Revamping Law Assignments: Embracing AI for Enhanced Legal Education

In the realm of legal education, adapting to the realities of AI usage among students is essential for effective teaching. I introduced a revised assignment framework called “ApprAIsals,” aimed at integrating AI while ensuring a manageable workload for both students and instructors.

The Core Assignment Structure

Both versions of my assignment—“Written ApprAIsals” and “ApprAIsals”—center around a pre-selected law for analysis. Students are tasked with evaluating its constitutionality while maintaining transparency about their AI usage.

This framework worked well, but soon, the associated workload revealed some serious challenges.

Challenges Encountered: The Grading Glut

Initially, the grading process was intensive:

• 100+ students submitted first drafts.
• Within two days, I returned detailed feedback based on a multi-point rubric.
• Three days later, they submitted AI logs to reflect their drafting process.
• Feedback on AI logs arrived two days later.
• Final drafts were submitted three days thereafter.
• Final grades were delivered a few days later.

All of this unfolded in a tight two-week timeline. Rather than creating an effective learning environment, this structure inadvertently turned into a grading marathon for me. The assignment, while well-intended, became unsustainable.

Revamping the Assignment for Sustainability

I recognized the need for a major shift: I now create the first draft, deliberately flawed, for students to critique. Instead of relying solely on their initial writing, this change enhances their analytical skills. The intentionally subpar draft, assisted by AI-generated mistakes, challenges students to:

• Identify factual, legal, and analytical errors.
• Apply their legal knowledge to enhance the draft.
• Write an error-free polished final version.

This new structure streamlines my grading process, allowing me to assess their final drafts and AI logs simultaneously and realistically. It addresses the inherent challenge of grading substantial student output without creating an overwhelming workload.

Learning Outcomes Remain Constant

While the structure has evolved, my assessment criteria to gauge students' understanding of legal concepts hasn’t changed. Errors in their final drafts indicate a lack of comprehension of the subject matter. Additionally, I continue to emphasize responsible AI usage, crucial for today’s legal practitioners. Students often input the entire flawed draft into AI, which can perpetuate errors or introduce new ones. Recognizing, correcting, and verifying AI-generated content is a skill I strive to instill in them.

In this revised framework, my pedagogical goals remain intact, aligning assessment with my practical teaching aims.

An Unexpected Positive: Students Embrace the Flawed Drafts

Interestingly, students have responded positively to the flawed drafts. Many appreciate the experience of stepping into a supervisory role, finding it more engaging to “repair” something rather than starting from scratch. Their interaction with the errors—often stemming from AI inaccuracies—has not only kept engagement levels high but even enhanced them.

Was AI a Part of This Writing Process?

To mirror the approach of “ApprAIsals,” I incorporated AI in the writing of this article. I aimed to:

• Begin with an imperfect version.
• Use AI as a supportive tool rather than a crutch.
• Revise, fact-check, and refine for clarity and coherence.
• Deliver a final piece that captures my voice.

This process embodies the essential lessons I want my students to internalize.

A Practical Adjustment That Yields Benefits

I didn’t overhaul “Written ApprAIsals” due to any pedagogical flaws; rather, it was essential for logistical sustainability. “ApprAIsals” retains key elements of effective teaching, such as:

• Conveying foundational legal principles
• Encouraging robust legal analysis and writing skills
• Promoting responsible AI utilization in practice

This approach provides a balance between educational integrity and practical teaching realities. It’s not a radical change; it’s a necessary, thoughtful adjustment that has proved successful.

Written by Machiavelli (Max) Chao, Full-Time Senior Continuing Lecturer at the Paul Merage School of Business at the University of California, Irvine and Cengage Faculty Partner.

For more insights, check out Part One of this series on utilizing AI in business law.

The post Revamping Law Assignments: Embracing AI for Enhanced Legal Education appeared first on The Cengage Blog.