Optimizing ELL in Low-Resource Environments through Cost- and Constraint-Sensitive Digital Strategies: A Cross-Sectional Survey with an Illustrative YouTube–WhatsApp Comparison in Sudanese Universities

Abstract

Digital English language learning experiences are defined not just by pedagogical considerations, but also by unreliable internet connections, data prices, power outages, and small periods of internet availability. This work both profiles these constraints in two Sudanese universities using the cross-sectional descriptive survey research design, and pilots the Resilience-Adjusted Cost-to-Learn (RACL) framework as a decision support tool for guided learner platform selection in resource-constrained environments. Respondent-normalized data from 42 participants were aggregated to produce estimates of constraint pressure (CONS) and associated self-reported operational friction. Our convenience sample experienced significant overall constraint (CONS = 0.76, SD = 0.09), with connection strength stabilization and infrastructure reliability yielding the largest pressures. Due to the instrument's failure to collect respondent-level time-series logging of platform use, the comparison between YouTube and WhatsApp presented here should be considered an illustrative proof of concept for the framework instead of a quantified treatment effect. Interpreted this way, we expect low-bandwidth messaging applications to have greater longevity under high constraint conditions; high-bandwidth applications should outperform as caching, subtitles, and internet window durations lengthen. Similarly, the learning outcome subcomponent of RACL is self-perception of learning rather than an objectively measured language proficiency gain, and cost is operational burden rather than device telemetry. The study offers a transparent and context-sensitive framework for constraint-aware instructional planning in ELL environments affected by digital inequality.