INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 02, FEBRUARY 2020 ISSN 2277-8616 3275 IJSTR©2020 www.ijstr.org Quality Evaluation In Higher Education: Dynamic Data Accumulation And Aggregation Silvia Gaftandzhieva, Rositsa Doneva, George Totkov Abstract: The paper presents a comprehensive approach for quality evaluation of higher education through data accumulation and aggregation. The proposed approach is tested for data accumulation and aggregation for NEAA criteria systems in Bulgaria. For this purpose, the criteria systems that this agency applies for quality evaluation in higher education are analysed. The possibilities for automated data accumulation and aggregation from different university information systems are explored. Experiments have been carried out to automate evaluation and accreditation procedures in a Bulgarian higher education institution. Index Terms: Data Aggregation. Data Accumulation, Higher Education, NEAA Criteria System, Institutional Accreditation, Quality Evaluation, Monitoring. ——————————  —————————— 1. INTRODUCTION The external quality assurance in higher education is an important and indispensable component of the Bologna process. In accordance with the priorities and policies of the Bologna process, independent (often more than one) quality assurance agencies in higher education operate in almost all European countries (e.g. Bulgaria - NEAA, UK - QAA, ODLQC, etc.). Today, 51 of these national quality assurance organizations (from 30 countries) are full members of the European Association for Quality Assurance in Higher Education (ENQA). Their systems for quality assurance follow the Standards and Guidelines for Quality Assurance in the European Higher Education Area (ESG) [1]. The Higher Education Law in Bulgaria [2] (Article 11.) defines the legal framework for the existence of the Bulgarian National Evaluation and Accreditation Agency (NEAA). Quality evaluation, accreditation and control in HE (after 2016) is performed by NEAA [3] on the basis of criteria systems, depending on the type of procedure and in accordance with ESG [1] developed by ENQA. The quality evaluation of higher education is based on a large number of criteria for a variety of objects and processes. This requires the processing of huge amounts of data to objective evaluation. Another important point is the requirement that the evaluation has to be carried out periodically and to reflect the results of processes and states of objects in different time periods. Dynamic monitoring of the procedures and activities related to the quality evaluation in higher education involves the collection (on the basis of automated accumulation, aggregation, analysis and interpretation) of a huge amount of data that function or are results of institutional information and management systems of the higher education institution (for the learning process, academic staff development, etc.), learning management systems, digital repositories, etc. Concrete results have been achieved in the field of automation of procedures for (self)assessment and quality management in higher education [4]. For example, the quality management system of the University of Graz (Austria) generates a large amount of data allowing quality monitoring [5]. A web-based application for monitoring of academic performance in real time based on business intelligence and service-oriented architecture has been developed in Indonesia [6]. The system of the Arab International University extracts and aggregates data from quality assurance and management systems for training, human resources and finance [7]. The system generates reports for the implementation of syllabuses, student performance, feedback, etc. A specific feature of these automated systems is the application of specific methods and approaches in computer modelling of procedures and data related to quality evaluation in higher education. In some cases, this is related to the use of different methodologies for quality evaluation and in others to the absence of a common approach to solve the problem of accumulation and aggregation of the various information resources necessary for quality evaluation. In any case, the issue of dynamic monitoring and quality management has not been satisfactorily resolved. An attempt to overcome these problems has been made in [4], where a model and prototype of a system of dynamic quality evaluation in higher education are proposed. On the basis of these results, the paper presents a comprehensive approach for dynamic accumulation and aggregation of data necessary to the quality evaluation in higher education. The proposed approach is tested for data accumulation and aggregation for NEAA criteria systems. For this purpose, analysis of the possibilities for automated accumulation and aggregation of data from university information system which can be used for the evaluation of criteria from NEAA criteria systems have been done. The paper presents in details the performed experiment for data accumulation and aggregation for automated quality evaluation in the case of institutional accreditation of Bulgarian higher education institutions. 2. APPROACH FOR DATA ACCUMULATION AND AGGREGATION FOR QUALITY EVALUATION IN HIGHER EDUCATION The quality evaluation of objects of higher education is carried out according to adopted evaluation models, presented in different formats - more or less formalized. In all cases, it is expected the areas for object evaluation to be clearly identified and specified, as well as rules, measures and procedures to be formulated, usually in the form of a quality management systems and/or quality evaluations system. Models for quality ———————————————— • Silvia Gaftandzhieva, Assistant Professor, University of Plovdiv “Paisii Hilendarski”, Bulgaria, Email: sissiy88@uni-plovdiv.bg • Rositsa Doneva, Professor, University of Plovdiv “Paisii Hilendarski”, Bulgaria, Email: rosi@uni-plovdiv.bg • George Totkov, Professor, University of Plovdiv “Paisii Hilendarski”, Bulgaria, Email: totkov@uni-plovdiv.bg