Business & Management Studies

But where will all the women come from? Tackling the supply side of gender diversity in the technology workforce. Why do (female) graduate students avoid or take up ‘Technology Oriented’ courses?

But where will all the women come from? Tackling the supply side of gender diversity in the technology workforce. Why do (female) graduate students avoid or take up ‘Technology Oriented’ courses?

The study provides in-depth analysis into the inclinations and inhibitions of students (male and female) to take up AI courses.

Authors

Sonam Chawla, Assistant Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India.

Anshu Sharma, Associate Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India.

Summary

To build and implement an inclusive technology, the AI workforce must be more diverse. The need for qualified technology professionals is growing along with AI’s development, making inclusion even more important. The study has two primary research objectives: (i) To identify and understand the factors associated with student(female) decisions about whether to take up AI/ML/analytics/DS courses, and (ii) To suggest ways and methods that stakeholders (educational institutions) can adopt to motivate and facilitate students to take up AI/ML/analytics/DS courses.

The present study is based on the Social Cognitive Theory (SCT) structure (Bandura, 1986). The data was collected using four focus group discussions, and thematic analysis method was used for data analysis. The study provided in-depth analysis into the inclinations and inhibitions of students (male and female) to take up AI courses. The results also highlight the gender-based differences in the rational and reasons for choosing or giving-up AI courses as a career choice.

The study findings reveal four broad themes: (a) personal, (b) contextual, (c) outcome expectations and (d) cultural. The study aims to identify and offer strategies that educational institutions and other stakeholders may use to encourage and enable women to enrol in courses in artificial intelligence, data analytics, and decision sciences.

Published in: AIP Conference Proceedings, 5th International Conference on ICT Integration in Technical Education, ETLTC 2023 in collaboration with the 2nd International Conference on Entertainment Technology and Management, ICETM 2023, Aizuwakamatsu, 24 January 2023 through 27 January 2023.

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