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Learning Path Dashboard for Enhancing Skills – Build Guide & Project Kit

Pradip Singh069 reads

Design and deploy a dashboard that tracks learner progress, personalises paths, and gives instructors real-time insight. Perfect for B.Tech/M.Tech capstones and institutional pilots.

  • Category: Software (EdTech)
  • Difficulty: Intermediate
  • Time to Build: 4–6 weeks
  • Prerequisites: Python/JS basics, SQL, dashboards (Power BI/Tableau/React)
  • Deliverables: SRS, Architecture, DB schema, Working prototype, Test report

Get Project Kit (Free)   |   Request Instructor Pack   |   Book 15-min Consult

Problem Statement & Expected Outcome

Abstract: Build a dashboard that tracks learning progress and helps instructors create personalised learning paths for students, integrating multiple resources and monitoring progress in real time.

Outcome: Tailored learning experiences that improve completion and mastery while giving instructors live visibility to guide interventions.

Details: User Stories & Acceptance Criteria
  • As a student, I can see my path, next best module, and mastery score.
  • As an instructor, I can create cohorts, assign learning paths, and monitor progress.
  • Acceptance: Dashboard loads under 2s on broadband; instructor can export cohort report; student progress persists across sessions.

Scope & Modules

Module 1: Data Ingestion & Profiles

Student profiles, course catalog, resource tagging (difficulty, prerequisites, time-to-complete).

Module 2: Path Engine (Rules-based)

Recommend next module using rules: prerequisite completion, mastery threshold, and time availability.

Module 3: Progress Tracking

Completion %, mastery, time-on-task, drop-off points, reminders.

Module 4: Instructor Dashboard

Cohort view, at-risk learners, bulk assignments, export to CSV/PDF.

Module 5: Student Dashboard

Personal path, progress donut, recommended resources, streaks/gamification.

Stretch Goals

AB testing different paths; adaptive engine using basic ML; LTI integration.

Proposed Architecture & Tech Stack

Option A (Fast to MVP): Supabase + React + BI Embed
  • DB/Auth: Supabase (Postgres)
  • Frontend: React/Next.js
  • Dashboards: Power BI/Tableau embedded
Option B (Python-heavy): Django + PostgreSQL + Plotly
  • API: Django/DRF
  • Charts: Plotly/Dash
  • Task queue: Celery for reminders

KPIs & Analytics

  • Active learners / week, time-on-task, module completion
  • Mastery growth, at-risk cohort %, intervention-to-improvement time
  • Resource effectiveness (completion <→ score lift)

Milestones & Timeline

4–6 Week Plan (Suggested)
  1. Week 1: SRS, schema, wireframes
  2. Week 2: Profiles + ingestion
  3. Week 3: Progress tracking + student view
  4. Week 4: Instructor view + exports
  5. Week 5: BI embed + polish
  6. Week 6: Testing, report, presentation

Who It’s For

  • Students/Capstone Teams: complete kit + mentorship option
  • Instructors: pilot pack with rubrics & cohort templates
  • Institutions: scoped POC with outcomes tracking

Get Project Kit (PDF + CSV + Figma)   |   Request Instructor Pack   |   Chat on WhatsApp

FAQs

What’s included in the Project Kit?

SRS template, DB schema, wireframes, sample dataset (CSV), KPI checklist, and a 4–6 week milestone plan.

Can you mentor or build with us?

Yes. Choose DIY with mentor support, co-build with our engineer, or done-for-you delivery with deployment support.

Which tech stack should we pick?

For speed, use Supabase + React + embedded BI. For Python-first teams, pick Django + Plotly; both are supported in our kit.

Related Abstracts You May Like

Ready to start? Download the kit or talk to a mentor. We’ll help you go from abstract to demo in 4–6 weeks.

Download Project Kit   |   Book 15-min Consult

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