I designed Sensei AI assisttant that helps teachers by generating lessons and personalized feedback. It saves grading time, streamlines administration and supports professional development, enabling teachers to focus on effective instruction and student engagement.
Context
How Might We
Design an intuitive AI Assistant that streamlines administrative work and helps teachers efficiently and create personalized learning materials to enhance student engagement
3 major gaps
My Approach
Zero Based Design by Mckinsey
Reimagining the teaching experience from the ground up, focusing solely on what teachers need to engage students effectively. This user-first mindset ensures the assistant is intuitive, impactful, and truly transformative.
0-1 Product Launch Strategy
Collaborated with PMs, engineers and internal stakeholders to create seamless AI exerience
Benchmarking with two platforms
Compared two leading products in market with their AI-assisted workflows and UI layouts to ensure intuitive navigation
01
Enhanced user flows
Focused on cross-device usability to ensure accessibility in low-resource settings
02
Hueristic evaluation
Heuristic evaluation of live version revealed critical usability gaps: poor error prevention, inconsistent IA, and cognitive overload—requiring immediate UX optimization
03
Hi- fidelity protoypes with use cases
Creating personalized worksheets and lesson plans using AI. Responsive flows crafted for critical moments (e.g., feedback generation, content creation)
04
Deliverables
Ensuring Product-Market Fit
Facilitated collaborative design walkthroughs from wireframes to high-fidelity prototypes, ensuring strong validation, stakeholder buy-in, and alignment with product goals.
Next Steps on Future Directions
Refine the AI interaction model to enhance natural language understanding and increase the accuracy of personalized content generation. Begin user pilot testing to gather real-world feedback on AI-driven workflow improvements.
Lesson learned
Designing for Clarity and User Trust
Effective AI assistant design requires incorporating mechanisms that detect and resolve ambiguous teacher query through clear prompts, improving accuracy and trust
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