Patents Assigned to CIVITAS LEARNING, INC.
  • Publication number: 20220180218
    Abstract: An automation analytics system and method for building analytical models for an education application uses data-availability segments of students, which are clustered into segment clusters, to create the analytical models for the segment clusters using a machine learning process. The analytical models can be used to identify at least at least actionable insights.
    Type: Application
    Filed: August 12, 2021
    Publication date: June 9, 2022
    Applicant: Civitas Learning, Inc.
    Inventors: David KIL, Jorgen HARMSE, Michael JAUCH, Kristen HUNTER, David PATSCHKE, Stephen D. HILDERBRAND, Laura MALCOM, Darren RHEA
  • Publication number: 20200057945
    Abstract: A flexible persistence modeling system and method for building flexible persistence models for education institutions using a Markov model based on units of academic progress of a non-traditional learning program of an education institution. The Markov model is used to quantify transitions of students between the states as parameters of state transitions so that features from the Markov model with the parameters of state transitions can be extracted that are related to the non-traditional learning program of the education institution using defined flexible persistence. The extracted features can then be used to build at least one flexible persistence model for different segments of the students.
    Type: Application
    Filed: October 28, 2019
    Publication date: February 20, 2020
    Applicant: CIVITAS LEARNING, INC.
    Inventors: David Kil, Edwin Woo, Clayton Gallaway, Jacob Rios
  • Patent number: 10460245
    Abstract: A flexible persistence modeling system and method for building flexible persistence models for education institutions using a Markov model based on units of academic progress of a non-traditional learning program of an education institution. The Markov model is used to quantify transitions of students between the states as parameters of state transitions so that features from the Markov model with the parameters of state transitions can be extracted that are related to the non-traditional learning program of the education institution using defined flexible persistence. The extracted features can then be used to build at least one flexible persistence model for different segments of the students.
    Type: Grant
    Filed: September 3, 2016
    Date of Patent: October 29, 2019
    Assignee: CIVITAS LEARNING, INC.
    Inventors: David Kil, Edwin Woo, Clayton Gallaway, Jacob Rios
  • Publication number: 20170256172
    Abstract: Student data-to-insight-to-action-to-learning analytics system and method use an evidence-based action knowledge database to compute student success predictions, student engagement predictions, and student impact predictions to interventions. The evidence-based action knowledge database is updated by executing a multi-tier impact analysis on impact results of applied interventions. The multi-tier impact analysis includes using changes in key performance indicators (KPIs) for pilot students after each applied intervention and dynamic matching of the pilot students exposed to the appropriate interventions to other students who were not exposed to the appropriate interventions.
    Type: Application
    Filed: March 6, 2017
    Publication date: September 7, 2017
    Applicant: CIVITAS LEARNING, INC.
    Inventors: David H. Kil, Kyle Derr, Mark Whitfield, Grace Eads, John M. Daly, Clayton Gallaway, Jorgen Harmse, Daya Chinthana Wimalasuriya
  • Publication number: 20170068895
    Abstract: A flexible persistence modeling system and method for building flexible persistence models for education institutions using a Markov model based on units of academic progress of a non-traditional learning program of an education institution. The Markov model is used to quantify transitions of students between the states as parameters of state transitions so that features from the Markov model with the parameters of state transitions can be extracted that are related to the non-traditional learning program of the education institution using defined flexible persistence. The extracted features can then be used to build at least one flexible persistence model for different segments of the students.
    Type: Application
    Filed: September 3, 2016
    Publication date: March 9, 2017
    Applicant: CIVITAS LEARNING, INC.
    Inventors: David Kil, Edwin Woo, Clayton Gallaway, Jacob Rios
  • Publication number: 20150193699
    Abstract: An automation analytics system and method for building analytical models for an education application uses data-availability segments of students, which are clustered into segment clusters, to create the analytical models for the segment clusters using a machine learning process. The analytical models can be used to identify at least at least actionable insights.
    Type: Application
    Filed: January 8, 2015
    Publication date: July 9, 2015
    Applicant: CIVITAS LEARNING, INC.
    Inventors: David Kil, Jorgen Harmse, Michael Jauch, Kristen Hunter, David Patschke, Stephen D. Hilderbrand, Laura Malcolm, Darren Rhea