Abstract: Systems and methods are disclosed for automatically scoring a constructed response using a neural network. In embodiments, a constructed response received by a processing system may be processed to divide the constructed response into multiple series of word tokens, wherein each word token includes a sequence of characters. The constructed response may be further processed to correct one or more spelling errors. The word tokens may be encoded to generate representation vectors for the constructed response. A set of nonlinear operations may be applied to the plurality of representation vectors in a neural network to generate a single vector output. A set of predetermined network weights may be applied to the vector output of the neural network to generate a scalar output for scoring the constructed response.

Abstract: Computer-implemented systems and methods are described herein for automatically generating questions from text. Text including one or more sentences is received. A sentence, comprising a predicate and one or more arguments associated with the predicate, is parsed from the text. Semantic role labels are assigned to the one or more arguments associated with the predicate. One or more questions are automatically generated relating to the predicate based on the assigned semantic role labels. Each answer to the generated questions is one of the one or more arguments associated with the predicate.