Education for sustainable development (ESD) is a growing research field, particularly over the last decade. Measuring the level of ESD that is currently embedded in curricula is useful for planning the further implementation of sustainability-related teaching. The Sustainable Development Goals (SDGs) are a useful benchmark for sustainability topics and so this paper follows a methodology in which a keyword scanning tool was created to quantify the level of SDG coverage within a list of learning outcomes for a module. The aim of the research is to further develop this methodology and compare the results from the keyword tool with results from a survey of the academic staff who deliver the modules. SDG-related keyword lists were collected from multiple sources for a meta-analysis, examining the performance of various lists. These lists were then compiled into one list of over 12,000 SDG keywords and a team of reviewers conducted a critical analysis on the relevancy of the context in which the keywords were found when scanned. This process reduced the list to 222 “crucial keywords” and gave the keywords a relevancy label based on the STARS definitions, the sustainability tracking assessment and rating system. Finally, ChatGPT was also investigated as a method of enriching the critically analysed list with contextually relevant synonyms. A survey was carried out within the College of Science and Engineering at the University of Galway. It asked staff to rate the level of SDG coverage within their own modules, in their own opinion. This gave results which could be compared with the keyword scanning tool. The findings show success in improving the accuracy of the SDG keywords. ChatGPT added synonyms to the crucial keywords identified and this list was the most accurate out of all keyword lists used in the study. Using these keywords and the modules that staff rated in the survey, a correlation was found in the SDG trend.

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