DEVELOPMENT OF A NEURAL NETWORK-BASED INCLUSION SIMULATION MODEL

VARIABLES THAT MIGHT LEAD TO WIDER ADOPTION OF INTEGRATED PRESCHOOL PROGRAMS INCLUDE EXPANSION OF THE WAY IN WHICH WE MAKE DECISIONS AND THE MANNER IN WHICH RELATED SERVICES ARE DELIVERED. EVALUATION EFFORTS SHOULD BE EXPANDED TO INCLUDE THE IMPACT OF VARYING METHODS OF INTEGRATION. THIS PROJECT PROPOSES THE DEVELOPMENT OF A COMPUTER INCLUSION SIMULATION MODEL THROUGH THE UTILIZATION OF NEURAL NET-BASED TECHNOLOGY. PHASE I WILL EVALUATE THE FEASIBILITY OF PROVIDING TECHNOLOGY THAT FOSTERS INCLUSIVE PRESCHOOL PRACTICES THROUGH UTILIZATION OF THE ABILITY OF NEURAL NETWORKS TO RECOGNIZE PATTERNS AND INTERACTIONS AMONG VARIABLES. THE PROPOSED INCLUSION SIMULATION MODEL (ISM), BUILT BY ENTERING DEPENDENT VARIABLES, INDEPENDENT VARIABLES, AND OTHER KNOWN CONDITIONS FROM RELEVANT RESEARCH WILL BE EVALUATED BY OBSERVING RESPONSES TO INCREMENTAL CHANGES IN ISM INPUTS AND BY TESTING ITS ABILITY TO PREDICT RESEARCH FINDINGS. THE SOFTWARE PACKAGE PROPOSED FOR DEVELOPMENT WILL BE USEFUL FOR THE TRANSLATION AND INTEGRATION OF ALL THE VARIABLES (VALIDATED INCLUSION STRATEGIES) IDENTIFIED IN THE LITERATURE INTO A FRAMEWORK THAT PROVIDES BOTH PROCESS ANDD OUTCOME GUIDANCE.