Live interest meter: learning from quantified feedback in mass lectures

Verónica Rivera-Pelayo, Johannes Munk, V. Zacharias, Simone Braun
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引用次数: 47

Abstract

There is currently little or no support for speakers to learn by reflection when addressing a big audience, like mass lectures, virtual courses or conferences. Reliable feedback from the audience could improve personal skills and work performance. To address this shortcoming we have developed the Live Interest Meter App (LIM App) that supports the gathering, aggregation and visualization of feedback. This application allows audience members to easily provide and quantify their feedback through a simple meter. We conducted several experimental tests to investigate the acceptance and perceived usefulness of the LIM App and a user study in an academic setting to inform its further development. The results of the study illustriate the potential of the LIM App to be used in such scenarios. Main findings show the need for motivating students to use the application, the readiness of presenters to learn retrospectively, and distraction as the main concern of end users.
现场兴趣计:从大量讲座的量化反馈中学习
目前很少或根本没有支持演讲者在面对大量听众时通过反思来学习,比如大众讲座、虚拟课程或会议。来自听众的可靠反馈可以提高个人技能和工作表现。为了解决这个缺点,我们开发了实时兴趣测量应用程序(LIM应用程序),支持收集,汇总和可视化反馈。这个应用程序允许观众成员通过一个简单的仪表轻松地提供和量化他们的反馈。我们进行了几项实验测试,以调查LIM应用程序的接受程度和感知有用性,并在学术环境中进行了用户研究,以告知其进一步发展。研究结果说明了LIM应用程序在这种情况下使用的潜力。主要研究结果显示,需要激励学生使用应用程序,演讲者准备回顾学习,以及最终用户的主要关注点是分心。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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