Systems and methods for automated machine learning model training quality control

• Main Authors: Habermehl, Kyle, Hellman, Scott, Baikadi, Alok, Foltz, Peter, Rosenstein, Mark, Hopkins, Stephen, Becker, Lee, Budden, Jill
• Format: Patent
• Language: English
• Published: 16.01.2024
• Subjects: ADVERTISING; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND,DEAF OR MUTE; CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; CRYPTOGRAPHY; DIAGRAMS; DISPLAY; EDUCATION; EDUCATIONAL OR DEMONSTRATION APPLIANCES; ELECTRIC DIGITAL DATA PROCESSING; GLOBES; PHYSICS; PLANETARIA; SEALS

Systems and methods for automated custom training of a scoring model are disclosed herein. The method include: receiving a plurality of responses received from a plurality of students in response to providing of a prompt; identifying an evaluation model relevant to the provided prompt, which evaluation model can be a machine learning model trained to output a score relevant to at least portions of a response; generating a training indicator that provides a graphical depiction of the degree to which the identified evaluation model is trained; determining a training status of the model; receiving at least one evaluation input when the model is identified as insufficiently trained; updating training of the evaluation model based on the at least one received evaluation input; and controlling the training indicator to reflect the degree to which the evaluation model is trained subsequent to the updating of the training of the evaluation model.