Towards an Integrated Land Administration Curriculum: leveraging the power of AI to synthesize international and regional guidelines

Abstract

We present a methodology for interrogating and synthesizing published international and regional guidelines relevant for the development of curricula on land administration and governance. Several guidelines have been published by different international and regional bodies. With so many informative resources available, curriculum developers may struggle to determine which ones to use most effectively. Leveraging the power of the latest frontier technology, generative artificial intelligence (GenAI), we use prompt engineering to derive summaries of five such guideline documents, present a synthesized set of guidelines, suggest graduate attributes, a three-year undergraduate curriculum (complete with course outlines and learning outcomes), possible degree names, practical teaching guidelines, entrance requirements, and career pathways. The models we interrogate are the free versions of ChatGPT, Copilot, NotebookLM, Claude.ai, and DeepSeek. The results are all similar but different. There are some cross-cutting themes and some unique contributions. Each model has its own strengths and peculiarities. We have shown that it is possible, with careful prompting, to use GenAI models to help curriculum developers make sense of multiple guidelines and propose a curriculum outline. Two of the guidelines we used have a strong African focus – curriculum developers from other contexts may supplement these with guidelines relevant to their context. We note that GenAI is error-prone and caution that human oversight is essential to review, modify, and approve its outputs. Our methodology should be seen as a first step.