Supporting Instructors in Collaborating with Researchers using MOOClets

J. Williams, Juho Kim, Brian Keegan
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引用次数: 4

Abstract

Most education and workplace learning takes place in classroom contexts far removed from laboratories or field sites with special arrangements for scientific research. But digital online resources provide a novel opportunity for large-scale efforts to bridge the real-world and laboratory settings which support data collection and randomized A/B experiments comparing different versions of content or interactions [2]. However, there are substantial technological and practical barriers in aligning instructors and researchers to use learning technologies like blended lessons/exercises & MOOCs as both a service for students and a realistic context to conduct research. This paper explains how the concept of a "MOOClet" can facilitate research-practitioner collaborations. MOOClets [3] are defined as modular components of a digital resource that can be implemented in technology to: (1) allow modification to create multiple versions, (2) allow experimental comparison and personalization of different versions, (3) reliably specify what data are collected. We suggest a framework in which instructors specify what kinds of changes to lessons, exercises, and emails they would be willing to adopt, and what data they will collect and make available. Researchers can then: (1) specify or design experiments that compare the effects of different versions on quantifiable outcomes. (2) Explore algorithms for maximizing particular outcomes by choosing alternative versions of a MOOClet based on the input variables available. We present a prototype survey tool for instructors intended to facilitate practitioner-researcher matches and successful collaborations.
支持教师使用moolet与研究人员合作
大多数教育和工作场所的学习都是在远离实验室或有科学研究特别安排的实地场所的课堂环境中进行的。但是,数字在线资源为大规模努力提供了一个新的机会,可以将现实世界和实验室环境连接起来,支持数据收集和随机a /B实验,比较不同版本的内容或交互[2]。然而,在协调教师和研究人员使用混合课程/练习和mooc等学习技术作为学生的服务和进行研究的现实环境方面,存在着巨大的技术和实践障碍。本文解释了“moooclet”的概念如何促进研究与实践者的合作。mooclet[3]被定义为数字资源的模块化组件,可以在技术上实现:(1)允许修改以创建多个版本,(2)允许不同版本的实验比较和个性化,(3)可靠地指定收集的数据。我们建议建立一个框架,在这个框架中,教师指定他们愿意对课程、练习和电子邮件进行哪些更改,以及他们将收集和提供哪些数据。然后,研究人员可以:(1)指定或设计实验,比较不同版本对可量化结果的影响。(2)根据可用的输入变量,通过选择MOOClet的备选版本,探索最大化特定结果的算法。我们为教师提供了一个原型调查工具,旨在促进从业者-研究人员的匹配和成功的合作。
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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