IRDLMay 15, 2020

The MUIR Framework: Cross-Linking MOOC Resources to Enhance Discussion Forums

arXiv:2005.07382v15 citations
AI Analysis

This addresses the issue of fragmented learning materials for MOOC learners, though it is incremental as it builds on existing Wikification techniques.

The authors tackled the problem of siloed learning resources in MOOCs by creating the MUIR framework to enable cross-platform linking, achieving a 54.6% success rate in automatically identifying and resolving resource mentions in discussion forums.

New learning resources are created and minted in Massive Open Online Courses every week -- new videos, quizzes, assessments and discussion threads are deployed and interacted with -- in the era of on-demand online learning. However, these resources are often artificially siloed between platforms and artificial web application models. Facilitating the linking between such resources facilitates learning and multimodal understanding, bettering learners' experience. We create a framework for MOOC Uniform Identifier for Resources (MUIR). MUIR enables applications to refer and link to such resources in a cross-platform way, allowing the easy minting of identifiers to MOOC resources, akin to #hashtags. We demonstrate the feasibility of this approach to the automatic identification, linking and resolution -- a task known as Wikification -- of learning resources mentioned on MOOC discussion forums, from a harvested collection of 100K+ resources. Our Wikification system achieves a high initial rate of 54.6% successful resolutions on key resource mentions found in discussion forums, demonstrating the utility of the MUIR framework. Our analysis on this new problem shows that context is a key factor in determining the correct resolution of such mentions.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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