8. A computer system for generating distractors for text-based multiple choice test (MCT) items, the computer system comprising: one or more computer processors, one or more computer-readable storage media, and program instructions stored on one or more of the computer-readable storage media, which when executed cause at least one of the one or more processors to perform a method comprising: receiving, by the first computer from a second computer over a network, in response to information entered into a user interface on the second computer, an MCT item stem and key; submitting, by the first computer, the stem to a Question Answering (QA) system, wherein a QA system is a computer system that, in response to a query, automatically generates a list of candidate answers to the query; in response to submitting the stem to the QA system, receiving, by the first computer, from the QA system a plurality of candidate answers; identifying, by the first computer, one or more incorrect answers in the plurality of candidate answers; extracting, by the first computer, textual features from the stem, wherein a textual feature is a term in the stem or a concept semantically related to a term in the stem; applying, by the first computer, a machine learning model to generate a set of semantic criteria associated with the extracted textual features; selecting, by the first computer, as distractors one or more of the incorrect candidate answers that satisfy the generated semantic criteria; creating, by the first computer, an MCT item that includes the stem, the key, and the distractors; and transmitting, by the first computer, the created MCT item via the network to the second computer.
8. A computer system for generating distractors for text-based multiple choice test (MCT) items, the computer system comprising: one or more computer processors, one or more computer-readable storage media, and program instructions stored on one or more of the computer-readable storage media, which when executed cause at least one of the one or more processors to perform a method comprising: receiving, by the first computer from a second computer over a network, in response to information entered into a user interface on the second computer, an MCT item stem and key; submitting, by the first computer, the stem to a Question Answering (QA) system, wherein a QA system is a computer system that, in response to a query, automatically generates a list of candidate answers to the query; in response to submitting the stem to the QA system, receiving, by the first computer, from the QA system a plurality of candidate answers; identifying, by the first computer, one or more incorrect answers in the plurality of candidate answers; extracting, by the first computer, textual features from the stem, wherein a textual feature is a term in the stem or a concept semantically related to a term in the stem; applying, by the first computer, a machine learning model to generate a set of semantic criteria associated with the extracted textual features; selecting, by the first computer, as distractors one or more of the incorrect candidate answers that satisfy the generated semantic criteria; creating, by the first computer, an MCT item that includes the stem, the key, and the distractors; and transmitting, by the first computer, the created MCT item via the network to the second computer. 11. A computer system in accordance to claim 8 , wherein identifying, by the first computer, incorrect answers comprises: identifying, by the first computer, a correct answer by comparing the plurality of candidate answers with the key; and deleting, by the first computer, the correct answer from the plurality of candidate answers.