✨Guide: Designing Assignments and Assessments in the Age of AI

The past nine months of our research is gathered into a guide for professors for the spring 2024 semester.

[image created with Dall-E 3 via ChatGPT Plus]

Welcome to AutomatED: the newsletter on how to teach better with tech.

Each week, I share what I have learned — and am learning — about AI and tech in the university classroom. What works, what doesn't, and why.

In this fortnight’s Premium edition, I present a guide for how to plan and develop assignments and assessments in the age of artificial intelligence.

Over the past nine months, we have been sent over a dozen take-home assignments for our AI-immunity challenge. By trying to solve these assignments in one hour or less, our goal was to establish that AI tools perform better at a range of college-level work than many professors thought possible. We had mixed results with the especially tough cases we covered in our newsletter pieces (see here, here, and here), but all of them revealed impressive and surprising capabilities. (We are still taking submissions, if you have one for us.)

We also looked into AI detectors, thought about how to design assignments that encourage constructive AI use, and came up with ways to design assignments to prevent AI misuse. The latter line of research culminated in our comprehensive guide — from early August — to preventing and discouraging AI misuse in the university setting. We asked a librarian and a professor for their thoughts on the AI era; we worked with educational researchers to learn how to do oral assessments and encourage class discussions; and we have been consulting with a range of professors, departments, and institutions about AI integration. Since then, we have been focused more on how our work as professors can be reimagined in light of the power of AI, whether we are using LLMs to plan lessons, using ChatGPT help grade/evaluate, or using custom GPTs for in-class activities.

In this piece, I build on these experiences to present a comprehensive guide to planning and developing university-level assignments and assessments in light of the risks and opportunities AI presents.

This is my 40000-foot (but 6000-word) take on the option space and how to navigate through it as a professor, at least as things stand as we enter the spring 2024 semester.

🖼️ The Big Picture

I have created a flowchart or decision tree that represents the following sections, with [A] representing a potential assignment or assessment. This is your map of this guide.

A map or decision tree to conceptualize this guide.

You can skip ahead to a section of this guide via the links in this table of contents.

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