Planning for Successful Final Projects
Picture this: It’s December. Students have submitted their final projects, whatever form those take in your course, and you’re reading through them. You feel delighted (or relieved) because so many projects meet or exceed your expectations, and because you see evidence that students have done so much of the learning you hoped they would when you began the semester in August.
How can you get from here to there? This week, we’ll share some practical tips for helping students do their best work on the final project in your course.
Make it meaningful: What was most important for students to learn and learn how to do in the course? Rather than a catch-all, a final project should be aligned with the highest priorities, and with what students have had opportunities to learn and to practice, so that it’s meaningful both for students to do and for you to evaluate. When students see value in a project, they are more motivated to put in their best effort.
Make it transparent: Ideally, a project description is separate from the syllabus and includes more detail than a brief description on a syllabus would. A transparent project description clearly defines the purpose of the project, the task(s), the process for completing the task(s), and the criteria for success. Providing this information in writing (i.e., on Canvas), rather than explaining the details aloud in class, allows students to refer to it outside of class and throughout the process of completing their work.
Address AI: Do you want students to use AI tools when completing their final projects? If so, which one(s) should they use and how may they use it? Have they learned how to use AI in the way(s) you want them to? Are there ways they are not allowed to use it? Some final projects may be totally focused on working with AI, while others may completely forbid using AI—whatever your approach, be sure to communicate your expectations to students in writing (e.g., on the syllabus, on the project description) and in class. Be sure to explain the rationale behind your AI expectations, especially how using or not using it is connected with the purpose of the project. In other words, explain what you intend for students to learn from doing the project and how using AI can support or obstruct that.
Check for understanding: A great project description doesn’t help much if students don’t read it, or read but don’t fully understand it. (You might be surprised how often instructions or expectations that seem clear to us are not clear to students.) It helps to launch the project in a way that includes a check for understanding. Some colleagues describe the project briefly in class, give students time to read the full project description, and then have a Q&A. Others create a homework assignment in which students read the project description and then respond to a few prompts on a discussion board, such as: In your own words, what are you supposed to do in this project? What will you turn in at the end? What do you think you might learn, or show that you have learned, by doing this project? What will successful work look like or include? What will you need to do (what steps will you take, what resources might you use) to complete your project successfully?
Break it down: Students produce better work if—instead of doing all parts of the final project on their own, at once, outside of class—we break the project into a sequence of smaller assignments that help them build a larger work over time, and with opportunities for feedback and revision. For example, we might ask students to write a project proposal and an annotated bibliography, on which they get some feedback, before writing a research paper. Any kind of project can be broken into steps, and doing so can also help us remember just how many component tasks and skills are involved in the projects we assign.
Spend class time on it: Designing class sessions to include some time for students to work (together or individually) on parts of their projects, or to do activities in which they learn something that they can apply to their final projects, ensures that students do the work over time instead of in a rush the night before the deadline. Just a few examples of in-class work they can do include: project planning (e.g., brainstorming, outlining); topic development; analysis and discussion of examples; research-related activities; guided self-assessment; structured peer review; etc.
Build skills: Final projects usually ask students to draw on a wide variety of skills, some they’ve nearly mastered and others they’re just beginning to develop. Often it’s the intellectual work—the thinking processes—involved in our assignments that needs the most support. For example, if you ask students to analyze a text, what exactly do you mean by that? And how can they get some practice before they do it for a grade? If you ask students to synthesize new ideas, how do you guide them as they attempt it? Projects should be both level-appropriate and challenging; they aren’t level-appropriate if we unintentionally ask students to do new and complex intellectual work without adequate support.
Provide feedback: Feedback is necessary for learning. Final projects turn out better if we incorporate opportunities for feedback and revision. That said, our ability and capacity to give helpful, targeted feedback in time for students to use it depends on our class sizes and workloads, so we need to use feedback strategies that work for our teaching contexts.
Give encouragement: To us, the coursework we assign usually does not seem intimidating, so it’s easy to forget that students might see it that way. Novice-expert differences can be profound, so it’s important that we remember where our students are in their development. Our encouragement does make a difference to students, from the first year to the doctoral dissertation. When we communicate that we have high expectations for our students, we must also communicate that we have confidence that, with effort, they can succeed.
If you’d like some support with the final project for your course, please contact us at pro-teaching@fsu.edu. We love to meet one-on-one or in groups with our colleagues to work on assignment design, sequencing, scaffolding, and so on. We look forward to working with you!
2026 Provost’s Showcase of Scholarly Teaching
Friday, April 10th | 1:00 p.m. – 5:00 p.m. | Strozier Library Basement | More details on our website
We’re delighted to announce that CAT and FSU Libraries will host the third annual Provost’s Showcase of Scholarly Teaching on April 10, 2026. This event is an opportunity for you to share your teaching expertise and innovations with the larger campus community. Even if you’ve never thought about presenting at a pedagogical conference before, you likely have strategies and insights that could be of benefit to colleagues. We invite you to apply to host a roundtable discussion or present a poster.
If you would like to submit a proposal, please fill out our Application Form. The application due date is Feb. 1, 2026. We look forward to reading about your teaching!