Metacampus.ai

An edtech platform for lifelong learning in the ever-changing digital economy

This case study consists of Y1 in a startup where I developed a new educational product from the ground up. The platform is focused on the most cutting-edge topics including AI, Blockchain and NFT technologies, Cryptocurrencies, Tokenomics, Decentralised Finance, Creative Economy, Virtual Worlds, and more.

Overview

Y1 product evolution

Initial
concept

Play-to-Learn
educational experience

First
pivot

Web3 fundamentals Express program

Second
pivot

AI and Web3 Content-on-Demand platform

My role and
competencies:

As a key member of the founding team, I was responsible for Product Design, shaping every aspect of product development. From strategy to UX and branding, I played a hands-on role. I facilitated collaborative strategy sessions, conducted market research, designed prototypes, and user-tested propositions, all while sharpening the product vision and user experience along with stakeholders.

Chapter 1:

Problem
statement

"Our education system faces three critical challenges: obsolete career models, out-of-reach job opportunities, and alienation from new technologies. Therefore, accessible and scalable solutions are urgently needed to bridge the skills gap in a market that is changing at an exponential rate."

Our first hypothesis

"We believe that by launching a 'play-to-learn' educational platform combining gaming, NFT mechanics, creative communities, and virtual spaces for people who like to play games and are eager to learn about web3 we will accelerate their proficiency in a safe and effective way. "

Chapter 2:

Deep dive

Researching the web3 ecosystem and beyond

I kicked-off the project by researching the web3 space (platforms, crypto projects, NFT collections, tools, marketplaces, KOLs, Twitter threads, Discord servers, and more), and facilitating knowledge exchange with the team during strategy sessions.

I run 'pre-mortem' workshops to help us surface the most critical assumptions, followed by a competitor analysis exercise, and the mapping of stakeholders according to our initial business model.

Market size estimation; Competition landscape matrix; Pre-Morten exercise: Stakeholder mapping

Chapter 3:

Ideate and build

My chosen method

Amid high risk in the fast-evolving environment of web3, Blockchain, Crypto, NFTs, and AI, I adopted a lean 'build, measure, learn' methodology. This approach enabled me to quickly validate and/or disprove the most critical assumptions, evolve our thinking based on evidence and market signals, and make efficient use of resources.

9_grasshoppers_layers_hex shape copy.jpg

Sensai lore: learning through storyliving

In its first iteration, the platform aimed to emulate web3 elements, including NFT collections, token mechanics, and community culture, conveyed by the Sensai and Grasshopper storyline. Our objective was to use a creative way to engage and entertain users while reflecting the web3 dynamics during the learning process.

Shaping the user-journey mechanics

The first concept was a game-based learning experience divided into four stages or 'hops’. I employed the 'Pirate Metrics' framework to outline user benefits, functionalities, delightful features, and value creation opportunities at each step. This guided me in the creation of a comprehensive user journey map that included motivation, action points, rewards, proficiency levels, emotional states, and potential partners, ensuring a well-structured and engaging process.

Task-oriented flowchart (hop1 and 2)

I prioritised designing the first two user experience stages as they offered essential elements for hypothesis testing. The subsequent stages were still under consideration given the evolving web3 landscape and the complexity in structuring an entire ecosystem made of students, alumni, collaborators, industry partners, and investors.

Chapter 4:

Test and learn

Fast experiment with a low-fi prototype

To test the game adventure hypothesis, I designed an experiment, recruited target users, and conducted moderated interviews using minimal viable designs. I transcribed and analysed all the feedback, organised through affinity mapping, and derived insights that led to a product strategy rethink.

Experiment goals:

Gauge product understanding
Assess the solution's perceived value
Story resonance with users
Acceptable level of gamification
Users' preferred content formats
Ideal length of the program
Clarity of information and language
Test underlying learning mechanics