Toward Enhanced Quality Assessment in Software Engineering MOOCs

Title:

Toward Enhanced Quality Assessment in Software Engineering MOOCs [Baixar]

Autores/as:

Prates, Jorge Marques and Alario-Hoyos, Carlos and Maldonado, José Carlos

Índice de termos:

Electronic learning;Computer aided instruction;Software engineering;Education;Quality assessment;Systematics;Software;Systematic literature review;Planning;Accreditation;Massive open online courses (MOOCs);software engineering education;quality;evaluation

Resumo:

Massive Open Online Courses (MOOCs) are digital courses that offer open learning content, reaching a broad audience of students. In the realm of Software Engineering Education, MOOCs can be integrated with methodologies like flipped classrooms and blended learning. However, effectively evaluating the use of MOOCs poses a challenge due to the absence of defined metrics for assessing their quality. In this context, this study aims to scrutinize the quality of MOOCs, specifically focusing on Software Engineering. The research questions investigate several aspects through a Systematic Mapping Mapping, including the quality criteria for MOOC evaluation, specific characteristics relevant to Software Engineering education, the application of quality models, the relationship between standardized concepts in MOOCs and their quality, and the benefits of quality assessments conducted by accreditation agencies. The research endeavors to offer a comprehensive insight into quality assessment within the MOOC landscape, with a particular emphasis on Software Engineering Education. The results encompass the identification of quality criteria for evaluating MOOCs in the field of Software Engineering, as well as a deeper understanding of the particular characteristics that impact the quality of these courses.

DOI:

10.1109/RITA.2025.3586806

Como citar:
Prates, Jorge Marques and Alario-Hoyos, Carlos and Maldonado, José Carlos, "Toward Enhanced Quality Assessment in Software Engineering MOOCs" in IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, pp. 172-181, . 2025. doi: 10.1109/RITA.2025.3586806