Neural engineering is an emerging and multidisciplinary field in which engineering approaches are applied to neuroscience problems. Women are underrepresented in engineering fields, and indeed in science, technology, engineering, and mathematics (STEM) fields generally. Underrepresentation of women is particularly notable at later academic career stages, suggesting that even though women are interested in the field, barriers exist that ultimately cause them to leave. Here, we investigate many of the obstacles to women’s success in the field of neural engineering and provide recommendations and materials to overcome them. We conducted a review of the literature from the past 15 years regarding the experiences of women in academic careers, as well as reports on the number of women in fields closely related to neural engineering from the National Science Foundation (NSF) and the American Society for Engineering Education (ASEE). Additionally, we interviewed six women in neural engineering who are involved in initiatives and outreach concerning the inclusion and experiences of women in engineering. Throughout the literature and interviews, we identified common themes spanning the role of identity and confidence, professional relationships, career-related hurdles, and personal and professional expectations. We explore each of these themes in detail and provide resources to support the growth of women as they climb within the field of neural engineering.

Neural engineering is an emerging and multidisciplinary field in which engineering approaches are applied to neuroscience problems. Women are underrepresented in engineering fields, and indeed in science, technology, engineering, and mathematics (STEM) fields generally. Underrepresentation of women is particularly notable at later academic career stages, suggesting that even though women are interested in the field, barriers exist that ultimately cause them to leave. Here, we investigate many of the obstacles to women’s success in the field of neural engineering and provide recommendations and materials to overcome them. We conducted a review of the literature from the past 15 years regarding the experiences of women in academic careers, as well as reports on the number of women in fields closely related to neural engineering from the National Science Foundation (NSF) and the American Society for Engineering Education (ASEE). Additionally, we interviewed six women in neural engineering who are involved in initiatives and outreach concerning the inclusion and experiences of women in engineering. Throughout the literature and interviews, we identified common themes spanning the role of identity and confidence, professional relationships, career-related hurdles, and personal and professional expectations. We explore each of these themes in detail and provide resources to support the growth of women as they climb within the field of neural engineering.

Neural engineering is an emerging and multidisciplinary field in which engineering approaches are applied to neuroscience problems. Women are underrepresented in engineering fields, and indeed in science, technology, engineering, and mathematics (STEM) fields generally. Underrepresentation of women is particularly notable at later academic career stages, suggesting that even though women are interested in the field, barriers exist that ultimately cause them to leave. Here, we investigate many of the obstacles to women’s success in the field of neural engineering and provide recommendations and materials to overcome them. We conducted a review of the literature from the past 15 years regarding the experiences of women in academic careers, as well as reports on the number of women in fields closely related to neural engineering from the National Science Foundation (NSF) and the American Society for Engineering Education (ASEE). Additionally, we interviewed six women in neural engineering who are involved in initiatives and outreach concerning the inclusion and experiences of women in engineering. Throughout the literature and interviews, we identified common themes spanning the role of identity and confidence, professional relationships, career-related hurdles, and personal and professional expectations. We explore each of these themes in detail and provide resources to support the growth of women as they climb within the field of neural engineering.

Founded in 2021, Raiseacad nitk operates in the Edtech sector offering courses on major subjects such as computer science, information technology, and various engineering disciplines including electronics, electrical, chemical, and civil engineering. The startup focuses on providing educational resources to students seeking knowledge in these fields. Raiseacad aims to enhance learning experiences through structured courses tailored to meet industry standards. The company's mission is to support aspiring professionals in their educational journey.

The statistic displays the sources of help or support reported by women working in a science, technology, engineering, or mathematics (STEM) field worldwide, as of 2016. At that time, **** percent of respondents highlighted diversity programs as having helped their careers.

Abstract

High quality postgraduate training in science, technology, engineering and mathematics (STEM) related disciplines in sub-Saharan Africa (SSA) is important to strengthen research evidence to advance development and ensure countries achieve the Sustainable Development Goals (SDGs). Equally, participation of women in STEM careers is vital, to ensure that countries develop economies that work for all their citizens. However, women and girls remain underrepresented in STEM due to gender stereotyping, lack of visible role models, and unsupportive policies and work environments. Therefore, there is a need to consolidate information on participation and experiences of women in STEM related postgraduate training and careers in SSA to enhance their contribution to realizing the SDGs. The primary objective of this study is to examine the participation and experiences of women in postgraduate training, and their subsequent recruitment, retention and progression in STEM careers in East Africa. A secondary objective is to establish the gender gaps in training and career engagement in selected STEM related academic disciplines in East Africa. The descriptive study will employ a mixed methods approach, including a scoping review, qualitative interviews, and quantitative analysis of secondary data. We will synthesize results to inform the development of an effective gendered approach and framework to improve participation and experiences of women in STEM training and career engagements in SSA. We will conduct the study over a period of five years.

Geographic coverage

Regional coverage (East Africa Region)

Analysis unit

Individual Women in STEM

Universe

Qualitative data: Women in Science Technology Engineering and Mathematics (STEM) in postgraduate training and career Quantitative data: Postgraduate students, faculty, reseachers and supervisors (both men and women) in STEM in Inter-University Council for East Africa (IUCEA) member Universitiies

Sampling procedure

The study utilized a purposive sampling technique and targeted all universities that offered doctoral programs in applied sciences, technology, engineering, and mathematics. At the time, only 23 of the 74 universities in Kenya—equivalent to 30%—offered doctoral degrees in STEM. It was assumed that a similar or lower percentage would be found in the other five countries, namely Uganda, Tanzania, Rwanda, Burundi, and South Sudan.

Purposive sampling was used to recruit participants from purposively selected universities and national higher education commissions and agencies for the study. In universities, all students enrolled in doctoral programs in STEM were considered. Additionally, female and male students' lecturers, supervisors, mentors, and other faculty members and researchers in the identified institutions were also considered for participation in the study.

Purposive sampling of doctoral students, faculty, and early career researchers (post-doctoral fellows within the first six years since receiving their PhD) was conducted using the following inclusion criteria:

Inclusion criteria i. Worked in a STEM field/discipline ii. Enrolled in a doctoral program within a STEM field iii. Early career researchers in a STEM field in research organizations iv. Faculty in a STEM field at a university

Additionally, registrars, postgraduate training coordinators, heads of departments, and officials from national agencies and ministries related to postgraduate training and research were purposively selected from all the identified universities to provide input on existing policies, guidelines, and enrollment data. For each of the mentioned groups, 7-12 interviews were conducted, totaling 60 interviews.

Sampling deviation

Qualitative For the Key informant interviews one participant was interviewed from the engineers board despite the scope being Inter-University Council for East Africa (IUCEA) member Universities.

Quantitative The online survey was completed by some researchers not working/teaching in IUCEA member universities

Mode of data collection

Other [oth]

Research instrument

Quantitative data collection A. Online Survey This was carried out through an online survey questionnaire that was circulated via email and other digital platforms such as WhatsApp. The questionnaire had various parts: Part A - Participants characteristics This section mainly collected demographic details such as age, gender, nationality, residence, marital status, income, highest level of education completed, year of study, supervision and mentoship relationship, field of study in STEM (Science, Technology, Enginnering and Mathematics), mode of funding of postgraduate degree,

Part B - Status of Gender equality This section collected information on students enrollment and graduation in masters and PhD in STEM looking at gender distribution,

Part C - Factors that contribute to participation of women in STEM This section collected information on the factors or situations encountered while pursuing career in STEM in your specific discipline

Part D - Strategies for Optimizing Women's Engagement in STEM This section collected information on the strategies can maximize engagement of women in STEM training PhD level and subsequent careers

Part E - Effect of the COVID-19 pandemic on women's progression In this section collected information on COVID-19 pandemic affect on research progress or deadline for submission of thesis, COVID-19 pandemic affect on current research funding, COVID-19 pandemic caused researchers to work from home, working from affected progress in studies, any direct responsibilities caring for children, number of children being taken care of, change of domestic work responsibilities since the COVID-19 outbreak, change of domestic work responsibilities since the COVID-19 outbreak on studies, COVID-19 pandemic affect on access to these research tools which inlude: Computer or laptop, Reliable Internet, Assistive Technology, Laboratory equipment, University Library, Archives/special collections and Access to patients/research participants. It als collected information on: any benefits to COVID-19 pandemic for your work, some ways one thinks their supervisor or line manager could support or help one manage the impacts of COVID-19 on studies

The questionnaire was developed in English and was latertranslated into French to accommodate the French speaking countries i.e Burundi and Rwanda. The French questionnaire was backtlanslated to English to ensure the questions still maintained their original meaning. This work was done by an external consultant and the French questionnaires were reviewed by the research assistant from Burundi and tested among postgraduate students in Light University.

All questionnares and modules are provided as external resources.

Cleaning operations

Qualitative The data was collected through qualitative interviews (In-depth interviews) and focus group discussions. They were audio recorded and the recordings were transcribed on Ms Ofiice.The transcript were subjected to data quality checks and the clean transcripts were anonyzed for data protection.

QUANTITATIVE Secondary data The data was collected from the five countries in an Ms Excel designed data abstraction sheet. The data abstraction sheet helped the universities administrators and rergistrars to directly enter the data only in the required field and for the defined or specific variables. For the dataset that was in hardcopy format the data entry was also done using the data abstraction sheets. The data sets were subjected to data quality checks for data quality. We used a standard template to ensure data editing took place during data entry.

Online survey Data entry was in form of responding to the survey. Data editing was done while cleaning the data.

Response rate

Quantitaive The online survey link was circulated using contacts within universities and research institutions in East Africa via email and social media platforms such as WhatApp hence it is impossible to track those who received the survey and hence it is not possible t calculate the survey response rate.

Sampling error estimates

NA

Number of people in STEM (science, technology, engineering, and math and computer science) and BHASE (non-STEM) fields of study who worked in STEM, STEM-related or non-STEM occupations.

The statistic displays the barriers or sources of harm to the career success of women working in a science, technology, engineering, or mathematics (STEM) field worldwide, as of 2016. At that time, ** percent of respondents felt that gender discrimination had hindered their careers.

STEM Education Market Size and Growth Outlook

Worldwide, the STEM education market size reached USD 98.2 billion in 2024, driven by rapid technological advancements and increasing government investments in educational infrastructure. The market is anticipated to grow at a robust CAGR of 13.5% from 2025 to 2033, projecting a remarkable market size of USD 292.8 billion by 2033. The growth of this market is primarily attributed to the rising demand for a skilled workforce in science, technology, engineering, and mathematics fields, as well as the integration of advanced digital learning solutions into mainstream education systems worldwide.

The growth factors propelling the STEM education market are multifaceted, with one of the most significant being the global shift toward digital economies. As industries increasingly rely on automation, artificial intelligence, and data analytics, the demand for professionals equipped with STEM skills continues to surge. Governments and educational institutions are responding by revamping curricula to emphasize STEM subjects and by introducing coding, robotics, and computational thinking at earlier stages of education. Additionally, the proliferation of EdTech companies offering innovative software and hardware solutions is making STEM education more accessible and engaging, further accelerating market growth.

Another crucial driver is the growing recognition of STEM education’s role in fostering innovation and economic competitiveness. Countries across the globe, especially in Asia Pacific and North America, are prioritizing STEM education to ensure their future workforce can meet the demands of rapidly evolving job markets. Public-private partnerships are on the rise, with tech giants collaborating with educational institutions to provide resources, mentorship, and experiential learning opportunities. The increased focus on gender diversity and inclusion in STEM fields is also expanding the talent pool, with targeted initiatives encouraging underrepresented groups to pursue STEM careers.

Furthermore, the COVID-19 pandemic has significantly accelerated the adoption of online and blended learning modes within STEM education. Schools, universities, and corporate training centers have invested heavily in digital platforms, virtual labs, and interactive tools to ensure continuity of learning during disruptions. This transition has not only highlighted the flexibility and scalability of technology-enabled STEM education but also exposed gaps in digital infrastructure, particularly in developing regions. As a result, there is a renewed emphasis on bridging the digital divide and ensuring equitable access to high-quality STEM learning experiences for all students, regardless of geography or socioeconomic status.

From a regional perspective, North America currently leads the STEM education market in terms of revenue, accounting for approximately 38% of the global share in 2024. This dominance is attributed to strong government support, advanced technological infrastructure, and a culture of innovation. However, the Asia Pacific region is expected to witness the fastest growth during the forecast period, driven by large-scale educational reforms, burgeoning youth populations, and increasing investments from both the public and private sectors. Europe continues to maintain a significant presence, focusing on research-driven STEM programs and cross-border collaborations, while Latin America and the Middle East & Africa are gradually catching up through targeted policy interventions and international partnerships.

STEM Education Market by Component

The component segment of the STEM education market is categorized into curriculum, software, hardware, and services, each playing a pivotal role in shaping the overall learning experience. Curriculum development remains the backbone of STEM education, with a growing emphasis on interdisciplinary and project-based learning approaches

This dataset tracks employed persons with tertiary education in science, technology, engineering, and mathematics fields, broken down by occupation across the European Union and member states. Understanding the distribution of STEM-educated talent across different occupations reveals how advanced economies allocate their highest-skilled human capital and identifies sectoral demand for specialized expertise. The dataset covers 28 European entities with 2,114 data records spanning from 2021 to 2024. All 28 entities, including Austria, Belgium, Bulgaria, Cyprus, and the Czech Republic, reported data through 2024. This comprehensive geographic and temporal scope enables both cross-country comparisons of STEM employment patterns and analysis of how occupational distribution shifted across the four-year period. Researchers and labor economists use this data to understand workforce composition, identify skills gaps, and forecast demand for STEM talent by occupation type. Policymakers reference occupational breakdowns to guide education and immigration strategies, while business analysts track employment trends to anticipate hiring needs in specialized technical roles. The data reveals whether STEM graduates concentrate in engineering and computing roles or distribute across broader professional occupations. This publicly available Eurostat resource supports evidence-based workforce planning, academic research on skills markets, and strategic business intelligence for companies competing for technical talent across Europe.