RALO: Accessible Learning Objects Assessment Ecosystem Based on Metadata Analysis, Inter-Rater Agreement, and Borda Voting Schemes

Autor: Paola Ingavelez-Guerra, Vladimir E. Robles-Bykbaev, Angel Perez-Munoz, Jose Hilera-Gonzalez, Salvador Oton-Tortosa, Elena Campo-Montalvo
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: IEEE Access, Vol 11, Pp 8223-8239 (2023)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2023.3234763
Popis: The increasing number of people are living with disability in the World and their access to formal education is considered a challenge for the development of the online education and educational resources. This problem is considered one of the 17 sustainable development goals that are focused on inclusive and equitable quality education. Nevertheless, the existing proposals for mainstream accessibility in virtual education are still complex to apply. However, the models, standards, and good practices to contribute to the virtual educational process and the design of learning for all are identified. For these reasons, in this paper, we describe an accessibility evaluation proposal based on 4 interaction domains: user analysis and interaction, intelligent systems, knowledge databases, and evaluation. In the same way, we describe a set of tools that constitute a Repository of Accessible Learning Objects (RALO) from the perspective of accessibility and adaptability metadata. In this line, the knowledge database follows the regulation and educational models focused on the students with disabilities needs and preferences from the conception of universal design. The validation of the proposal is based on the interaction study and analysis of regular and disabled students and teachers who developed the Learning Objects (LO). To determine whether there was consensus among the teacher’s scores, we used Kendall’s Coefficient of Concordance W.
Databáze: Directory of Open Access Journals