Automation Model Development for School Reaccreditation of Early Childhood Education

Abstract

As stated in the Research and Development Objectives 2020-2024 by BSKAP, it was agreed on the need to implement a correct and credible quality monitoring and evaluation system. For Primary and Secondary Education, it is determined that 100% of education units will carry out Competency Assessment (AK) and Character Surveys (SK) starting in 2021 by first developing and preparing relevant measuring tools along with indicators of AK-SK readiness in the future, its implementation in 2021 while trying implement the overall accreditation process automation policy. Therefore, performance assessment in these units requires other proxies of learning indicators which are considered to have functions equivalent to competency assessments and character surveys. Instead of direct field visits, if correct, mathematical modeling can be performed to derive measurement proxies derived from the PPA or IPV variables or a combination of both. Automation modeling has been applied to approximately 5,000 school samples by applying three alternative methods, namely Principal Component Analysis (PCA), Partial Least Square (PLS) and Confirmatory Factor Analysis (CFA). PCA modeling was successfully used on 49 predictors without a response variable (Y); ii) PLS modeling was successfully applied to 49 predictors involving response variables; iii) CFA modeling has been successfully carried out on PPA and IPV one by one, because the combined modeling has not succeeded in producing an adequate model in the form of goodness of fit. Keywords: accreditation, assessments, early childhood education, statistical modeling