Pearson Education, Inc.

Andrew Gorman

William M Murray

Lee Becker

Scott Hellman

Peter Foltz

Alok Baikadi

Kyle D Habermehl

Mark Rosenstein

Jill Budden

Stephen Hopkins

Luis Manuel Oros

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.

Systems and methods for interface-based automated custom authored prompt evaluation

Systems and methods for interface-based machine learning model output customization

Systems and methods for automated evaluation model customization

Growing community of inventors

Bloomington, MN, United States of America

Andrew Gorman