Female Students’ Perceptions of Artificial Intelligence and STEM in Tanzania: Insights from an AI Awareness Workshop
Female Students’ Perceptions of Artificial Intelligence
Keywords:
Artificial intelligence, STEM Education, Female Students, AI Literacy, Women in STEM, Technology Perception, Digital Inclusion, TanzaniaAbstract
The underrepresentation of females in Artificial Intelligence (AI) remains a global concern, with implications for both equitable participation and the inclusivity of AI-driven solutions. While efforts to promote gender equality in Science, Technology, Engineering, and Mathematics (STEM) have increased, limited research examines how female students perceive AI and their participation in it, particularly in developing-country contexts such as Tanzania. In Tanzania, limited exposure to emerging technologies, constrained access to digital resources, and persistent gendered perceptions continue to restrict female students’ participation in STEM and AI pathways. This study investigates the perceptions, awareness, and participation of female secondary school and university students in AI. Using a qualitative research approach, data were collected during an AI awareness and sensitisation workshop on Artificial Intelligence concepts, applications, and careers organised under the Girls in AI initiative by DarasaTech in partnership with AI4D Labs. The workshop involved presentations, group activities, and focus group discussions. Data from these interactions were analysed using an open coding approach to identify key themes. Findings indicate that exposure to AI concepts significantly improved participants’ understanding of AI beyond common misconceptions, such as associating it solely with robots, to recognising its application in everyday life and community problem-solving. The study also found a generally positive attitude toward technology and increased interest in pursuing STEM-related careers. However, several barriers to participation were identified, including low self-confidence in science subjects, limited access to technological resources, insufficient institutional support, and a lack of female role models. The study highlights the need for early integration of STEM education, increased access to learning resources, and targeted mentorship programs to support female participation in AI. These findings provide valuable insights for educators and policymakers seeking to foster inclusive and contextually relevant AI ecosystems in Tanzania and similar settings
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