| Title: |
Unveiling Career Pathways: Success and Challenges of Bangladeshi Women in Computer Science Through Machine Learning. |
| Authors: |
Howlader, Md. Azim; Aziz, Fahad Bin; Turaba, Mahbuba Yesmin; Emon, Tarikuzzaman; Hoque, Moskura; Jahan, Israt; Reza, Ahmed Saif; Chowdhury, Rayhan |
| Source: |
Journal of Innovation &Technology; 2025, Vol. 2025 Issue 2, p1-8, 8p |
| Subject Terms: |
MACHINE learning; GENDER inequality; EMPLOYMENT discrimination; EMPLOYMENT; VOCATIONAL guidance; BANGLADESHIS; STATISTICS |
| Geographic Terms: |
BANGLADESH |
| Abstract: |
Although the number of working computing women is steadily increasing in Bangladesh, it is a ray of hope that the gender gap is reducing day by day among final year students to higher-level job holders. This research aims to forecast how women in Bangladesh perceive and respond to pursuing careers in Computer Science. Primary data is collected by surveying women's experience that incorporates various open-ended and closed-ended questions and thus developed a dataset from 501 respondents, whereas respondents' age group were 19 to 60 years, and the majority were working in private sector jobs. A statistical tool Pearson's chi-square test is implemented to correlate between variables and thus different machine learning approaches, including Random Forest (which achieved a topmost accuracy of 85.00%), Decision Tree, XGBoost, Logistic Regression and K-Nearest Neighbors were implemented. It has explored the position, success, and obstacles of women in their place in Computer Science in Bangladesh, and one of the most delightful revelations is the borderline association of unequal pay. Notably, over 66% of the respondents reported that they do not encounter gender-based discrimination in their workplaces in terms of career advancement within various sectors of computer science. [ABSTRACT FROM AUTHOR] |
| : |
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| Database: |
Complementary Index |