Revealing the United Nations sustainable development goals in international massive open online course (MOOC) content: text analysis based on machine learning

Purpose Based on the sustainable development goals (SDG) adopted by the United Nations in 2015, this study aims to analyse the content of selected massive open online courses (MOOCs) to reveal the distribution pattern of SDG implementation in online education. In addition, the impact of including SDG content on course popularity was explored. Design/methodology/approach The authors searched the descriptive texts of all courses on the three largest international MOOC platforms and used the OSDG 2.0 algorithm (an open-source tool that maps and connects activities to the UN SDGs by identifying SDG-relevant content in any text) to classify these descriptive texts. Combined with the number of enrolments and course category classifications, this study analysed the current presence of sustainable development in MOOCs, based on text analyses. Findings The findings revealed the distribution of SDGs among the three most influential MOOC platforms and different categories, the most relevant keywords to SDGs, and the most often referred topics. The results indicated that the enrolment number of MOOCs labelled with SDGs is generally lower than those without SDG labels and the situation varies among course categories. Originality/value This study verified the general pattern of distribution of different SDGs in education for sustainable development (ESD) of MOOCs, with the breadth and depth of the MOOC content analysis surpassing existing research. Based on these findings, MOOC platforms should further increase attention to ESD on their websites. This study also verified the feasibility of using machine learning methods to quantitatively evaluate the sustainable development context of text within the framework of the SDGs.