From xc-MOOC to e-MOOC: A case study as a reference model and a proposed non-linear approach to an evolved MOOC

Bugueno-Cordova I.G.; Sperberg-Parra R.A.; Mathias-Naranjo C.A.; Menares-Fernandez D.E.; Ehijo-Benbow A.O.

Keywords: MOOC, AI; MOOC Roadmapping; Non, linear and dynamics models; Smart Help Desk; e, MOOC; xc

Abstract

This paper presents a case study describing the digital transformation of a socio-religious community through the integration of MOOCs. The massiveness of the courses is evident, growing from 400 students in 2017, to +2,700 in 2020 and +3,000 in 2021. The consolidation and sustainability of the MOOC-based system required the organisation's adaptation as an enabling methodology. Based on this experience, and the need to evolve the platform associated with the MOOC, an enhanced MOOC proposal was addressed, based on the available Artificial Intelligence technologies, and a dynamic and non-linear pedagogical approach. For this purpose, emerging technologies such as AI-based multidimensional metrics, Facial Landmark Detection, Facial and Emotion Recognition, text-based Emotion Detector, and Emotion Speech Recognition were applied to the multimedia resources obtained from the case study. The relevance of enhanced and evolved MOOCs in engineering education is also discussed. Finally, we propose the development of a strategic and technological evolution roadmap for MOOCs.

Más información

Título según WOS: From xc-MOOC to e-MOOC: A case study as a reference model and a proposed non-linear approach to an evolved MOOC
Título según SCOPUS: From xc-MOOC to e-MOOC: A case study as a reference model and a proposed non-linear approach to an evolved MOOC
Título de la Revista: IEEE Global Engineering Education Conference, EDUCON
Volumen: 2022-
Editorial: IEEE Computer Society
Fecha de publicación: 2022
Página final: 1532
Idioma: English
DOI:

10.1109/EDUCON52537.2022.9766554

Notas: ISI, SCOPUS