Overview:
BORD is an institutional Learning Management System designed to support teaching, learning, assessment, communication, scheduling, and academic oversight across physical, hybrid, and fully online learning environments.
As the Lead Product Designer responsible for BORD, I led the product design across its core LMS experience and AI-powered capabilities.
The product was designed around four distinct roles:
Student
Educator
Tenant Admin
System Admin
Each role has different responsibilities, permissions, and workflows, requiring a product experience that could remain consistent while adapting to each user's needs.
Beyond the core LMS, BORD incorporates an AI ecosystem designed to make learning more personalized, support educators with content and teaching workflows, surface actionable insights, and provide intelligent assistance throughout the platform.
The challenge was therefore not simply designing an LMS.
It was designing a scalable learning ecosystem where traditional LMS workflows and AI-powered experiences could work together naturally.
Problem:
Traditional LMSs can become complex as functionality grows
BORD needs to support institutions operating across different teaching environments.
In a physical-first environment, educators might primarily use the platform for assignments, quizzes, resources, announcements, and student participation.
In hybrid environments, the platform also needs to coordinate physical and virtual sessions.
For fully online institutions, BORD becomes the primary environment for teaching, learning, assessment, communication, and virtual classes.
At the same time, the platform needed to introduce AI capabilities without making the experience feel fragmented or unnecessarily complicated.
This created several design challenges:
Four distinct user roles with different responsibilities.
Complex permission and escalation structures.
Multiple teaching models.
Large amounts of academic data.
Assessment and grading workflows.
Course and content management.
Reporting and analytics.
AI-powered recommendations and assistance.
Different AI experiences for students and educators.
Future-facing capabilities such as career guidance, certification, and personalized learning.
The challenge was to make all of this feel like one coherent product, not a collection of disconnected features.
Solution:
A role-based LMS with AI embedded into the learning experience.
I designed BORD around a consistent product architecture that connects core LMS functionality with intelligent AI capabilities.
Role-based experiences:
Each role receives a focused experience based on its responsibilities. Students focus on learning, assessments, communication, and progress. Educators focus on teaching, course management, assessment, grading, and performance. Tenant Admins focus on institutional operations and intervention. System Admins focus on platform-wide governance and oversight.
AI-powered personalization: The AI layer can use student progress, learning preferences, quiz results, participation, and assignments to provide contextual feedback and personalized learning support.
AI Tutor: Students can interact with an AI Tutor through chat and voice to ask questions about course content, assignments, and concepts. The concept also supports contextual conversation, voice-based assistance, and multilingual interaction.
AI-powered content tools: AI capabilities extend into educator workflows, including automated quiz and assignment generation, content summarization, content customization, and AI-assisted content development.
Educator intelligence: Educators can receive performance analytics, real-time feedback, AI-generated content support, syllabus assistance, quiz generation, assignment-rating support, and course optimization recommendations.
AI ecosystem: The wider AI architecture includes specialized agents such as the Content Agent, Learner Agent, Research Coach Agent, Resume Agent, Analytics Agent, AI Tutor Agent, Educator Coach Agent, and Multilingual AI Support.
Designing Human + AI Interactions
AI introduced an additional layer of UX complexity.
Instead of treating AI as a standalone feature, I explored how to integrate intelligence into existing workflows.
This included:
AI Tutor interactions
AI-generated learning support
Personalized feedback
AI content creation
Educator assistance
Analytics and recommendations
AI-powered career and development tools
The goal was to make AI feel like a natural extension of the LMS, rather than an unrelated chatbot added to the interface.
Designing with Clarity and Purpose
Every project follows a clear process that balances strategy, creativity, and user insight.
User Research:
BORD's foundation requirements defined four primary user roles:
Student
Students use BORD to consume assigned courses, complete assessments, attend virtual classes, participate in forums, view announcements, manage their schedules, communicate, and monitor progress.
The AI experience adds another layer by providing personalized feedback, learning assistance, and an AI Tutor.
Primary need:
Help me understand what I need to learn, complete my work, and improve.
Educator
Educators use BORD to manage assigned courses, create assessments and resources, grade students, communicate, manage forums, host virtual classes, and review performance.
AI extends their workflow through content creation, assessment generation, analytics, course optimization, and teaching support.
Primary need:
Help me teach more effectively without adding more administrative work.
Tenant Admin
Tenant Admins manage their institution's users and workflows, monitor reporting, and intervene when educators cannot perform important operational tasks.
Primary need:
Give me visibility and control without forcing me to manage everything myself.
System Admin
System Admins provide platform-wide governance, reporting, audit access, and final operational intervention.
Primary need:
Give me enough visibility and control to understand and manage the entire ecosystem.
User Journey:
I mapped the experience around the different responsibilities users encounter throughout the learning lifecycle.
For students, the journey moves from accessing their dashboard and courses through learning activities, assessments, communication, scheduling, and progress tracking.
For educators, the journey centers around managing assigned courses, creating and grading assessments, communicating with students, managing learning resources, and monitoring performance.
For administrators, the experience shifts toward oversight, reporting, user management, and operational intervention.
This role-based approach helped ensure BORD remained focused on users' immediate responsibilities rather than exposing every capability to everyone.
Usability Study:
View Usability Study
BORD's complexity meant usability was closely tied to information architecture and role clarity.
I focused on questions such as:
Can users immediately understand where they are within the platform?
Can they find the tools relevant to their role?
Are important actions clearly surfaced?
Can users navigate deeper academic workflows without losing context?
Are permissions and responsibilities clear?
Can the interface accommodate different teaching environments without becoming overwhelming?
These considerations informed the dashboard structure, navigation, page hierarchy, breadcrumbs, actions, and reusable component patterns.
Iterations:
01 — Role-based navigation: The navigation structure was refined around the responsibilities of each user role, reducing unnecessary options and keeping the primary workspace focused.
02 — Persistent sidebar: A persistent left sidebar became the primary navigation pattern across the authenticated experience, with an expanded and collapsed state to accommodate different workspace preferences.
03 — Contextual navigation: Breadcrumbs were introduced for deeper workflows, allowing users to understand their location within structures such as courses, assessments, and submissions without repeatedly navigating backward.
04 — Dashboard hierarchy: Dashboard layouts were structured around the most relevant information for each role. For students, this meant surfacing learning obligations and upcoming activities. For educators, the focus shifted toward course operations, assessments, students, and reporting.
05 — Reusable components Instead of designing each screen independently, I established reusable UI patterns for buttons, inputs, tables, cards, lists, navigation, states, and academic workflows. This created a stronger foundation for scaling the product across multiple modules.
06 — System states: The design system accounted for essential product states, including loading, empty, error, success/confirmation, and permission-denied states. This ensured that the experience was considered beyond the ideal or "happy path."
Results:
As Lead Product Designer, I led BORD's design direction across its core LMS experience and AI-powered ecosystem.
The work established:
A role-based product architecture
Four distinct user experiences
Core student workflows
Educator teaching workflows
Administrative workflows
AI-powered learning experiences
AI-assisted educator workflows
AI-powered analytics concepts
An AI agent ecosystem
A scalable design system
Reusable interaction patterns
Permission-aware experiences
Consistent navigation and information architecture
The AI layer expanded BORD beyond a conventional LMS by introducing personalized learning, AI tutoring, educator assistance, content intelligence, analytics, career support, and faculty development capabilities.
