The gender-gap in the fields of science, technology, engineering, and mathematics (STEM) is an impediment to the success of digitized education. The causal factors of this gap have remained a matter of speculation. This study focuses on the STEM gender gap in online learning, seeking to identify causal factors through an innovative fuzzy-set qualitative comparative analysis (fsQCA) that is integrated with sentiment analysis in the Asian context. Findings from the empirical results reveal two pathways to explain STEM gender inequality in the context of online classes. The study advances knowledge by providing insight into the causal factors that contribute to the existing gender gap and by disclosing what demotivates STEM female students in an e-learning environment. The findings will be helpful to practitioners seeking to address digital exclusion issues like the gender inequality in online learning platforms.