Restructuring assignment creation around how instructors actually think.

Writing Solutions is an instructor-facing assessment tool for creating and grading typed assignments, in beta release as part of Pearson's "Generate" portfolio. Following a platform-wide UX audit, the assignment-creation flow emerged as a key opportunity to address recurring issues around cognitive load, decision clarity, and misalignment with instructor mental models.

This case study focuses on the assignment-creation redesign. The audit gave me the strategic foundation, and I extended those findings to tackle the issues specific to Writing Solutions.

The existing assignment-creation page stacked every decision into a single scroll. Because some choices affected others downstream, users had to scroll back constantly to revise.

This forced instructors to context-switch constantly while scrolling up and down:

The structure conflicted with both:

On top of that, a few high-impact decisions, like the choice between automatic and instructor-graded paths, carried consequences the page never spelled out. That left instructors confused, redoing work, and ending up with assignments that didn't behave the way they intended.

The platform-wide audit had already surfaced patterns that applied directly to this flow:

Assignment creation was a clean place to put those findings into practice. Read the audit case study →

Before designing the ideal flow, I had to account for a near-term system constraint: in WSOL, scoring method determines whether prompts are system-defined or instructor-authored.

Practically, that meant scoring intent had to be surfaced first, with content creation following within those constraints. The coupling may loosen long-term, but the near-term redesign had to work within it, and honor it visibly rather than designing around it.

The redesign worked at three levels.

• Structural changes to the page itself, the chrome that wraps every step.
• A re-sequencing of the actual decisions into four steps.
• Visual treatment that followed Nebula, the up-and-coming design system. Since the department planned to update Nebula by the end of 2026, I designed against where it was heading, so the work would still be aligned after the update rather than need reworking.

Tying assignments to learning outcomes is good pedagogical practice, and Pearson's own guidance supports it. But in practice:

Removing the field entirely would weaken pedagogical alignment and limit downstream AI / analytics value; requiring it could frustrate instructors, slow authoring, and feel rigid. So I kept it optional within Step 2, the deliberate middle path.

Should scoring method really come before the assignment objective? Right now a technical constraint forces that order. The open question is whether AI's time savings justify it, or whether instructors should define what they're assigning first.

This question matters because time savings is core to the value proposition for Writing Solutions and the other "Generate" products. It's often what decides whether an instructor assigns an authentic assessment at all, rather than a traditional one. So if surfacing the AI path early helps instructors capture that value sooner, the current order may be worth keeping.

But early research, three rounds of interviews with distinct panels of higher-ed instructors, suggests instructors don't yet trust AI enough to commit to it that early. The next step I'd explore is twofold. First: are there ways to build that trust, through transparency, previews, or more control? Second, and just as important: is doing so worth it? If earning that trust unlocks the time savings instructors care about, the investment likely pays for itself. If it doesn't, the simpler answer may be to honor how instructors already think and let them define the assignment first.