Critique room
12 learners active · 4 peer reviews open
Edtech · Cohort learning platform
Learning that feels alive, even when teams are apart.
Loop Learning is a remote learning platform designed for cohort-based programs where students need structure, feedback, peer connection, and timely instructor support without turning the experience into another passive video library.
LIVE COHORTHuman-Centered Research Lab
On pace for certificate completion
Three learners need clarity on synthesis framing.
Suggested intervention: run a 12-minute examples clinic before critique.
A connected learning system for focus, belonging, and measurable progress.
Remote programs often fail because the learning experience fragments across video calls, slide decks, chat threads, LMS modules, and private notes. Loop Learning brings those moments into one coherent workflow: live learning, practice, reflection, feedback, and instructor follow-up.
Lead Product Designer
Owned product strategy, learning journey mapping, interaction design, UX writing, dashboard architecture, and high-fidelity prototype direction.
Cross-functional pod
Product manager, learning strategist, two engineers, data analyst, and instructor advisors.
Reduce disengagement
Make learner risk visible earlier while giving students a calmer, more motivating way to keep moving.
02 · The challenge
Remote learning had content, but not enough human signal.
Students were completing tasks, yet instructors could not tell who was confident, who was stuck, and who was quietly drifting away. The product problem was not more content. It was designing a system that made support visible, timely, and actionable.
Live sessions, homework, peer critique, and instructor feedback lived in separate places, making progress hard to understand.
Students often waited too long to ask for help because the platform treated silence as progress.
Program teams were forced to scan comments, attendance, and assignment status manually before taking action.
Research synthesis
Three needs shaped the product direction.
The strongest insight was simple: learners do not just need access to information. They need a visible loop of practice, feedback, confidence, and next steps.
Presence before content
Students were more likely to return when the platform showed who else was learning, asking, reviewing, and progressing.
Progress without anxiety
Progress tracking needed to feel orienting, not punitive. Learners wanted a clear path without feeling watched.
Support at the right moment
Instructors needed signals that separated normal struggle from disengagement risk.
Primary personas
Designing for the full learning loop.
The experience had to serve students, instructors, and program operators without forcing one group into another group's workflow.
AS
StudentAisha Sule
Career switcher balancing coursework with a full-time job.
- Needs clarity on what to do next.
- Wants feedback before final submission.
- Feels isolated when sessions are async-heavy.
ER
InstructorElena Rivera
Facilitates weekly cohort sessions and reviews learner work.
- Needs to identify blockers quickly.
- Wants richer context before intervening.
- Needs feedback patterns, not scattered comments.
JP
Program leadJamal Pierce
Owns completion, learner satisfaction, and instructor operations.
- Needs cohort-level engagement visibility.
- Wants early indicators before drop-off.
- Needs repeatable program health reporting.
Critical workflow
From joining a cohort to receiving useful feedback.
Loop was designed around one repeatable learning rhythm: orient, participate, practice, get feedback, reflect, and continue.
Orient
Student sees today's objective, prep status, and cohort activity.
Participate
Live studio keeps session materials, chat, prompts, and questions together.
Practice
Assignments break complex work into guided checkpoints.
Feedback
Peer and instructor critique becomes structured and actionable.
Reflect
AI coach summarizes gaps, next steps, and confidence patterns.
Low-fidelity wireframes
Testing the rhythm before polishing the interface.
Early wireframes focused on whether learners understood where they were, what mattered today, and how to move forward without asking an instructor for basic orientation.
Final product experience
A premium learning workspace that keeps people in motion.
The final UI uses warm surfaces, luminous learning states, and dense-but-readable cards to make the platform feel intelligent without becoming cold or over-automated.
Welcome back, Aisha
Human-Centered Research Lab
Research synthesis critique
Bring one insight, one quote, and one open question.
12learners ready4questions queued
Two checkpoints remaining this week.
Your synthesis is strong. Add evidence from one more interview before submission.
Feature 01
Live cohort studio
A session space that combines prompts, materials, questions, breakout tasks, and peer activity in one room so students do not lose context during live learning.
- Objective-first session structure
- Real-time questions and confidence pulses
- Facilitator cues for quieter learners
Critique Sprint
Session pulse84%
High clarity · moderate discussion energy
Feature 02
AI study coach
The coach translates learner behavior into helpful next steps, not generic chatbot answers. It references current work, missed concepts, peer feedback, and upcoming checkpoints.
- Context-aware reflection prompts
- Confidence tracking by concept
- Suggested recovery plans after missed work
CoachYour project brief is clear. The weak spot is evidence. Add one direct quote.AishaWhat should I review before critique?CoachFocus on synthesis patterns and decision rationale. I made a 15-minute plan.
Instructor intelligence
Signal without surveillance.
The instructor console highlights patterns that need attention, then explains why. The goal is faster, more empathetic support, not performance policing.
Cohort health
Week 4 · Research synthesis
Aisha Sule · strong work, needs evidence check
Noah Kim · missed two peer reviews
Priya Shah · high effort, low confidence
Design system direction
Warm intelligence, not corporate LMS.
The visual system uses soft depth, focused cards, friendly data visualization, and clear completion language to make the platform feel supportive while still scaling to enterprise learning operations.
Warm cream foundations with bright learning states for live, progress, risk, and coach moments.
Learning checkpointEvidence added
Reusable cards for modules, critique states, coach prompts, and instructor signals.
Clear, calm, next-step oriented.
Language avoids blame. Empty states guide recovery instead of calling out failure.
Impact targets
Designed to improve learning momentum and human support.
Loop Learning frames success as a healthier learning loop: more active participation, earlier support, better feedback quality, and clearer progress across the cohort.
Next project