Systems and methods for assessment item credit assignment based on predictive modelling

A system comprising:

• at least one processor;
• and
• at least one memory device configured to store computer-readable instructions which, when executed, cause the at least one processor to:
• receive a request from an external server;
• analyze the request to identify a user and a plurality of assessment items corresponding to a digital assessment;
• retrieve a machine learning model definition based on the request;
• retrieve first feature data based on the user, the assessment item, and the machine learning model definition;
• execute a machine learning model corresponding to the machine learning model definition to process at least the first feature data to determine a plurality of correct first attempt probabilities for the user for the plurality of assessment items, wherein each of the plurality of correct first attempt probabilities represents a respective probability that a corresponding response submitted by the user to a corresponding assessment item of the plurality of assessment items will be correct;
• identify a subset of the plurality of correct first attempt probabilities having values exceeding a predetermined threshold;
• and
• cause credit to automatically be recorded for the user for a subset of the plurality of assessment items corresponding to the subset of the plurality of correct first attempt probabilities.

A method comprising:

• receiving, with at least one computer processor, a request from an external server;
• analyzing, with the at least one computer processor, the request to identify a user and a plurality of assessment items corresponding to a digital assessment;
• retrieving, with the at least one computer processor, a machine learning model definition based on the request;
• retrieving, with the at least one computer processor, first feature data based on the user, the assessment item, and the machine learning model definition;
• executing, with the at least one computer processor, a machine learning model corresponding to the machine learning model definition to process at least the first feature data to determine a plurality of correct first attempt probabilities for the user for the plurality of assessment items, wherein each of the plurality of correct first attempt probabilities represents a respective probability that a corresponding response submitted by the user to a corresponding assessment item of the plurality of assessment items will be correct;
• identifying, with the at least one computer processor, a subset of the plurality of correct first attempt probabilities having values exceeding a predetermined threshold;
• and
• sending, with the at least one computer processor to the external server, a recommendation to automatically assign credit for the user for a subset of the plurality of assessment items corresponding to the subset of the plurality of correct first attempt probabilities.