Predicting Students' Performance in Final Examination using Deep Neural Network
Md. Hanif Sikder, Md. Rakib Hosen, Kaniz Fatema, Md. Ashraful Islam
Asian Journal of Research in Computer Science · pp. 218–227 · Published 22 Dec 2022
10.9734/ajrcos/2022/v14i4306Abstract
The academic result is the most important thing in a student's career. This result depends on their academic performance and many other factors. Educational data mining can help both students and institutions develop their academic performance. For analysis of their performance, we can use new techniques Deep Learning, Convolution Neural Networks, Data Clustering, Optimization Algorithms, etc. In machine learning. Using Deep Learning, we will predict the student’s performance yearly in the form of CGPA and compare that with the real CGPA. A real dataset can boost the prediction performance. We used a real dataset from the Institute of Science, Trade & Technology (ISTT). We used a total of 18 data factors to predict the performance and the data factors are: Class Performance, Test Marks, Class Attendance, Due Time Assignment Submission, Lab Performance, Previous Semester Result, Family Education, Freelancer, Relationship with Faculty, Study Hours, Living Area, Social Media Attraction, Extra-Curricular Activity, Drug Addiction, Financial Support from Family, Political Involvement, Affair & Year Final Result.
Cited by 6
Jibril Abdikadir Ali, M. K. Abdi, Tawakal Abdi Ali · Discover Data · 2025
Tarik Kucukdeniz, M. Altuntas, Canan Hazal Akarsu · International Journal of Applied Mathematics, Computational Science and Systems Engineering · 2025
Pradeesh Hosea, Sebastian Terence · International Conferences on Information Science and System · 2025
Bayan Alnasyan, M. Basheri, M. Alassafi · Computers and Education: Artificial Intelligence · 2024
Bayan Alnasyan, Mohammed Basheri, Madini Alassafi · 2024
Quynh-Mai Do Le, Tien-Dat Nguyen, Viet-Tung Nguyen · Lecture Notes in Networks and Systems · 2025
Related research
- Prediction of Radiotherapy Dose Distribution for Glioblastoma Using Convolutional Neural Network Model — shares topic coverage
- A Review of Artificial Neural Networks for Chemical Process Optimization and Compound Property Prediction — shares topic coverage
- Monkeypox Detection Using Transfer Learning, ResNet50, Alex Net, ResNet18 & Custom CNN Model — shares topic coverage
- Leveraging Deep Learning Algorithms for Predicting Power Outages and Detecting Faults: A Review — shares topic coverage
- Deepfake Detection Using Deep Learning: A Review — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
6
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.