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In engineering education in the United States (as elsewhere), it is widely recognized that the percentage of women and minorities who acquire engineering degrees is significantly lower than their representation in the general population. Many studies have investigated the cause of this lack of representation in engineering and other STEM (science, technology, engineering, and mathematics) degree programs. It is widely recognized that the percentage of women and minorities who acquire engineering degrees is significantly lower than their representation in the general population. Adolescents' occupational identity development depends in large part on their internalized mental models of what a given type of professional “looks like,” their subjective sense of their own capacity to be successful at certain tasks and with certain types of knowledge, and the degree to which they feel as if they belong to a community of practice. This paper considers how the concept of “hidden curriculum” can be applied to how underrepresented students experience engineering education uniquely. The concept of the “hidden curriculum” is used to describe the set of structured learning experiences or conditions that occur beyond the design intent of the learning journey established by the explicit curriculum. The hidden curriculum is typically unintentional, unplanned, and less “controllable” than the explicit curriculum. Despite the difficulty in assessing hidden learning expectations, hidden curriculum consistently places expectations on students beyond the explicit curriculum. It is critical to understand not just what variables prevent underrepresented students from persisting, but also what factors encourage their persistence, as such persistence is critical to ensuring a more diverse engineering workforce. This work focuses on how minoritized groups specifically develop professional identity through the hidden curriculum. We consider their perception of belonging in engineering, their experiences of exclusion in various forms, and the mechanisms by which exclusion transpires. By better understanding the cultural dimensions of exclusion, we hope to advance efforts toward inclusion.
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Introducing Women to Data Science: Investigating the Gender Gap in a Learning Initiative on Kaggle
Unlike many STEM fields, data science has emerged with online communities serving as prominent spaces for professional development and learning. This paper explores factors that contribute to gender differences regarding perceptions of satisfaction and difficulty in a learning initiative for data science hosted by the Kaggle community. We investigate multiple factors: prior experience and skills, professional role, and communication within a learning community. Our results, based on a survey of 2,707 aspiring data scientists, suggest that learners who identify as women do not perceive assignments to be more difficult than men, but complete fewer assignments. The increasing difficulty of the learning experience affected all learners, but men were still able to complete the hardest assignments at a higher rate than women despite experiencing similar barriers. Overall, the findings demonstrate how learning initiatives in technically intensive domains contribute to different outcomes between groups.
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- Award ID(s):
- 2104551
- PAR ID:
- 10543098
- Publisher / Repository:
- Proceedings of the 57th Hawaii International Conference on System Sciences
- Date Published:
- Page Range / eLocation ID:
- 7184
- Subject(s) / Keyword(s):
- STEM Education and Workforce Development: Addressing Equity and Inclusion for Underserved Populations, data science, gender gaps, informal learning, online communities, stem
- Format(s):
- Medium: X
- Location:
- https://hdl.handle.net/10125/107247
- Sponsoring Org:
- National Science Foundation
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