Designing an Intelligence Quotient (IQ)-Based Student Assessment Model Utilizing Machine Learning

Project Code :TCMAPY1095

Objective

The objective of this project is to create a machine learning-based student assessment model that accurately measures intelligence quotient (IQ) while addressing unaddressed challenges This model will prioritize personalization, providing tailored recommendations for cognitive improvement Long-term predictive validity will be evaluated, ethical and privacy guidelines established, and bias mitigated Transparency and explain ability will ensure model comprehensibility Real-time monitoring and feedback will enhance the learning process.

Abstract

This research aims to develop a comprehensive student assessment model based on Intelligence Quotient (IQ) using machine learning By utilizing various parameters, including academic records, input from professors, and family background, a dataset was created Multiple machine learning algorithms were trained and evaluated to select the best one Parameters such as quantitative reasoning ability and bachelor's degree certifications were considered and rated on a scale of 1-10 The study's objective was to determine the factors influencing student placement in companies and calculate a student's IQ score on a scale of 0-3 This model also estimated a suitable salary package range for students, aiding companies in assessing their capabilities

Keywords: Intelligence quotient (IQ), student assessment, academic performance, machine learning, data mining

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.