Information communication technologies (ICT) stands out as one of the rapidly developing and highly paid fields. In response to the increasing demand and interest in ICT education, in recent years, Kazakhstan has substantially increased the allocation of educational grants to this sector. This increase is marked by a fourfold rise, from 2469 grants in the 2020-2021 academic year to 10 103 grants in 2022-2023 (Ministry of Science and Higher Education of Kazakhstan, 2023). However, a pronounced gender gap persists in ICT education in Kazakhstan, consistent with a global pattern emphasized by UNESCO in 2017.  According to UNESCO (2017), the representation of women in STEM education, particularly in ICT, remains notably low, with only three percent of women and girls worldwide opting for STEM-related fields of study. This trend is reflected in Kazakhstan, where, based on the data from the Bureau of National Statistics for the 2022-2023 academic year, only a quarter of students enrolled in undergraduate IT programs were females (13 298 out of 49 938 students). Women’s participation in STEM education and employment not only faces low levels, but also experiences a notably high attrition rate, often described as a “leaky pipeline”. Notably, in STEM fields, women tend to "leak out" more than men, creating a sex-based filter that unintentionally contributes to the observed gender imbalance (Blickenstaf, 2005). The imbalance results from a cumulative effect of multiple factors rather than a conscious decision to exclude women from the STEM pipeline (Blickenstaf, 2005).

A lot of international research looking at women in IT focuses on female students’ enrollment in computing majors and investigates primary, secondary and high school initiatives and experiences that might influence gender differences in school students' decision-making to pursue a major in IT (Beck et al., 2023; Diethelm et al., 2020; Zdawczyk & Varma, 2023). Interestingly, the further girls are in their school years, the lower self-efficacy in STEM they have (Yu & Jen, 2021). Yet, research addressing the issue of women’s low representation in IT studying the population at higher education started to emerge just recently (Holanda & Silva, 2022). Recent research involving university students in computing majors reported gender differences in distributing roles during group work (Jimenez et al., 2021), the presence of discourses linking masculinity and software development (Tassabehji, 2021) and computer science (Ottemo et al., 2021), and positive influence of informal mentoring and sense of belonging to the program on women’s persistence in computer science majors (Davis, 2022).

The underrepresentation of women in IT fields is deemed crucial due to its impact on the effective use of talent, as well as the importance of diversity in maintaining economic competitiveness. Although experiences during school predict female students’ persistence in computer science majors in college (Weston et al., 2019), a closer investigation of young women’s experiences in IT majors in tertiary education might contribute to providing more insight into understanding how women progress through the pipeline. This study aims to explore undergraduate women’s perspectives on the challenges they face and success strategies they use in pursuing their academic degree in IT, and what they see as important factors to successfully navigate through the pipeline.  

The proposed Research questions are:

1. What factors do undergraduate women see as important for their success in IT majors?

2. What are the challenges that undergraduate women in the IT field face when pursuing their academic degrees? 

3. What are their success strategies? 

To ensure a thorough investigation of the viewpoints and experiences of undergraduate women majoring in IT (n = 30), the study utilizes a qualitative research design that incorporates collecting interview data alongside participants’ visualizations of their perspectives using text-to-image generative AI. The utilization of both methodologies allows not only to enrich the depth of the study but also facilitate triangulation, enabling the cross-verification and validation of results (Creswell & Creswell, 2017). The sample for the study is thirty undergraduate women who major in IT in universities in the two main cities in Kazakhstan, Astana and Almaty. The participants are recruited through the universities selected based on the convenience sampling strategy, using a gatekeeper to allow access to the research sites and the potential participants. The data collection process involves two stages. First, the recruited participants are asked to use an AI tool to graphically visualize the desired but possibly “missing ingredients” to successfully pursue their studies and career in IT as a woman. To provide conditions for the participants to actually connect with their identities of future IT specialists, while simultaneously tapping into participants’ creativity and facilitating a more in-depth understanding of the participants' thoughts, feelings, and experiences, the participants are trained to use Microsoft Bing Image Creator powered by OpenAI’s latest image-generating model, DALL-E 3, to create these graphic images. During the second stage of data collection, in-depth semistructured face-to-face follow-up interviews are conducted with each of the participants to probe further into their subjective interpretations of the AI-generated images. Beyond these interpretations, the interview questions elicit information on personal and institutional factors that impact participants’ choices to major in computer science and information technology, continue their education, or possibly leave the field altogether. The AI-generated images are analyzed using social-semiotic analysis that examines how participants construct and interpret meanings and the social contexts where these meanings are formed and understood (Ghazvineh, 2024). The interviews are analyzed in NVivo, computer-assisted qualitative data analysis software, using thematic analysis (Clarke and Braun, 2017). Thematic analysis follows the system of stages developed by Braun and Clarke's (2017): becoming acquainted with the data, creating preliminary codes, identifying themes, reviewing these themes, delineating and assigning names to the themes, and ultimately producing the final report.

Leveraging the capabilities of the text-to-image generator DALLE, the research provides a novel lens through which to examine participants' experiences but also offers a unique avenue for expressing and understanding ideas and emotions that may be challenging to articulate in traditional qualitative research. Using AI that enables individuals with limited or no artistic training to create striking images that embody their experiences (Li & Yang, 2023), the study might uncover the “missing ingredients” in women’s success in pursuing an IT degree that may have been overlooked in previous research, thereby contributing to a more comprehensive and holistic understanding of women’s perspectives. The outcomes of this research will contribute to achieving gender equality and empowerment of women in IT in accordance with the UN’s Sustainable Development Goal 5 (SDG 5), developed in 2015. More specifically, understanding the factors undergraduate women see as important for their success in IT majors will contribute to fostering an environment that supports the empowerment of women and girls, as outlined in SDG 5. Revealing potential challenges of undergraduate women in IT might prompt the integration of support mechanisms within educational practices and policies, promoting a more gender-responsive environment for pursuing an IT degree in Kazakhstan and broader international contexts.

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