Context

The 2024 acquisition of LearnPlatform by Instructure created an operational crisis: a fractured EdTech ecosystem. The existing LTI (Learning Tools Interoperability) product libraries were dispersed across three disparate locations: the Emerging AI Marketplace, the Edu App Center, and LearnPlatform’s Learn Community Library. This fragmentation created a significant operational disconnect and eroded the platform’s credibility, as there was no single, authoritative source of truth for Instructure’s vetted LTI tools.

The High-Cost Challenge

The primary challenge was the scale of manual process failure. Managing product data across three existing, manually-maintained frameworks was unmanageable, directly resulting in:

1. Stale Data: Partners could not efficiently update their product information, leading to outdated listings.
2. Poor Discovery: School Administrators and Educators were unable to easily discover, vet, and procure the right tools, slowing down adoption and reducing partner opportunities.
3. Ambiguous Vetting: The lack of a unified system complicated the internal compliance and vetting process for new resources.

The business mandate was clear: consolidate three systems into one unified, scalable marketplace.

Continuous Discovery, Unifying User Needs

Continuous discovery research was instrumental in revealing the critical pain point: both Institution Administrators and EdTech Providers lacked a streamlined way to interact and exchange verifiable information. Administrators struggled to access clear, factual vetting documentation about tools, while providers lacked an intuitive channel to manage product documentation.

User-Centered Methodology

We adopted a focused process to synthesize these contrasting needs:

Interviews → Personas → User Stories → User Flows

• Administrators & Educators Focus: We conducted interviews focused on their current vetting and procurement processes, specifically investigating the criteria needed to trust a new LTI resource.
• EdTech Partners Focus: We investigated how they prefer to manage interactions and documentation, uncovering a high demand for a self-service portal.

The Critical Insight

Trust, not quantity, was the primary blocker. The system needed a transparent mechanism to verify and display vetting compliance status to the Administrators, making the process faster and more trustworthy.

Leveraging AI for Synthesis

To handle the volume of qualitative data, we leveraged AI tools to consolidate interview transcripts and generate refined user personas and user-needs matrices. This allowed the team to quickly develop empathy-driven design hypotheses and significantly minimize errors during the validation phase.

Ideation: Translating Needs into Vetting Workflows

With the critical insight (the need for vetting transparency) confirmed, our ideation focused on creating two specific, streamlined workflows: The Partner Self-Service Portal and The Admin Vetting View.

I led the creation of Actionable User Flows, mapping out the end-to-end process from a Partner uploading documentation to an Admin viewing the verified status. This process was a collaborative effort with Product Management to align page functionality with the intended user outcome.

Key Feature Design Decisions:

• The Vetting Status Toggle: We designed a clear status indicator for Admins, allowing them to instantly see the compliance level of any LTI tool without leaving the marketplace. (This directly addresses the ‘trust’ insight).
• Documentation Upload Modal: We created a dedicated, secure partner workflow for uploading vetting documentation, complete with privacy controls and password fields. (This directly addresses the Partner self-service need).

Development & Technical Feasibility:

To stay on a tight 6-month delivery schedule, we focused on rapidly created L3 Mockups (high-fidelity screens without final pixel perfection). These screens were crucial for early collaboration with our engineering team, allowing us to test and validate complex technical requirements (like API calls for vetting status) and ensure our design intentions were technically feasible before committing to development.