Adaptable Dimensional Models based on the Academic processes factors of the CNA institutional accreditation model

Abstract

In Colombia, the entity in charge of evaluating quality in higher education is the National Accreditation Council, which requires institutions to submit a self-evaluation report with quantitative data. This report often becomes a bottleneck because the data must be extracted from various sources. In this context, Data Warehouses are an alternative solution since they allow information to be centralized and support decision making. In this paper, seven dimensional models are proposed focused on three factors of the CNA related to Academic Processes: students, professors, and academic processes, which are adaptable to the data available in the institutions’ sources. For these models’ design, the literature was first reviewed to identify existing dimensional models focused on academic processes. Then, the DW development methodology for MSMEs was used, which allowed for the identification of the aspects to be evaluated of the study factors of the accreditation guidelines, the quantitative requirements present in the self-assessment reports for these factors, making a mapping between these factors, and validating these requirements by a group of accreditation experts. Then, the dimensional models to be designed to meet these requirements were identified. Their adaptability was validated by a group of experts in data warehouses, who considered that the seven proposed dimensional models have a 100% degree of adaptability to the identified requirements since these models can be adapted to the information available in the higher education institutions, with respect to more frequent, less frequent and proposed requirements.