AI Instructor Assistant
User Experience, Business Strategy, Generative AI
Overview
The Cengage Instructor Center’s AI Instructor Assistant streamlines course planning by helping instructors quickly determine if a title is a good fit for their course. Acting as a knowledgeable product specialist, it reduces the need for back-and-forth communication with the sales team by serving as a first point of contact. Additionally, it generates personalized materials to support instructors in offering effective study tools for their students.
🎯 Tasks & Goals
Enable instructors to experiment with leveraging AI to help with tasks like syllabus creation, summarizing content, curriculum mapping, and evaluating narrative content.
Introduce our novice GenAI Instructors to the potential functionality and benefits in a low-stakes decision moment.
🎨 Design Deliverables
High-fidelity mockups and prototypes
Usability tests and findings
🤝 Stakeholders & Collaboration
Product Leadership
Product Managers
Technical Product Managers
Development Teams
User Experience Researchers
📊 Key Takeaways & Results
Title alignment was top of mind
100% of users asked how the title aligned with their learning objectives.
AI interest is growing
Most instructors agreed generative AI will play an increasingly important role in higher education.
Curiosity, not clarity
Early usability testing showed instructors were interested in trying the assistant, but many misunderstood its purpose.
Discoverability issues were significant
80% of testers didn’t notice the launcher until prompted.
AI was mistaken for support chat
Users assumed it was a standard help bot, not a generative tool.
🖼️ High Fidelity
Launch Call-out
The product details page provides users currently browsing titles or adopting a new title a chance to evaluate with the AI assistant.
iFrame AI Assistant Chat
AI-powered assistant embedded in the Cengage Instructor Center, designed to help instructors evaluate if a textbook is a good fit for their course.
📐 Research & Testing
The UX Researcher and I shared concerns about the assistant’s discoverability and users’ potential misinterpretation of its purpose, specifically, that it might be mistaken for a generic support chatbot rather than an AI-driven tool. By raising these flags early, we were able to advocate for and conduct a small-sample usability test to validate our assumptions and uncover opportunities for clarification.
Primary Goal
Identify any major usability issues to address pre-launch. Major usability issues can be defined as anything that could impact the user’s ability to engage with the AI bot, like issues with discoverability or accessibility.
Secondary Goal
Gather some attitudinal and directional data on how instructors feel about our use case for AI as an assistant when evaluating a specific title.
Methodology
30 minutes
Moderated Usability Sessions
5 Higher Education Instructors
Figma Prototype
📌 Key Findings
Users did not notice the Launcher
80% of testers did not see the AI launcher and needed to be prompted to continue reviewing the page to spot it.
Users don’t think the assistant is AI
They think it’s a regular chatbot which they don’t value. Phrases in the copy create a mismatch of expectations.
“Real-time support” gets misinterpreted as human support.
The learning curve of AI intimidates instructors.
They want to interact with the Chatbot but worry, they won’t know how to engage it to yield useful responses.
🗣️ User Quotes
“It’s going to give me things that aren’t helpful.”
“Waste of time”
“I don’t want to have to like teach it what I’m looking for.”
🗂️ Summary Overview
The AI Instructor Assistant was designed to streamline course planning by helping instructors quickly evaluate whether a textbook aligns with their teaching goals. Positioned as a knowledgeable, AI-powered guide, the tool aimed to reduce adoption time while also introducing instructors to generative AI in a low-stakes, exploratory context.
As the UX Designer on this project, I collaborated closely with researchers, PMs, and developers to bring this new experience to life. Early in the process, we identified critical risks around discoverability and user expectations—many instructors either didn’t notice the tool or mistook it for a basic support chatbot. By advocating for and conducting usability testing, we validated these concerns and used the findings to shape clearer UI patterns and copy direction. The result was an interface designed to educate, guide, and empower instructors while demystifying AI’s role in their workflow.