Patents by Inventor Stephan Peter Guttman

Stephan Peter Guttman has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Comprehension Modeling and AI-Sourced Student Content Recommendations
    Publication number: 20230419849
    Abstract: A system generates a training dataset based on historical consumption information and historical comprehension information of historical users, and uses the training dataset to train a machine-learned model to predict a measure of comprehension for a user consuming educational content. The system applies the machine-learned model to behaviors of a target user to determine a target measure of comprehension for target educational content, identifies one or more characteristics of the target educational content, applies a content identification model to identify supplemental educational content, and generates an educational content interface to present the supplemental educational content to the target user. In some examples, the system trains the machine-learned model to predict a collective measure of comprehension for a set of users consuming educational content, identifies a set of supplemental educational content, and generates a teacher interface to present the set of supplemental educational content.
    Type: Application
    Filed: June 22, 2023
    Publication date: December 28, 2023
    Inventors: Stephan Peter Guttman, Joel Marc Podolny, Gregory N. Christie, Pooja Brown
  • CLASS-WIDE COMPREHENSION MODELING AND AI-SOURCED TEACHER CONTENT RECOMMENDATIONS
    Publication number: 20230419848
    Abstract: A system generates a training dataset based on historical consumption information and historical comprehension information of historical users, and uses the training dataset to train a machine-learned model to predict a measure of comprehension for a user consuming educational content. The system applies the machine-learned model to behaviors of a target user to determine a target measure of comprehension for target educational content, identifies one or more characteristics of the target educational content, applies a content identification model to identify supplemental educational content, and generates an educational content interface to present the supplemental educational content to the target user. In some examples, the system trains the machine-learned model to predict a collective measure of comprehension for a set of users consuming educational content, identifies a set of supplemental educational content, and generates a teacher interface to present the set of supplemental educational content.
    Type: Application
    Filed: June 22, 2023
    Publication date: December 28, 2023
    Inventors: Stephan Peter Guttman, Joel Marc Podolny, Gregory N. Christie, Pooja Brown