Knowing the level of complexity of digital resources is crucial to delimit their use in the educational context. This paper summarizes the contributions of my thesis and focuses on strategies to build conceptual networks based on the content of digital resources; identifying metrics and features to measure complexity in conceptual networks accurately; and, proposes new approaches to level digital resources complexity. The contributions of this thesis are extensively evaluated with two large datasets containing resources in varied levels of complexity. The results show that the proposed metrics and features are suitable to estimate digital resources complexity and applicability in educational scenarios. The outcomes of this thesis have been published in high-impact venues.
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