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An exploratory analysis of why a person enrolls in a Massive Open Online Course within MOOCKnowledge data collection

Abstract:

Massive Open Online Courses, as latest phase of Open Educational Resources development, represents a nonformal education opportunity for a great number of people from any place in the world. This format is characterized by the great diversity of enrolled people, which are shaped by different personal and professional backgrounds, dissimilar motivations and degrees of satisfaction, among many other features. All these features make up participants' profiles, whose lack of knowledge constitutes an important barrier in order to uncover and get a better understanding of their underlying relationships within input data. The purpose of this study, whose scope is the data collection of MOOCKnowledge project, is to perform an in-depth analysis of the reasons why a person enrolls in a Massive Open Online Courses, as well as to what extent the types of motivation (extrinsic and amotivation) and their degrees are different from one profile to another. Knowledge Discovery in Databases is the methodology applied in this study that performs a comprehensive analysis of the perceptions of participants regarding their degree of motivation for participating in a Massive Open Online Course. The methodological approach carries out a data mining process by running nine clustering algorithms that cover hierarchical (agglomerative and divisive) and partitional techniques. Afterwards, the validation clustering stage raises both internal and stability measures that determine the best clustering algorithm and the appropriate number of clusters in order to decide how best the observations are clustered in the dataset. Finally, within Knowledge Discovery in Databases last stage, goes into a descriptive analysis of the resulting clustering, three motivational profiles labeled as CONVINCED, CAUTIOUS and IRRELEVANT. The analysis of the hidden relationships in the internal structure of motivational elements on each cluster might help educational stakeholders identify which ones impact in a more decisive way on participant's types of motivation regarding MOOC format.