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Project Overview

Project Model Canvas​

The Educado project follows a comprehensive project model focused on educating waste pickers through simple courses.

Key Components​

  • Smart Objective: Educate waste pickers with simple courses
  • Stakeholders: Waste pickers, educational institutions, environmental organizations
  • Team: AAU CCT/Software (Denmark) team
  • Deliverables: Mobile application for iOS and Android platforms

MoSCoW Prioritization​

🔴 Must Have

Core Educational Features:

  • Educate waste pickers through simple courses
  • Follow WAGC usability guidelines (low-level smartphones)
  • User identification (for tracking progress, could be username)
  • Certificate page (for showing proof of course completion)

Gamification & Engagement (Design team):

  • Design at least 4 types of gamification
  • Up-to-date content guide for gamification
  • Duolingo-like approach to courses
  • User progress tracking must be shown

User Experience:

  • Simple onboarding/tutorial
  • Implement at least 1 games
  • 3rd party course platform (Moodle)

🟡 Should Have

Authentication & Personalization:

  • User authentication
  • Detailed onboarding/tutorial
  • Personas present throughout the app

Interaction Design:

  • Clear micro interactions
  • Course feedback

🟢 Could Have

Enhanced Features:

  • Explore courses based on interests (intro-quiz)
  • Streaks of days where app has been used
  • Leaderboard
  • Text-to-speech
  • Access courses offline

⚫ Won't Have

Excluded Features:

  • Point system
  • Purely generated AI Videos

Impact vs Effort Analysis​

🚀 High Impact, Low Effort

Quick Wins:

  • Simple onboarding
  • 1 type of gamified course
  • User course progress tracking

🎯 High Impact, High Effort

Major Projects:

  • 3rd party course platform integration (Moodle)
  • Design of least 4 gamified course experiences
  • Duolingo-like approach to courses
  • Access courses offline
  • Text-to-speech for accessibility

🔧 Low Impact, Low Effort

Fill-ins:

  • Certificate page
  • User identification for tracking
  • Clear micro interactions

⚠️ Low Impact, High Effort

Questionable:

  • Purely generated AI Videos
  • Advanced leaderboard system

Priority Explanation​

The MoSCoW method helps prioritize features based on business value and project constraints:

  • Must Have (60%): Critical features without which the project fails
  • Should Have (20%): Important features that add significant value
  • Could Have (20%): Nice-to-have features if time and budget allow
  • Won't Have: Features explicitly excluded from current scope