Although scholars in higher ed do not agree on the role that AI should play in teaching and learning, one perspective is that students and faculty must learn how to collaborate with AI. Jose Antonio Bowen and C. Edward Watson (2024) succinctly state it this way – “AI is more than an assistant: it is a new collaborator” (39) – and other scholars agree (i.e., Dobrin, 2023; Mollick, 2024).
I also agree; however, in much of the current scholarship, researchers discuss student-AI collaboration as a way to help students learn course content and meet learning outcomes. While this is certainly a valuable approach, my claim is that this approach is only one way to harness the powerful potential of student-AI collaboration. As this article will show, student-AI collaboration can also be a way to personalize student learning and create learning outcomes.
In this article, I share an assignment in which undergraduate students at Florida International University collaborate with AI in an interactive interview to personalize one of our course outcomes to their own interests and goals. I provide assignment details and reflect on the assignment so that other faculty can consider how they might use/adapt this assignment for their own purposes.
The Assignment
I designed this assignment for my Summer 2024 upper-level writing course: Rhetorical Theory and Practice. This course is required for students majoring in Writing and Rhetoric as well as those working towards the Certificate in Professional and Public Writing. It is also a common elective for pre-law students. During the first week of the course, after we have reviewed the course syllabus, I ask the students to return to the portion of the syllabus that outlines our six course objectives:
- Explain rhetorical principles, ideas, and terminology
- Analyze rhetorical principles, ideas, and terminology
- Describe the ways in which rhetoric impacts public perceptions and representations
- Describe the ways in which rhetoric is used as a tool for persuasion and resistance
- Create texts in varying genres that incorporate visual and written rhetoric
- Create texts that showcase connections between your personal experiences and rhetorical principles
We discuss that a course objective is a learning goal that each person is expected to achieve by the end of the semester, and these objectives are the same for each student. We also discuss that each student in the classroom has their own unique interests and goals. Some students are pre-law; others are working on professional and public writing certificates. Some hope to get into grant writing; others are working for the FIU student newspaper. Put simply, the students are not a monolith, and although they are all expected to achieve the same learning outcomes at the end of the semester, the journey towards those outcomes should be specific to each individual student. AI can help with this.
I then explain to the students that one of the interesting uses of AI is to interact with it as a thought partner, and with careful prompting, AI can help us engage in in-depth and personalized thinking and learning. I tell the students that we will use AI to help us personalize course objective 2 – “Analyze rhetorical principles, ideas, and terminology” – to our own personal, professional, academic, and/or cultural experiences.
My rationale for asking each student to personalize the same course objective rather than allowing them to choose which objective they will personalize is to maintain some consistency with the student experience in the course. Additionally, the reason I selected this particular objective for our AI collaboration is because it has wide potential application across a variety of interests and experiences. For instance, the rhetorical principles and ideas relevant to a pre-law student is different than it is for someone pursuing journalism. Therefore, by personalizing this objective, students interact with rhetorical principles in ways that are relevant to their own interests and goals rather than in an abstract, impersonal way that lacks meaning beyond our specific classroom.
Next, I provide students with instructions for our “Personalized Learning Goal + AI” assignment. Included in the assignment is a specific prompt the students can edit and then copy/paste to begin their interview with AI.
Importantly, this prompt tells the AI how to act (as an experienced, knowledgeable, friendly academic advisor), what to do (ask two open-ended interview questions at a time), and what not to do (do not suggest a personalized learning outcome until told to do so). The assignment description also includes step-by-step instructions students can follow to guide them through their interview with AI, and it concludes with a series of reflective questions designed to help students reflect on their personalized learning goal and the process of collaborating with AI in this way.
This interactive interview occurs during the first week of class. Then, as the semester progresses, students complete progress reflections where they write about the progress they are making towards their personalized outcome, ultimately culminating in a professional, academic research poster that spotlights the progress they have made towards their personalized learning goal.
You can view the progress reflection prompt and the academic research poster assignment instructions here.
Strengths of this assignment
Strength 1: Personalizes student learning according to future career goals
One strength of this assignment is that it allows students to personalize their learning for their future career goals. Despite being in the same class and perhaps even pursuing the same major, not all the students share the same professional goals. For instance, one of my students hopes to get into activist work. Another student is working towards being an environmental lawyer. A third hopes to pursue creative writing.
Clearly, students do not all share career aspirations, and it would be a disservice to their time in the classroom if the content of our course did not acknowledge this. The activity helped them tailor our course objectives to align with their interests, allowing them to make a more explicit connection between their course work and their visions of the future. After all, what am I preparing them for, if not life beyond our classroom walls? My experiences suggest that one way we can effectively do this is by inviting students to collaborate with AI to personalize a course objective.
Strength 2: Promotes AI literacy
Another strength of this assignment is that it helps students grow their AI literacy by introducing them to the potential to productively collaborate with AI. Specifically, the scaffolded interview gives students practice with effectively prompting and responding to AI to get productive output. This is an important aspect of promoting AI literacy because the act of engaging with AI can help to demystify AI and begin to show students that they can productively interact with AI. Additionally, providing editable prompts, as this assignment does, makes the student-AI collaboration more accessible for students who are new and therefore hesitant to explore AI on their own.
Many of my students shared that they had not previously interacted with AI in this way, and they were surprised by the usefulness of this interaction. Students expressed surprise and curiosity as they saw the AI draft outcomes. The activity introduces students to the potential to productively collaborate with AI as thought partners, a skill they will undoubtedly need in their future careers, and it also illustrates one way in which students can use AI as a tool for their own growth and learning.
Area for Improvement
One area for improvement is that most students did not continue to collaborate with AI following this interview assignment. That is, although I invite students in the progress reflections to use AI to refine their learning goal and/or conduct research, the majority of students did not take advantage of this. One possible reason for this is that, as I previously noted, for the majority of my students, this was the first time they had collaborated with AI in this way. In other words, my students seem to have had little previous experience with AI and therefore relatively low levels of AI literacy, both of which might have caused them to be hesitant to continue collaborating with AI without more explicit guidance. Therefore, the next time I use this assignment, I will incorporate more scaffolded activities that invite students to return to AI throughout the semester as a means of further refining their learning outcome and also collecting research.
Conclusion
My intention in sharing this assignment is to showcase one way that we can use AI to help personalize student learning. I see this assignment as an extension of the important work offered by Drs. Ethan and Lilach Mollick from The Wharton School of the University of Pennsylvania. In “Instructors as Innovators: a Future-Focused Approach to New AI Learning Opportunities, With Prompts” (2024), Mollick and Mollick claim that AI “has the potential to democratize the development of educational technology and put instructors in the role of builders and creators” (43). Similarly, the “Personalized Learning Goal + AI” assignment I have shared here extends this approach by highlighting one way that we can put students “in the role of builders and creators.”
I invite faculty across disciplines to use and/or adapt this assignment for their purposes, and I would be happy to hear about the ways in which this is done.
References
Bowen, Jose Antonio, & Watson, C. Edward. (2024). Teaching with AI: A Practical Guide to a New Era of Human Learning. Baltimore, MD: Johns Hopkins University Press.
Dobrin, Sidney I. (2023). AI and Writing. Broadview Press.
Mollick, Ethan. (2024). Co-Intelligence: Living and Working with AI. Penguin Random House.
Mollick, Ethan, & Mollick, Lilach. (2024, April 22). Instructors as innovators: A future-focused approach to new AI learning opportunities, with prompts. The Wharton School Research Paper. http://dx.doi.org/10.2139/ssrn.4802463