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

2025-06-28 16:36:10 - Adil Khan

Project Title

Student performance predication

Project Area of Specialization Computer ScienceProject 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 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

Benefits of the Project Technical Details of Final Deliverable Final Deliverable of the Project Software SystemCore Industry ITOther Industries IT Core Technology OthersOther Technologies OthersSustainable Development Goals Quality EducationRequired Resources
Item Name Type No. of Units Per Unit Cost (in Rs) Total (in Rs)
Total in (Rs) 70000
GPU Equipment16000060000
Printing, marketing Miscellaneous 11000010000
- Miscellaneous 000
- Miscellaneous 000

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