, the instructor should revise the prompt in front of students by stating, for instance: “Give me five specific (public speaking, argumentation and debate, etc.) topics about mental health among college students.”
Revise again: “Now, give me five debatable public speaking topics about mental health policy on college campuses.” Finally, revise once more: “Give me three persuasive speech topics arguing for changes to mental health services on college campuses, and explain why each one could matter to a student audience.” T
his demonstration helps students see that brainstorming with AI is iterative whereby better prompts usually lead to more focused results. Students also begin to see that they can direct the tool instead of simply accepting its first response.
Step 3: Students Begin Their Own Brainstorming
Once students have seen a brief model, they begin their own brainstorming. Students first identify an area of interest that may come from their major, personal interests, current events, course themes, or a general issue they care about. They then enter an initial prompt into an AI tool. The first prompt should ask for several possible topic ideas connected to that area of interest.
For instance, a student interested in social media might begin with: “Give me ten possible topics about social media for a public speaking class.” After receiving ideas, the student should review the list and identify one or two topics that seem most promising. They should then continue the conversation with the AI by asking followup prompts that make the topic more specific. For example:
- “Give me different angles on the effects of social media on teenage mental health.
- “Give me policy-based arguments related to social media use in schools.”
- “Help me narrow this topic so it would work for a sixminute persuasive speech.”
At this point, students should be encouraged to keep revising their prompts until they have ideas that feel specific, workable, and genuinely interesting to them.
Step 4: Students Evaluate the AI Responses
After students generate a range of ideas, they should pause and assess what they received. The instructor should direct students to ask questions such as:
- Which ideas feel too broad and why?
- Which ideas feel too vague or repetitive?
- Which ideas seem strong enough to pursue?
- Did the AI suggest anything inaccurate, generic, or off-topic?
- Which responses helped me think in a new way?
This step is important because it slows the process down and reminds students that part of the process of brainstorming is thoughtfully evaluating the options iterated through AI.
Step 5: Students Choose a Topic
After reviewing and refining their AI outputs, students select one primary topic they want to pursue. They also identify two to three possible directions, angles, or subtopics within that topic. This helps them move beyond a single general idea and begin thinking more concretely about focus. For instance, a student who selects “mental health on college campuses” might identify the following possible directions:
- expanding access to on-campus counseling
- improving mental health crisis response policies
- increasing mental health education for first-year students
At the end of this step, students should have one topic and several possible pathways for developing it further.
Step 6: Students Complete a Short Reflection
Students then write a brief reflection of approximately 250 to 350 words. In that reflection, they should explain:
- how AI helped them brainstorm or refine their topic
- one idea or direction they found especially useful
- one limitation, concern, or weakness they noticed in the AI’s responses
- why they ultimately selected their final topic
Step 7: Submission
Students submit the following:
- their final chosen topic
- two to three possible subtopics or directions
- their written reflection
If the instructor wishes, students may also be asked to include the prompts they used and a short record of the AI outputs they found most helpful. This optional addition gives the instructor more visibility into the student’s process and makes it easier to discuss strengths and weaknesses in later class conversation.
Debrief
When implemented, this activity consistently helps students generate more specific, focused, and viable topics than they often produce through unguided brainstorming alone. Students frequently report that the iterative prompting process helps them explore a wider range of possibilities while narrowing their interests into manageable and meaningful topics. Reflection responses also tend to demonstrate early forms of critical AI literacy, as students identify limitations in AI-generated content such as bias, repetition, lack of depth, or overly generic suggestions. Perhaps most importantly, students often develop stronger ownership of their selected topics because they actively evaluate, revise, and sometimes reject AI-generated recommendations. Rather than simply accepting AI outputs, students learn to view the technology as a tool that supports, rather than replaces, their own judgment and decision-making.
Variations
This activity is highly adaptable and can be modified to fit different course goals, assignment types, and instructional contexts. Instructors may choose to require students to submit their AI prompts and selected outputs alongside their reflection, providing greater transparency into the brainstorming process. The activity can also be expanded into peer workshops in which students compare AI-generated ideas, discuss the strengths and weaknesses of different prompts, and provide feedback on one another’s topic development. For courses with larger assignments, the exercise can serve as the foundation for a research proposal, speech outline, or other major project. Instructors may further tailor the activity by incorporating discipline-specific expectations, such as requiring the application of a particular theory, methodological approach, or policy perspective. Finally, students can be placed into pairs or small groups after selecting their topics to discuss their experiences with AI, compare reflections, and collaboratively evaluate the effectiveness of various prompting strategies.
References
Baidoo-Anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52–62. https://doi.org/10.61969/jai.1337500
Barton, M. H., & Coombs, H. V. (2023). Concise guide for preparing GIFT articles. Utah Journal of Communication, 0(2), 6–10. https://doi.org/10.5281/zenodo.7702244
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274
Ritchhart, R., Church, M., & Morrison, K. (2011). Making thinking visible: How to promote engagement, understanding, and independence for all learners. Jossey-Bass.