Indian Institute of Technology, Ropar — Internship 2025
The Concept Positioning System (CPS) is an educational recommendation engine inspired by intelligent systems like YouTube and Netflix, but adapted for learning. It analyzes a learner’s current knowledge and designs a personalized path toward mastering a desired concept by bridging gaps through intermediate concepts and resources.
Instead of recommending based on user preference, CPS emphasizes:
- Conceptual prerequisites
- Learning trajectory
- Pedagogical diversity
- Automatic path correction and augmentation
A learner who understands concepts A, B, and F may struggle with advanced concept K due to missing links. CPS recommends a prerequisite-aware sequence (X₁, X₂, ...) so the learner reaches K effectively.
In Continuous Active Learning (CAL) environments, if a student gets stuck at V₃ before reaching V₄, CPS may suggest auxiliary resources (V₃a, V₃b, ..., V₃n) to bridge the gap autonomously.
- Prerequisite Graph Construction for Domain-Specific Knowledge
- Personalized Learning Path Recommendation Using Knowledge Graphs
- Identifying Conceptual Gaps from Video Learning Logs
- Semantic Analysis of Learner Queries to Map to Concept Gaps
- Multi-Modal Learning Path Optimization
- Dynamic Path Adjustment in Strict CAL Settings
- Dependency-Aware Assessment Generator
- Learner Knowledge State Estimation using Bayesian Networks
- Intervention Detection for Conceptual Bottlenecks
- Comparative Study of CPS vs Traditional Recommendation Systems in Education
- Personal Learning Path Visualization Dashboard
- Meta-Learning for Cross-Domain Concept Reusability
- Explainable Recommendation in Concept-Based Learning Paths
- Benchmarking CPS Algorithms on Open Educational Data
- Simulated Learner Model for CPS Evaluation
- Parthan Rajesh (Team Lead) - [email protected]
- Manjistha Bidkar - [email protected]
- Adwaidh Payattuparambil - [email protected]
- Srishti Koni - [email protected]
- Vansh Tuteja - [email protected]
- Chirag Khairnar (Team Lead) - [email protected]
- Aditi Mishra - [email protected]
- Pola Gautam Sai - [email protected]
- Shashwat Kumar - [email protected]
- Shrey Ojha Shreya - [email protected]
- Bhavitha B (Team Lead) - [email protected]
- Tamalampudi Sameer Reddy - [email protected]
- Anurag Kumar - [email protected]
- Nishant - [email protected]
- Davuluri Siva Sai (Team Lead) - [email protected]
- Adapala Meghana - [email protected]
- Galla Durga Rama Satya Pradeep Kumar - [email protected]
- Jahnavi Jahnavi - [email protected]
- Kommineni Sai Sahithya - [email protected]
- Alakh Mathur (Team Lead) - [email protected]
- Aditya Chandra Das - [email protected]
- Anand - [email protected]
- K Pavithra - [email protected]
- Omkar Kumar - [email protected]
- Nishita Sharma (Team Lead) - [email protected]
- Deepali - [email protected]
- Devansh Srivastava - [email protected]
- Shiv Kumar Behera - [email protected]
- Sonali - [email protected]
- Tanisha Kundra - [email protected]
- Ayush Singh (Team Lead) - [email protected]
- Abhinav Ranjan Sulabh - [email protected]
- Ankit Pandey - [email protected]
- Titus George - [email protected]
- Vedam Venkata Sarma - [email protected]
- Nikita S Raj Kapini (Team Lead) - [email protected]
- Nakshatra Bhandary - [email protected]
- Manda Rani - [email protected]
- Shreyas Mene - [email protected]
- Yeddula Pushkala - [email protected]
- Nelluri Saideepak (Team Lead) - [email protected]
- Deekshita Totapally - [email protected]
- R Hindu - [email protected]
- Rasmal Gnaneshwar - [email protected]
- Subathra R - [email protected]
- Pentapati V V Satya Pavan Sandeep (Team Lead) - [email protected]
- Mondi Sai Lokesh - [email protected]
- Nabarupa Banik - [email protected]
- Snehasis Mukhopadhyay - [email protected]
- Venkata Sai Pranav Balusu - [email protected]
Each team maintains its project implementation in a dedicated sub-folder under the root