Coping with Access Difficulties and Absenteeism through Data Visualization: A Case Study from a Rural Vocational School in Northern Greece

Abstract

Absenteeism and early school leaving (ESL) constitute two main problems in education with a significant impact on adolescents’ life. Early leavers from education and training may face considerable difficulties in the labor market later as adults. Motivated by the necessity of minimizing this phenomenon, we developed a novel application that uses big data, generated from a student attendance management system in a vocational senior high school in Greece. This application first automatically conducts data preprocessing and data transformation and saves the processed data on a cloud data warehouse. Then, an online analytical processing (OLAP) analysis is performed, resulting in a real-time visualization that provides a variety of different graphs. In this study, we demonstrate the need for real-time visualization of the analyzed data. Such a type of presentation provides information on the spot regarding potential early leavers’ behavior, helping school administrators gain time for prompt and effective actions. Through the data processing and analysis, the application provides instructors with constant information, in addition to those acquired by the formal student attendance management systems. Our research provides indicative evidence in favor of the use of such applications, as by adequately reacting to the observed patterns in real-time, we observed a significant decrease in students’ unnecessary absences and a reduction of the ELS phenomenon in a three-year school period.

Keywords

• early school leaving (ELS)
• absenteeism
• data visualization
• learning analytics