A revised application of cognitive presence automatic classifiers for MOOCs: a new set of indicators revealed?
Int J Educ Technol High Educ
; 19(1): 48, 2022.
Article
en En
| MEDLINE
| ID: mdl-36118283
Automatic analysis of the myriad discussion messages in large online courses can support effective educator-learner interaction at scale. Robust classifiers are an essential foundation for the use of automatic analysis of cognitive presence in practice. This study reports on the application of a revised machine learning approach, which was originally developed from traditional, small-scale, for-credit, online courses, to automatically identify the phases of cognitive presence in the discussions from a Philosophy Massive Open Online Course (MOOC). The classifier performed slightly better on the MOOC discussions than similar previous studies have found. A new set of indicators to identify cognitive presence was revealed in the MOOC discussions, unlike those in the traditional courses. This study also cross-validated the classifier using MOOC discussion data from three other disciplines: Medicine, Education, and Humanities. Our results suggest that the cognitive classifier trained using MOOC data in only one discipline cannot yet be applied to other disciplines with sufficient accuracy.
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1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Int J Educ Technol High Educ
Año:
2022
Tipo del documento:
Article
País de afiliación:
Nueva Zelanda
Pais de publicación:
Suiza