VLEngagement：用于评估基于人口的参与度的科学视频讲座数据集
VLEngagement: A Dataset of Scientific Video Lectures for Evaluating Population-based Engagement
摘要：
随着电子学习和个性化教育的出现，数字教育资源的制作和分发蓬勃发展。视频讲座现已成为当今数字时代向大众传授知识的主要方式之一。视频讲座内容的快速创建对目前建立的以人为本的审核和质量保证管道提出了挑战，需要更有效，可扩展和自动化的解决方案来管理学习资源。虽然存在一些与教育视频参与相关的数据集，但仍然需要旨在了解学习者参与科学视频讲座的数据和研究。本文介绍了VLEngagement，这是一个新的数据集，它包含从公开的科学视频讲座中提取的基于内容和特定于视频的特征，以及与用户参与度相关的几个指标。我们介绍了几个新的任务相关的预测和理解上下文无关的参与视频讲座，提供初步的基线。据我们所知，这是处理此类任务的最大和最多样化的公开数据集。基于维基百科主题的特征的提取还允许将更复杂的基于维基百科的特征与数据集相关联，以提高这些任务的性能。数据集、帮助工具和示例代码片段可在https://github.com/sahanbull/context-agnostic-engagement上公开获取
英文摘要：
With the emergence of e-learning and personalised education, the production and distribution of digital educational resources have boomed. Video lectures have now become one of the primary modalities to impart knowledge to masses in the current digital age. The rapid creation of video lecture content challenges the currently established human-centred moderation and quality assurance pipeline, demanding for more efficient, scalable and automatic solutions for managing learning resources. Although a few datasets related to engagement with educational videos exist, there is still an important need for data and research aimed at understanding learner engagement with scientific video lectures. This paper introduces VLEngagement, a novel dataset that consists of content-based and video-specific features extracted from publicly available scientific video lectures and several metrics related to user engagement. We introduce several novel tasks related to predicting and understanding context-agnostic engagement in video lectures, providing preliminary baselines. This is the largest and most diverse publicly available dataset to our knowledge that deals with such tasks. The extraction of Wikipedia topic-based features also allows associating more sophisticated Wikipedia based features to the dataset to improve the performance in these tasks. The dataset, helper tools and example code snippets are available publicly at https://github.com/sahanbull/context-agnostic-engagement
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。
