From Burden to Breakthrough: How AI is Transforming OER for African Academics

Across Africa, universities are exploring how digital technologies can strengthen teaching and learning. Two developments stand out: the rapid rise of artificial intelligence (AI), and the continued growth of Open Educational Resources (OER) – freely available materials that can be adapted and shared. While both hold enormous promise, OER adoption has often fallen short of expectations. A key reason is practical: working with OER can be time-consuming. A new AI and OER Tutorial developed by OER Africa addresses this challenge directly, showing how AI can simplify and accelerate the OER workflow for academics.

The tutorial can be accessed here: https://www.oerafrica.org/communication/oer-and-ai/

OER can offer clear benefits. They reduce costs of educational materials for students, allow educators to tailor materials to local contexts, and support collaboration across institutions. For African academics, the ability to adapt content – whether through language, examples, or case studies – is particularly valuable. Yet the process of working with OER has traditionally been labour-intensive. Academics must search across multiple platforms, verify licences, evaluate quality, adapt materials, and ensure correct attribution. For those managing already demanding workloads, this often turns OER from a promising idea into a practical challenge.

The tutorial makes a compelling case that AI may help to remove many of these barriers. Tools like ChatGPT can assist with finding relevant resources, summarizing and evaluating content, adapting materials for specific contexts, and even generating correct Creative Commons attributions. Importantly, AI does not replace academic judgement; rather, it supports it by reducing the time spent on routine tasks. This allows educators to focus more on teaching and less on process.

This tutorial has a practical focus. Using step-by-step examples, it shows how AI can be integrated into real academic workflows, from identifying suitable OER, to evaluating and adapting them, to ensuring proper attribution. In doing so, it demystifies both AI and open education, offering a clear and accessible entry point for academics who may be new to either.

Perhaps the most significant insight is that AI has the potential to make the traditional OER lifecycle – searching, evaluating, adapting, and attributing – more efficient by supporting each stage of the process. What was once labour intensive can now become far more manageable. This suggests that the slow uptake of OER may not have been due to lack of interest, but rather the practical effort required to use them effectively. Empirical studies support this, highlighting barriers such as difficulty in discovering relevant resources due to poor metadata and fragmented repositories, challenges in evaluating quality and alignment, and the time and effort required to adapt materials for specific contexts. These factors contribute to a workflow that is often perceived as complex and time-consuming, reducing the likelihood of sustained use (Tlili et al., 2020).

The tutorial also invites reflection on both the limitations of using AI and the evolving relationship between AI and open education. As AI platforms increasingly draw on openly available knowledge, questions arise about how openness can support more transparent, collaborative, and locally relevant forms of knowledge creation. African academics have an important role to play in shaping this future, by advocating for ethical AI practices such as transparency, attribution, and openness, while shaping institutional policies and research agendas that ensure AI strengthens rather than extracts from African knowledge ecosystems.

Educators are encouraged to take the tutorial and consider how these tools might be integrated into their own practice.