Coursera has introduced a new tool that helps universities identify courses on the company's online learning platform that most closely match their on-campus offerings. The CourseMatch solution uses machine learning and natural language processing to "automate the matching and minimize the need for human curation," according to a company blog post. CourseMatch can "ingest" on-campus course catalogs in more than 100 languages and map them to the most relevant Coursera courses in any of the languages available on the platform. It then returns up to five "matches" along with a relevance score, with higher scores given for stronger matches. Some 1,800 schools globally have already used the tool to match more than 2.6 million on-campus courses with Coursera equivalents, according to the blog post.

Since we launched the Coronavirus Response Initiative on March 12, more than 2,600 colleges and universities around the world have activated Coursera for Campus programs to take learning online and minimize student disruption. We're humbled by the global response and are working hard to be even more useful to universities who need to move online quickly. As universities go live using our offering, they urgently need an easy solution to help identify courses on Coursera that most closely match each course in their on-campus catalogues. Manual curation is too slow when it's to be done across thousands of universities and millions of on-campus courses, especially when faculty and staff are already stretched thin. Two weeks ago, the Data Science team at Coursera started developing a natural language processing solution to automate the matching and minimize the need for human curation.