<![CDATA[Flexibility, a cornerstone of online distance education, enables learners to access instructional content asynchronously from dispersed locations. However, this individualization of learning temporality and spatiality can obscure disparities in learners’ access to domestic resources, potentially exacerbating social inequities. This qualitative study examines how the flexibility inherent in Emergency Remote Teaching (ERT) shaped the academic experiences of students from diverse social groups at Jordanian universities during the COVID-19 pandemic. Grounded in a synthesis of capital theory and self-regulated learning (SRL) models, the investigation focuses on the intersection of socioeconomic status, gender, and regional background. Through thematic analysis of semi-structured interviews with 50 undergraduate and graduate students, four pivotal mediating factors were identified: spatial capital, temporal capital, temporal agency, and temporal intensity. Findings reveal that the capacity to benefit from ERT’s flexibility was unevenly distributed. Students with higher socioeconomic status and urban residency typically possessed superior spatial and temporal capital, allowing them to leverage asynchronous learning effectively. In contrast, students from rural areas, lower-income households, or those with significant familial or occupational obligations experienced flexibility as a source of stress and academic disadvantage, often due to deficient infrastructure, limited quiet study space, and constrained time. The study concludes that flexibility is not an inherent pedagogical good but a dimension that interacts with pre-existing inequalities. To foster inclusive flexibility, higher education institutions must move beyond a one-size-fits-all model by providing targeted SRL support, ensuring equitable access to essential digital and spatial resources, and adopting pedagogies sensitive to students’ divergent domestic contexts. This research underscores the urgent need to build more equitable and resilient digital learning ecosystems.]]>
