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A PREDICTED APPROACH TOWARDS WOMEN IN ENGINEERING EDUCATION/PROFESSION USING MACHINE LEARNING TECHNIQUES

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Title: A PREDICTED APPROACH TOWARDS WOMEN IN ENGINEERING EDUCATION/PROFESSION USING MACHINE LEARNING TECHNIQUES

Authors: Tahira Mahboob, Sabheen Gull, Zahra Saleem

Journal: International Journal of Innovation In Teaching And Learning

HEC Recognition History
Category From To
Y 2024-10-01 2025-12-31
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
Y 2020-07-01 2021-06-30

Publisher: International Islamic University, Islamabad

Country: Pakistan

Year: 2016

Volume: 1

Issue: 2

Language: en

DOI: 10.36261/ijdeel.v1i2.328

Categories
Prediction Models (16) Surgical Outcomes (181) Engineering Education (137) Digestive System Abnormalities (10) Women in Engineering (1) Pediatric Surgery (1097) Machine Learning (3478) Mortality (95) Neonatal Surgery (40) Higher Education (3928)

Abstract

Women have contributed to the diverse fields of engineering in modern and historical times. Women are often under-represented in the fields of engineering, both in academia and in the profession of engineering. A number of organizations and programs have been created to understand and overcome this tradition of gender disparity. In this paper we have applied a machine learning approach for the prediction of women in engineering in the coming future in Pakistan. We have identified several factors which influence the decision of women while selecting engineering as a profession.

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