DISTRACTOR GENERATION FOR MULTIPLE-CHOICE QUESTIONS

In one embodiment, a computer-implemented method comprises, using an application server computer that is communicatively coupled to a database via a telecommunication network, the database comprising a digitally stored relational table schema storing a plurality of term sets, each of the term sets comprising a plurality of terms, the application server computer hosting an application program programmed with a plurality of distractor selection algorithms; executing each of the distractor algorithms to access a particular term from among the plurality of the terms as an input and to generate a plurality of corresponding first interim sets of candidate distractor terms, for the particular term, as an output; executing a first inference stage of a within-set machine learning model over the same particular term as input to generate classification output comprising a second interim set of candidate distractor terms, for the particular term; executing a second inference stage of a cross-algorithm ranking machine learning model over the plurality of corresponding first interim sets and the second interim set to generate a top-N set of best candidate distractors; digitally storing the top-N set of best candidate distractors in a table of the relational table schema in association with the particular term; formatting the top-N set of best candidate distractors with the particular term as a multiple-choice question set and transmitting, to a client computer, presentation instructions which when rendered using the client computer cause presenting a user interface comprising the particular term as a prompt and the top-N set of best candidate distractors as available answers.