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Paper short abstract

Multiple (successful and unsuccessful) experiments with AI and OER in India and the UK highlight constraints from students' study practises and access to technology, university policy and resources. We provide reflections and suggestions that might further the OER-AI agenda.

Paper long abstract

The Dubai Declaration emphasises context-sensitive integration of AI in open education. This is an important aim, but faces practical constraints. We reflect on our experiments developing and using open educational resources (OERs) and multiple experiments developing large language model (LLM) based systems using OERs in our economics and marketing courses in India and the UK.

We have been motivated to enable free access for students to quality, critical materials, including for students in rich economies, but very low-income households. Some of those projects (e.g., CORE Econ) have been very successful, others (the marketing project) not so.

We draw on our experiences with multiple projects for reflection and suggestions across three dimensions: 1) students' learning risks (ChatGPT habituation, unsocial learning, uneven access to relevant technology); 2) university resource constraints (content development costs, AI tool evaluation skills and costs); and 3) university policy constraints (IT policies that restrict educators' use of tools, reward systems that de-incentivise development of OERs and open AI/ML tools).

Our experiments forced us to interrogate our educational and technological choices and their underlying assumptions.

They highlight the inadequacy of "one-size-fits-all" AI systems and the necessity of community-engaged development processes. But, they also highlight that without some broader support and coordination, of the type the 2019 and 2024 declarations imagine, such as through the development of open, adaptable platforms, the resource requirements of doing this make it practically impossible.

We take our experience to make a series of suggestions for practically advancing OER-AI integration that furthers the OER agenda.

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Paper short abstract

Drawing on a practice-based case from a science and arts education center, this paper explores how artificial intelligence and open educational resources can be used to design equitable and sustainability-oriented learning environments.

Paper long abstract

Educational systems are increasingly challenged to respond to global crises by reimagining learning futures that prioritize equity, sustainability, and social responsibility. In this context, the intersection of artificial intelligence (AI) and open educational resources (OER) offers significant potential to transform learning environments, while also raising important pedagogical and ethical questions.

This paper presents a practice-based case from a Science and Arts Center (BİLSEM) in Türkiye, focusing on a Sustainable Development Goals–oriented entrepreneurship workshop designed for gifted learners. Grounded in UNESCO’s Green Curriculum Guidance, Green School Quality Standards, and Global Citizenship Education (GCED) principles, the program integrates AI-supported learning tools and openly licensed educational resources to address themes of climate change and sustainability.

Within the workshop, AI is positioned not merely as a technological innovation but as a pedagogical support that enhances personalization, accessibility, and learner agency. OER are used to promote equitable access to knowledge, adaptability to local contexts, and collaborative knowledge production. Students engage in problem-based learning scenarios, develop sustainability-oriented entrepreneurial ideas, and translate these ideas into prototypes, thereby connecting learning with real-world action.

The paper discusses how this integrated approach contributes to students’ self-efficacy, global citizenship awareness, and sense of social and environmental responsibility. It also reflects on emerging pedagogical tensions related to teacher roles, ethical use of AI, and the balance between automation and human judgment in learning design.

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Paper short abstract

Tamil Nadu’s digital learning platform showed promise with its universal design and contextualised content promoting student inclusivity. However, program implementation faced challenges due to inadequate infrastructure, lack of funds, multi-stakeholder coordination, and lack of robust evidence.

Paper long abstract

The integration of AI-driven open educational resources (OER) in public schools offers significant potential for equitable education, especially in multilingual and low-resource contexts. This paper presents a case study from Tamil Nadu, India, where an open-source digital language learning platform with voice recognition technology was launched in 2023 to improve language outcomes for middle-school students. The digital platform was built using content from a Creative Commons-Licensed platform which was contextualised and customised for the state with the help of external technology partners. The platform design applied Universal Design for Learning (UDL) principles which included multilingual instructions, audio prompts, and screen readers, enabling students with minimal literacy to navigate the platform confidently and independently, promoting a safe and inclusive learning space. However, scaling up this program to more schools exposed systemic challenges which included inadequate institutional infrastructure, server overloads, and governance complexities in multi stakeholder collaboration, especially conflicts between local content creators and technology experts. Lack of a dedicated program budget and limited evidence of measurable learning outcomes further constrained sustainability. Introducing AI-driven personalisation raised more fiscal and ethical concerns, including the increase in financial investment towards upgrading institutional infrastructure and privacy risks related to the collection and storage of large-scale individual student data. This paper explores how AI-enhanced open-source contextualised digital content hosted by state institutions can democratise learning, while acknowledging that the sustainability of such programs is dependent on political will for long-term financial investment and resource allocation, coordinated governance, and rigorous learning-outcome evidence in developing countries.

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Paper short abstract

Sub-Saharan Africa faces poor education, unemployment, skills gaps despite enrollment gains. AI multiplies development via adaptive tools, job matching, inclusive tech—but risks divides, bias. The Study finds conditional boosts; AI needs human-centered policies, infrastructure, co-design for equity.

Paper long abstract

Sub-Saharan Africa faces enduring challenges in education, youth employability, and social inclusion, marked by low learning outcomes, skills mismatches, unemployment, and persistent inequalities despite improved school enrolment. Artificial Intelligence (AI) emerges as a potential development multiplier, amplifying existing investments by enhancing productivity, personalizing education through adaptive learning and tutoring systems, improving job matching and skills forecasting, and supporting marginalized groups via assistive technologies and inclusive services. However, empirical evidence on AI's effectiveness in these domains remains fragmented, often lacking contextual sensitivity to SSA's socio-economic realities, institutional constraints, and informal systems, with risks of exacerbating digital divides, algorithmic bias, and inequalities. Guided by human capital theory, the capability approach, and sociotechnical systems theory, this qualitative study—integrating systematic literature review and phenomenological analysis—examines how AI functions as a multiplier, shaped by contextual factors like infrastructure, literacy, and governance. Findings indicate AI enhances efficiency, reach, personalization, and system-level transformation, yet its benefits are conditional on supportive conditions; weak enabling environments can reinforce exclusion. Ultimately, AI holds promise for inclusive development but requires human-centred policies, investments in digital infrastructure and literacy, strengthened institutional capacity, contextual co-design with local stakeholders, and integration as a complement to human investments, prioritizing equity, ethics, and sustainable capability expansion.