The Challenges Faced by Doctoral Student Mothers in the Education Sector: Artificial Neural Network Modeling

Globally, reforms in doctoral education aim to address social inequalities, particularly gender disparities, to democratise knowledge access. However, little is known about the experiences of women doctoral candidates who are mothers in STEM fields in China, where the gender gap has notably narrowed since the 1980s. This study focuses on the challenges faced by these academic mothers, whose time and energy are divided among academic, familial and professional commitments. Through in-depth investigations and questionnaires with nine doctoral student mothers, the paper explores their motivations for pursuing doctoral degrees amid diverse responsibilities. An artificial neural network (ANN) model further analyes the complex relationships among various influencing factors. The findings reveal that these women are motivated not only by external vocational factors but also by personal aspirations for self-actualisation and academic growth. By effectively integrating their multiple identities, they cultivate a positive academic identity and experience personal development within specific societal contexts. The insights from this research shed light on the challenges and strategies employed by higher education professionals in maintaining a sustainable balance among their roles. These results have important implications for policy-makers and academic institutions striving to create more supportive and inclusive environments in the higher education sector.