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
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
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
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
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
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