1美元会话转向检测器:测量视频会话如何影响在线课程中的学生学习

A. Stankiewicz, Chinmay Kulkarni
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引用次数: 6

摘要

大量的在线课程可以从同伴的互动中受益,比如讨论、批评或辅导。然而,为了支撑富有成效的同伴互动,系统必须能够在大规模的互动中检测学生的行为,当互动发生在像视频这样的富媒体中时,这是具有挑战性的。本文介绍了一种不精确但简单的基于浏览器的视频会话转向检测器。在不访问视频或音频数据的情况下检测转弯。我们展示了这个转向检测器如何在基于视频的对话中找到主导地位。在对1027名使用Talkabout(一种基于视频的在线课堂讨论系统)的学生进行的案例研究中,我们展示了被检测到的会话转向行为如何与参与者在讨论中的主观体验和他们的最终课程成绩相关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
$1 Conversational Turn Detector: Measuring How Video Conversations Affect Student Learning in Online Classes
Massive online classes can benefit from peer interactions such as discussion, critique, or tutoring. However, to scaffold productive peer interactions, systems must be able to detect student behavior in interactions at scale, which is challenging when interactions occur over rich media like video. This paper introduces an imprecise yet simple browser-based conversational turn detector for video conversations. Turns are detected without accessing video or audio data. We show how this turn detector can find dominance in video-based conversations. In a case study with 1,027 students using Talkabout, a video-based discussion system for online classes, we show how detected conversational turn behavior correlates with participants' subjective experience in discussions and their final course grade.
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