AI Student Test Analytics Platform
Budget: ₹12,500 – ₹37,500 INR
I am building a cloud-hosted as well as on premises platform that ingests exam results from schools and coaching institutes and turns them into actionable insights on learning gaps, performance trends, and individualized improvement areas. The data you will receive is never uniform—each upload can combine multiple-choice scores, long-form essays, and other descriptive answers—so the analytics engine needs to handle mixed question types seamlessly.
Core expectations
• End-to-end data pipeline: secure upload (CSV, Excel or API), automatic parsing, storage, and cleansing.
• Analytics engine:
- MCQ analysis for accuracy, distractor strength, topic mastery
- NLP models to evaluate essays for structure, content, and rubric alignment
- Pattern mining to surface cohort-level trends and outliers
• Web dashboard (teacher, student, admin views) with drill-downs, heat maps, and downloadable PDF/CSV reports.
• Role-based access control and audit logs.
• Deployment scripts and concise documentation for hand-off.
If you have tools you prefer, let me know—what matters most is proven experience delivering AI-driven analytics products and the ability to explain your architectural choices.
Phase 1 (MVP – Online): Identify concept-wise weaknesses through online or scanned test
submissions mapped to a Smart Concept Bank.
Phase 2 (Offline Integration): Extend insights to traditional tests using scanned papers or teacher
uploads — making every test, online or offline, insight-rich.
Expected Outcomes: Students know exactly which concepts they’re weak in and how to improve.
Timeline is tight: I need a functional MVP live within a couple of months. Factor that into your milestones and highlight similar projects you have shipped on similar schedules when you respond.
Platform- Web app, Mobile app PWA
Data input- Pdf, Image, Word
Data security- VERY CRITICAL. No information of individual student should be visible to others
Analysis of single chapter tests & multiple chapters
- %age analysis of each section
- Which topics are consistently wrong?
- Which questions were completely wrong? 2/3 or 1/3, why were the marks deducted?
- Pattern across multiple tests?
- As data collects, compare result with better/ higher scoring papers
- Time management- Completion of test or questions left.
- Though the student completed all the questions in stipulated time, still if they would have focused on high marks questions, they would scored better?
Integration with existing platforms like multiple providers of LMS
Very Important:: Share the challenges in the first instances, no surprises later..
Core expectations
• End-to-end data pipeline: secure upload (CSV, Excel or API), automatic parsing, storage, and cleansing.
• Analytics engine:
- MCQ analysis for accuracy, distractor strength, topic mastery
- NLP models to evaluate essays for structure, content, and rubric alignment
- Pattern mining to surface cohort-level trends and outliers
• Web dashboard (teacher, student, admin views) with drill-downs, heat maps, and downloadable PDF/CSV reports.
• Role-based access control and audit logs.
• Deployment scripts and concise documentation for hand-off.
If you have tools you prefer, let me know—what matters most is proven experience delivering AI-driven analytics products and the ability to explain your architectural choices.
Phase 1 (MVP – Online): Identify concept-wise weaknesses through online or scanned test
submissions mapped to a Smart Concept Bank.
Phase 2 (Offline Integration): Extend insights to traditional tests using scanned papers or teacher
uploads — making every test, online or offline, insight-rich.
Expected Outcomes: Students know exactly which concepts they’re weak in and how to improve.
Timeline is tight: I need a functional MVP live within a couple of months. Factor that into your milestones and highlight similar projects you have shipped on similar schedules when you respond.
Platform- Web app, Mobile app PWA
Data input- Pdf, Image, Word
Data security- VERY CRITICAL. No information of individual student should be visible to others
Analysis of single chapter tests & multiple chapters
- %age analysis of each section
- Which topics are consistently wrong?
- Which questions were completely wrong? 2/3 or 1/3, why were the marks deducted?
- Pattern across multiple tests?
- As data collects, compare result with better/ higher scoring papers
- Time management- Completion of test or questions left.
- Though the student completed all the questions in stipulated time, still if they would have focused on high marks questions, they would scored better?
Integration with existing platforms like multiple providers of LMS
Very Important:: Share the challenges in the first instances, no surprises later..