Real time development of auto scoring essay models for custom created prompts

A system for dynamic composite machine learning model selection, the system comprising:

• a memory comprising:
• a content library database containing a plurality of prompts and scoring data associated with each of the plurality of prompts;
• and a model database comprising a plurality of machine learning models for automated scoring of received user responses;
• and
• at least one processor configured to:
• receive a first plurality of responses received from a plurality of users in response to providing of a prompt;
• identify rules relevant to the received first plurality of responses;
• select a first one of a plurality of machine learning models for scoring of the first plurality of responses according to the rules identified as relevant to the received plurality of responses;
• auto-generate scores for the first plurality of responses with the selected first one of the plurality of machine learning models;
• receive evaluation of the auto-generated scores;
• identify a set of machine learning models via the rules relevant to the received first plurality of responses;
• evaluate the efficacy of each of the set of machine learning models based on the received evaluation of the auto-generated scores;
• and
• identify the best performing machine learning model;
• and
• update the rules relevant to the received prompt to select the identified best performing machine learning models in response to receipt of a next plurality of responses.