Options for Effective Assignment Design 

Authentic Assessments

The more you can design authentic assessments for your course, meaning assessments that ask students to apply the knowledge they gain in your course in real-world situations, the more motivated and engaged your students will be to engage with your assessment, and the less likely they will be to off-load their work to AI.

Process-Based

A best practice for assessments is moving away from high-stakes, single instances of a particular assessment (i.e., one long research paper due at the end of the course with no touch-points from the time it is assigned to the time it is collected) to taking a process-based approach where you have students submit smaller pieces of a larger assessment that represent their work-in-progress.

Student Choice

Research in the field of psychology has long demonstrated the positive effects when individuals are given choices. These findings also have been explored in educational contexts, showing a strong correlation between choice, intrinsic motivation, and better academic achievement. In short, when students are given options, they are more likely to feel connected to and in control of their work, which can lead to a sense of greater ownership of their learning and subsequent investment of time and effort. 

In the time of AI, what this might mean is that providing students with opportunities for choice could lead to less of a possibility that they might choose to use GenAI irresponsibly. 

A Framework for Re-Imagining Assessments

Derek Bruff, in “Assignment Makeovers in the AI Age: Essay Edition” offers a framework of six questions to help instructors think through how to revise their assessments in “this new age of AI.” We’ve listed Bruff’s questions below with some additions that we think will help guide faculty to design more authentic assessments. 

1. Alignment

Why does this assignment/assessment make sense for this course?

• Does it connect to crucial content or skills for your discipline?
• Is it connected to fostering student motivation and engagement?

2. Learning Objectives

What are specific learning objectives for this assignment/assessment and how do they relate to AI?

3. AI Use

How might students use AI tools while working on this assignment/assessment?

This is where you will want to put yourself in the role of a student and experiment with AI tools yourself. To what extent can you complete your assignment/assessment using AI? 

4. Risks

How might AI undercut the goals of this assignment/assessment? How might you mitigate this?

• Based on your experimentation in Step 3, you’ll have a better idea of how students might offload their work to AI. How might you change your assignment/assessment to address this? Some ideas might include:
  • Having students create something for a public audience
  • Providing a greater level of student choice in terms of their topic and the form of their ultimate final product 
• Talk with students about sourcing. Where do we find our sources? How do we assess their credibility? As of Summer 2023, GenAI does not do a great job with sourcing, and this is something students should keep in mind, whether or not AI is a permitted component of an assignment or assessment. 

5. Opportunities

How might AI enhance the assignment? Where would students need help figuring that out? 

6. Process

Focus on the process. How could you make the assignment more meaningful for students or support them in the work? 

• How might you break your assignment down into smaller components?
• How might you incorporate more in-class sharing of in-progress work?
• How might you incorporate more opportunities for peer feedback?