MUIR框架：交叉链接MOOC资源以增强论坛
The MUIR Framework: Cross-Linking MOOC Resources to Enhance Discussion Forums
摘要：
在按需在线学习时代，每周都会在大规模开放式在线课程中创建和制作新的学习资源--部署新的视频、测验、评估和讨论线程并与之互动。然而，这些资源通常被人为地隔离在平台和人工Web应用程序模型之间。促进这些资源之间的联系有助于学习和多模式理解，改善学习者的体验。我们为MOOC资源统一标识符（MUIR）创建了一个框架。MUIR使应用程序能够以跨平台的方式引用和链接到这些资源，从而可以轻松地将标识符转换为MOOC资源，类似于#hashtags。我们证明了这种方法的可行性，自动识别，链接和决议-一个被称为维基化的任务-在MOOC讨论论坛上提到的学习资源，从收获的10万+资源的集合。我们的维基化系统实现了54.6%的初始成功率在讨论论坛中发现的关键资源提到决议，演示MUIR框架的实用性。我们对这一新问题的分析表明，语境是决定正确解决这类提及的关键因素。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
