Base Algorithm and Open Data of Auditing the e-Learning Digital Accessibility

Abstract

Enhancement the methodology for assessing the digital accessibility of e-learning is an important condition for improving the quality of modern educational services. In order to develop a basic algorithm for auditing digital accessibility, the expert data from 173 e-learning resources (56 Massive Open Online Courses (MOOCs) in mathematics, 65 MOOCs in computer science and programming, 22 intra-university online courses in mathematics, computer science and programming, 30 MOOCs in cardiopulmonary resuscitation) were systematized and analyzed. The paper considers: methods and process of collecting expert data, the content of data sets, the procedure for empirical analysis of the results of testing the e-learning content accessibility. The structure of the proposed algorithm of auditing the digital accessibility includes the following stages: preparation for examination; automatic and expert testing of digital accessibility and generation of data sets; data analysis; formulating a final conclusion and recommendations for improving digital accessibility. Further use of the basic algorithm and data sets of audits can be useful for the development of accessible education, the training of e-learning specialists, and the strengthening of regulatory and control mechanisms in the field of education.