SkillPath
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I worked with the Tech4Good HCI team to create Skillpath, an e‑learning platform that tackles the isolation and Week‑3 dropout pattern seen in most MOOCs. Skillpath combines AI‑driven group formation, adaptive checkpoints, and structured peer feedback to help learners “learn by doing” ,reflect together, and actually finish what they start.
Responsibilities
Time
Problem
Conventional e‑learning platforms were built for consumption, not connection. Learners move through static videos alone, rarely see how their progress stacks up, and struggle to find timely help when questions arise. The absence of purposeful peer groups, adaptive assessments, and on‑demand guidance leaves many feeling isolated and unsure whether they are actually mastering the material.
Solution
Skillpath replaces that one‑way, watch‑and‑hope model with an AI‑orchestrated learning ecosystem. Its Group Formation engine assembles cohorts with shared interests and comparable skill levels, creating instant study circles that motivate each other. Behind the scenes, Knowledge Assessment tools continuously analyse performance, surfacing personalised insights and actionable recommendations that let learners see—and believe in—their own progress. Meanwhile, always‑on Virtual Agents act as tireless teaching assistants: answering questions, recommending resources, and nudging learners toward their goals. Together, these three layers transform an isolating course catalogue into a dynamic, supportive path that keeps more learners engaged through completion and unlocks higher conversion for the business.
How the research shaped the solution
The convergence of behavioral data, user testimony led us to three design mandates and ultimately to Skillpath’s AI‑driven pillars:
Accountability spikes when learners share goals with similar peers
Micro‑assessments boost completion more than end‑of‑module quizzes
Students in 100 + person MOOCs stay engaged when guided by chat mentors
Competitive Analysis
Market gap: The leading MOOCs don’t support real‑time collaboration
Key insight — None of the major players offers structured, in‑session collaboration.
Design implication — Skillpath can differentiate by making peer interaction, shared projects, and synchronous feedback core to the experience.
Semi‑Structured Interviews
Learners crave accountability and quick help.
“I got stuck on one concept and never went back.”
“If I had a study buddy, I’d finish the course.”
“Asking a question in a forum hours later feels pointless.”
Themes we heard
Timely answers — learners want to ask questions without leaving the lesson.
Visible peer progress — seeing classmates advance motivates them to keep up.
Belief in collaboration — most feel teamwork improves understanding and retention.
Design implication — These themes shaped Skillpath’s three AI pillars: automatic Group Formation, continuous Knowledge Assessment, and always‑on Virtual Agents for instant support.
User Persona
We researched who uses e-learning and what they want to get the most out of an e-learning platform. We categorized our target users into three main groups:
Wisdom
Seekers
These learners use e-learning to enhance their knowledge
Job
Hunters
These are learners who take up e-learning courses to get a good job
Net
Workers
These learners want to collaborate with others
“How Might We…?”
Aligned with Sara’s goals, pain points, and the collaboration gap we uncovered
HMW keep learners like Sara motivated past week 3 by making their progress and achievements unmistakably visible?
Addresses the drop‑off cliff and Sara’s need for ongoing engagement.HMW connect Sara with a flexible, like‑minded cohort so she can learn and network even when her schedule is unpredictable?
Targets her desire for collaboration and real‑life peer support.HMW deliver hands‑on, industry‑relevant projects and rapid feedback that translate classroom concepts into career‑ready skills?
Speaks to her goal of gaining practical knowledge for a summer internship.HMW tailor the learning path to Sara’s skill level and interests while guiding her with just‑in‑time answers?
Combines personalisation with the need for instant help, paving the way for AI‑driven assessment and virtual agents.
Hypothesis
AI system that plays a teacher role in e-learning platforms!
If an AI coach inside Skillpath can behave like a human instructor—diagnosing each learner’s needs, forming balanced study groups, and delivering just‑in‑time feedback—then learners will feel as supported as they would in a live classroom, remain engaged past week 3, and finish more courses.
Guided‑Learning Phases
Proposed Solution
The core pain points were the lack of personalized learning and limited opportunities for peer collaboration. To address these, I proposed a phased solution powered by AI to support both independent learning and community-driven feedback.
Phase 1: Students begin with individualized learning and complete their assignments independently.
Phase 2: After submitting their assignments by a set due date, each student is paired with a peer's submission for review. Using guided prompts, students provide structured feedback and, in turn, receive feedback from their assigned peers.
Phase 3: With peer insights in hand, students revise and resubmit their work—reinforcing active learning through reflection and iteration.
Individual
Learning
Group
Feedback From yourPeer
Individual + Group
Development
Wireframe
Upon explorations of various flow towards the main design, I decided to create a foundation for the main screens in each phase, to better understand the user flow and validate essential elements based on variuos feedback from eight student users.
Style Guide
To ensure Designing Emotionally Driven e-Learning system and have consistency in the project implementation, I developed a style guide which is the single source of truth that groups all the elements that will allow the teams to design and develop a product.
High-Fidelity
Based on the proposed solution, we decided to create a foundation for the main screens in each phase, to better understand the user flow and validate essential elements.
