CLASS Cognitive Load Adaptive Software System. A complex software system and method for managing the continuous improvement of human learning based on evidence-based strategies arising from Cognitive Load Theory.

摘要

#$%^&*AU2018236887A120190418.pdf#####Patent Claim by David Isaacson, 2018 Title: CLASS Cognitive Load Adaptive Software System ABSTRACT CLASS (Cognitive Load Adaptive Software System) is a cloud-based, databasedriven, mediative-adaptive software system with password-protected access to persona-based interface and dashboards for Administrators, Teachers and Students. The purpose of CLASS is to support educators in the rapid analysis of learning programs and learner needs, then use this information to implement interventions for the continuous improvement of learning design based on strategies arising from cognitive load theory. The learning design in programs or courses may be strengthened based on: a) a standard derived from cognitive load theory without reference to learners, or; b) a standard derived from cognitive load theory with reference to learners' prior knowledge and heutagogical (self-determined learning) capabilities. A central database serves as a repository for evidence-based research information to support teachers in devising learning interventions that are implemented over time in cyclical iterations, thereby facilitating incremental, continuous improvement. The CLASS system is fully integrated across all functionalities (See DIAGRAM 1), contains a dynamically-updateable knowledge database, contains all online forms, templates and interfaces for creating, implementing and monitoring learning interventions, as well as the capability to generate visualised reports at multiple levels (learner, groups, departments, and institutions) via persona-based interfaces. CLASS is not limited to these functions and may be integrated with other systems via LTI (Learning Tools Interoperability) or other software integration protocols. Patent Claim. David Isaacson Title: CLASS Cognitive Load Adaptive Software System CLASS © David Isaacson 2018 All rights reservedPatent Claim by David Isaacson, 2018 Title: CLASS Cognitive Load Adaptive Software System 2. The best method of performing this invention is through the use of cloud-based, database-driven software as described in Description documents Point 1-10 (submitted as part of this application) and illustrated by the functional diagram, (DIAGRAM 1) below (submitted as part of this application): CLASS Cognitive Load Adaptive Software System A mediative-adaptive software system for the continuous improvement of learning design informed by the principles arising from cognitive load theory and heutagogy within a "double-loop" evaluation architecture 12. LTI 1. Administrator global Functions Functionality, A au ~Systems 4. Dynamic Database Integration Knowledge base of evidence-based practices 2. Interface -Teacher -- arising from cognitive load theory - earn Dashboard 4 Information for populating questinnaires/ Dashboard rating forms for evaluating a) program and b) individual learners Recommender system/database search function 6. Learner self-analysis questionnaires/rating s. Questionnaires/ """" •Forms, templates and funcrtions for setting, statements based on cognitive load theory rating statements 4* -= - - implementing and tracking interventions and heutagogical principles; system (course and student) ("nodes of e xpertise") functionality for in-process self-rating of S capability and longitudinal intervention cognitive load tracking/monitoring .0 407. System-generated visualised 11. Evaluation data stored in 40 41,reports on alignment of program database for future reference, o with a) evidence-based principles aayi n aamnnitr and ) idivdualleaer eed and intra- institutional analysis 8. System "recommender" function provides possible 9. Teacher ("mediator") formulates an evidence-based interventions to individual plan (IP) based an 10. Learner is tested on "nodes strengthen the learning program 're commender" to strengthen program of fluency' and result with regard to a) evidence-based for learner. "Node of fluency' activities recorded; Learner completes principles and b) individual and review date is set. IP stored in Step 2 again. learner needs database for montioring and reporting Steps 1-11 represent an analysis/improvement iteration for a) program, b) course, or both a) and b) j 6.VCLASS © David Isaacson 2018 All rights reserved DIAGRAM 1 Patent Claim. David Isaacson1 Title: CLASS Cognitive Load Adaptive Software System CLASS © David Isaacson 2018 All rights reserved