Towards Automatic Building of Learning Pathways

Learning material usually has a logical structure, with a beginning and an end, and lectures or sections that build upon one another. However, in informal Web-based learning this may not be the case. In this paper, we present a method for automatically calculating a tentative order in which objects should be learned based on the estimated complexity of their contents. Thus, the proposed method is based on a process that enriches textual objects with links to Wikipedia articles, which are used to calculate a complexity score for each object. We evaluated our method with two different datasets: Wikipedia articles and online learning courses. For Wikipedia data we achieved correlations between the ground truth and the predicted order of up to 0.57 while for subtopics inside the online learning courses we achieved correlations of 0.793.

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