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Author(s):

Swapnil Abadar | Rahul Bade | Hemant Devkar | Indrajeet Pakhare | Prof. Shifa Shikalgar
Keywords:

Centralized Admission Process, E-Counsellor, Machine Learning, Recommender Systems, CAP, Education Technology
Abstract:
The Centralized Admission Process (CAP) Carried Out By The Maharashtra State CET Cell Plays A Crucial Role In Allocating Seats To Students Seeking Admission To Engineering Programs. Every Year, Thousands Of Students Struggle To Interpret Cutoff Trends, Rank Variations, Category-wise Seat Distributions, And Institute Preferences. Existing Manual Procedures Often Lead To Suboptimal College Selection, Stress, And Poor Decision-making. To Address This Challenge, This Paper Proposes E-Counsellor, An Intelligent, Data-driven Recommendation System That Predicts Suitable Colleges Based On CET Percentile, Rank, Category, And Student Preferences. The System Integrates Historical Cutoffs, Machine Learning Prediction Models, And A User-centric Interface To Deliver Accurate Recommendations. Similar AI-based Educational Counselling Frameworks Have Been Explored In Previous Studies [1], [10], [15], Confirming The Effectiveness Of Using Recommender Systems For Academic Decision-making. The Review Analyses Related Literature, Identifies Gaps, And Presents A Comprehensive Architecture For E-Counsellor.