RETRACTED ARTICLE: Exploring ML-based classification system for digital learning platforms: a mapping technique of massive open online courses
Ayse Kok Arslan
The object of research is massive open online courses. One of the most problematic areas in online learning is how to improve the quality assurance of digital learning systems. Analysis and classification of massive open online courses is a difficult task, given the variability of massive open online courses structures, contents, designs, platforms, providers, and learner profiles. To overcome this challenge, this study aims to propose an automatic and large-scale machine learning based classification system for massive open online courses according to their learning objectives by making use of the six cognitive levels of Bloom’s taxonomy. During the course of the research, it is shown that analyzing learning objectives associated with modules and programs can further enhance the quality of digital learning system. As a result of the research, a representation and a detailed analysis of the dataset for experimentation with the different models are provided. Further research can focus on the privacy implications of the current control on developments of artificial intelligence taking into account creativity, and innovation which can hardly be performed by machines.
How to cite paper:
Arslan, A. K. (2022). RETRACTED ARTICLE: Exploring ML-based classification system for digital learning platforms: a mapping technique of massive open online courses. Technology Audit and Production Reserves, 5(2(67), 15–19.
