Develop an Offline-First Digital Learning Analytics & Impact Reporting Dashboard (4 Required)

Mission and objectives

Camara works to improve learning outcomes for underserved communities by expanding access to inclusive, technology‑enabled education solutions. Through its digital learning initiatives, Camara supports students and teachers with tools that strengthen subject learning, digital literacy, and equitable access to quality education. As part of this mission, Camara has developed the Camara AI Assistant, an offline, curriculum-aligned digital learning tool used in schools to support classroom instruction, exam preparation, and independent learning.

To strengthen evidence‑based decision‑making and accountability to education partners, Camara seeks to develop a Digital Learning Analytics and Impact Reporting Dashboard that transforms system-generated learning data into actionable insights. This assignment aims to support the development of a structured digital reporting platform that enables Camara to better monitor learning engagement, inform program improvement, and strengthen data‑driven reporting to donors and relevant education stakeholders.

Context

Camara deploys offline curriculum‑aligned digital learning systems in schools through smart classrooms and digital learning hubs. These systems include the Camara AI Assistant and other digital tools designed to support classroom instruction, independent learning, and digital literacy development in low‑connectivity environments. While these tools generate valuable data on learning engagement and usage at the school level, this information is currently stored locally and is not consolidated into a centralized analytics and reporting structure. As a result, Camara has limited ability to systematically monitor adoption trends, analyze learning engagement patterns across schools, or translate digital usage data into insights that support programme improvement and external reporting. Camara has completed Phase 1, which involved the design stage. This phase defined the analytics framework, architecture, KPI model, dashboards, and data flow design, with support from UNV online volunteers.

The next phase focuses on implementation, including: – Developing backend APIs and data pipelines – Building interactive dashboards – Integrating AI-powered analytics – Supporting offline-first synchronization – Enabling device activity tracking (including Android tablets) In our project schools, Linux/Windows client computers with LAN networked school-based servers are being used alongside Android tablets. To improve visibility into digital learning engagement, the system will include application usage tracking (app name and time spent) on all these platforms including Android devices using permission-based methods. The goal is to build a working system that can be deployed in the project schools and scaled across multiple regions.

Expected Start Date: As soon as possible, following completion of onboarding requirements.

Task type

Web and Software Development

Task description

Camara Education Ethiopia is seeking four (4) Online Volunteers with complementary technical skills to develop the Digital Learning Analytics & Device Activity Tracking Platform that operates in low-connectivity environments and supports exportable reporting. Under the supervision of the Digital Learning & AI Lead and approved framework, volunteers will collaborate remotely to develop a functional, cross-platform system based on the approved design framework.

The assignment focuses on the development of a structured, privacy-conscious learning analytics and impact reporting platform that enables the aggregation, processing, and interpretation of learning engagement data generated by Camara’s digital learning tools. The assignment is task‑based, time‑bound, and fully remote, in line with UNV Online Volunteering criteria. Online Volunteers will collaborate virtually through email, shared documents and GitHub as a central platform for version control, code management, and collaborative development alongside periodic coordination calls, and will receive regular guidance and feedback from the supervising team.

The work will be divided into four main technical components, with tasks distributed among the four Online Volunteers according to their expertise. All activities will be carried out collaboratively, with close coordination among the online volunteers to ensure coherent and integrated outputs.

1. Backend & Data Engineering

– Develop backend APIs (e.g., FastAPI) for data ingestion

– Design and implement database schema (students, sessions, attempts, AI usage, device usage)

– Implement data validation and transformation logic

– Build endpoints for dashboard and AI integration

– Support offline-first data synchronization

2. Frontend & Dashboard Development

– Develop web-based dashboard interface (HTML, JS)

– Implement charts and analytics (e.g., Chart.js)

– Build interactive filters (time, school, subject, device type)

– Ensure mobile responsiveness (Android access via browser/PWA)

– Design user-friendly UI for different stakeholders

3. AI & Learning Analytics Integration

– Integrate Offline AI models for:

• – Question explanation
• – Student performance insights
• – Recommendations
• – Connect AI to analytics data (e.g., engagement, subjects’ mastery, trends)
• – Optimize AI models for offline/low-resource environments
• – Support chatbot interface for querying analytics

4. Platform & Device Integration (Android, Linux, Windows)

– Set up deployment environment for:

• – Linux – Windows compatibility
• – Develop a lightweight Android tracking module to:
• – Collect app usage (app name, usage time)
• – Store data locally (offline-first)
• – Sync data to backend when connectivity is available
• – Guide manual configuration on Android devices:
• – Enable Usage Access permission
• – Support school-based classroom server with local network deployment (LAN-based access)
• – Package system for easy installation in school’s devices

Expected Deliverables

– A working system including:

• – Backend API and database
• – Interactive analytics dashboard
• – AI-powered chatbot/insights
• – Device usage tracking module (including Android)

– Implemented data pipeline:

• – Learning activity data
• – Device usage data

– Core dashboards:

• – Executive overview
• – Student performance
• – Device & usage analytics
• – Android-based tracking application designed for learning analytics
• – App usage + time tracking
• – Offline storage and sync

– Technical documentation:

• – Setup and deployment guide
• – API documentation
• – Data schema
• – User guide

Assignment requirements