Many schools across the world, especially in developing regions, face a basic but often overlooked challenge: learners want to study programming, but the school infrastructure is not designed for modern computing education. Limited computers, unreliable connectivity, and the absence of licensed software create a gap between curriculum expectations and what teachers and learners can realistically achieve.
Open-source tools often become the only viable path forward. They provide accessible, reliable, and cost-free ways to teach programming and computational thinking, even in environments where technology resources are scarce. This talk explores how open-source software enables meaningful programming education in such low-resource settings, using practical examples from classroom situations and insights from ongoing research with teachers in Namibia.
The session will highlight the specific challenges encountered when teaching Python without enough machines, when internet access is intermittent, and when schools rely heavily on outdated hardware. It will also show how tools such as Linux distributions, Python’s ecosystem, and browser-based or offline notebooks make it possible for learners to write, run, and share code with only minimal resources. These examples demonstrate that high-quality programming education does not always require high-end infrastructure, what matters more is adaptability, tooling choice, and an open ecosystem.
The talk will also cover experiences gathered from teachers across different schools, focusing on the barriers they face when adopting open-source tools. Alongside these challenges, it will share creative strategies teachers have developed: planning offline lessons, integrating printed materials, running unplugged computing sessions, and gradually introducing Linux where appropriate.
The goal of this session is to introduce the wider Python community to a perspective that is rarely represented in global conferences: how open-source tools directly shape educational opportunities in environments where resources are limited.
