It was designed to read and solve the kind of word problems found in high school algebra books.
Within Project MAC at MIT, the STUDENT system was an early example of a question answering software, which uniquely involved natural language processing and symbolic programming.
[2] Other early attempts for solving algebra story problems were realized with 1960s hardware and software as well: for example, the Philips, Baseball and Synthex systems.
[3] STUDENT accepts an algebra story written in the English language as input, and generates a number as output.
More powerful techniques for natural language processing, such as machine learning, came into use later as hardware grew more capable, and gained popularity over simpler rule-based systems.