Student performance predication

Every year, a large volume of information about students? performance is processed in schools, colleges, and higher studies institutes. This information statistically associates students? performance with their study schedule and family-related characteristics. Recent methods have significantly cont

Project Title

Student performance predication

Project Area of Specialization

Computer Science

Project Summary

Every year, a large volume of information about students’ performance is processed in schools, colleges, and higher studies institutes. This information statistically associates students’ performance with their study schedule and family-related characteristics. Recent methods have significantly contributed to student’s performance prediction area of research, but they are insufficient to address the challenges created by students' daily activities schedules. Therefore, in the current attempt, we will present a multilayer students' performance prediction method that will use students' daily activities schedules for performance prediciton. The contributions of the proposed method will be threefold. First, during quantization, a multilayer model is initiated by splitting students' daily activities schedules into four factors, and a specific range is assigned to each factor (timing schedules of studying, outing, traveling to school, and free timing as well as parent’s relationships). Second, the range of students' performance outcome (0–100) is divided into four periodic intervals (with a period of 1), i.e., At Risk, Average, Satisfied, Secured. The component-wise division of students' daily activities schedules and students' performance outcome is to ensure prediction accuracy that makes the method more testable and maintainable. Third, it iteratively estimate the students' performance outcome under the influence of students' daily activities schedules layers.

Project Objectives

• To make a comfortable android application
• To help the students to know his/her specialty, weakness and strengths
• To provide a better feedback

Project Implementation Method

The Bayesian neural network is one of the techniques to do this work and will produce posterior probability of the most probable performance class

• At Risk
• Average
• Satisfied
• Secured

Benefits of the Project

• All organization will use this system to check the students performance and will able to tell them if they are eligible for a particular filed or course
• This will be an android based application which can be used by students and educational systems
• It will have the ability to test the student’s psychology
• It can provide the feedbacks as well

Technical Details of Final Deliverable

• We will provide andriod application to predict students' performances. 
• Literature is saturated with many research findings; nevertheless, this system will quantize and iteratively estimate students' performance under the umbrella of students' schedules, i.e., Study Schedule, Outing Schedule, Travel Timing (Between School and Home), and Sleeping Schedule.

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

IT

Core Technology

Others

Other Technologies

Others

Sustainable Development Goals

Quality Education

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com