Name
Title | ||
|---|---|---|
A Machine Learning Approach to Performance and Dropout prediction in Computer Science - Bangladesh Perspective. |
Abstract | ||
|---|---|---|
This is an era of computers and technology. Nowadays Computer Science (C.S.) and other technology-related subjects are a hot cake for the students. Due to a good job market for these subjects, students are taking computer science and other related topics without thinking about their capability and without knowing the curriculum of these subjects. So the dropout rate is getting high day by day in these subjects. Especially developing countries like Bangladesh. In this work, we have used current computer science students\u0027 data to predict their and also prospective C.S. students\u0027 future performance and the chance of dropout using machine learning algorithms like SVM, naive Bayes, neural network, etc. We have also predicted the crucial factors that are strongly correlated to the performance of a C.S. student. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICCCNT49239.2020.9225356 | ICCCNT |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sheikh Arif Ahmed | 1 | 0 | 0.34 |
| Md. Aref Billah | 2 | 0 | 0.34 |
| Shahidul Islam Khan | 3 | 0 | 0.34 |