Educational technology (EdTech) solutions have shown promise for disseminating educational opportunities to last-mile learners, particularly in the Global South. Low-infrastructure EdTech as a digital learning resource is especially critical to understand in remote contexts where educational opportunities and resources are limited. Our work investigated insights from 81 learners who engaged with a remote course that provided engineering education through radios and mobile phones in rural Uganda. Findings revealed that the course facilitated goal-driven and practical motivations in safe, adaptable environments. Our work goes beyond the idea that low-infrastructure EdTech can easily facilitate learning, highlighting diverse learner experiences navigating radio and phone use and presenting novel findings on community skepticism towards the course. Our research extends the EdTech and HCI literature by bringing light to the underrepresented voices of last-mile learners, sharing their insights on interacting with low-infrastructure EdTech, and how these insights can guide the design of contextually aligned EdTech.

Most learners worldwide are multilingual, yet implementing multilingual education remains challenging in practice. EdTech offers an opportunity to bridge this gap and expand access for linguistically diverse learners. We conducted a quasi-experiment in Uganda with 2,931 participants enrolled in a non-formal radio- and mobile-based engineering course, where learners self-selected instruction in Leb Lango (a local language), English, or a Hybrid option combining both languages. The Leb Lango version of the course was used disproportionately by learners from rural areas, those with less formal education, and those with lower prior knowledge, broadening participation among disadvantaged learners. Moreover, the availability of Leb Lango instruction was associated with higher active participation, even among learners who registered for English instruction. Although Leb Lango learners began with lower performance, they demonstrated faster learning gains and achieved comparable final examination outcomes to English and Hybrid learners. These results suggest that providing local language options to learners is an effective way to make EdTech more accessible.

Generative artificial intelligence (GenAI) is rapidly entering K-12 classrooms worldwide, initiating urgent debates about its potential to either reduce or exacerbate educational inequalities. Drawing on interviews with 30 K-12 teachers across the United States, South Africa, and Taiwan, this study examines how teachers navigate this GenAI tension around educational equalities. We found teachers actively framed GenAI education as an equality-oriented practice: they used it to alleviate pre-existing inequalities while simultaneously working to prevent new inequalities from emerging. Despite these efforts, teachers confronted persistent systemic barriers, i.e., unequal infrastructure, insufficient professional training, and restrictive social norms, that individual initiative alone could not overcome. Teachers thus articulated normative visions for more inclusive GenAI education. By centering teachers’ practices, constraints, and future envisions, this study contributes a global account of how GenAI education is being integrated into K-12 contexts and highlights what is required to make its adoption genuinely equal.