开发MOOC实验平台:来自用户研究的见解

Vitomir Kovanovíc, Srécko Joksimovíc, Philip Katerinopoulos, Charalampos Michail, George Siemens, D. Gašević
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引用次数: 9

摘要

2011年,mooc现象席卷教育界,使在线教育成为全球公共话语的焦点。尽管研究人员对收集到的大量MOOC数据感到兴奋,但由于一些挑战,这些数据的好处并没有达到预期。MOOC数据的分析是非常耗时和劳动密集型的,并且需要一套非常先进的技术技能,而教育研究人员通常无法获得这些技能。因此,MOOC的数据分析很少在课程结束前完成,这限制了数据影响学生学习成果和体验的潜力。本文介绍MOOCito (MOOC干预工具),这是一个用户友好的MOOC数据分析软件平台,重点是进行数据知情的教学干预和课程实验。我们涵盖了MOOCito背后的重要设计原则,并概述了MOOC研究的发展趋势。虽然这是一项正在进行的工作,但在本文中,我们概述了MOOCito的原型和用户评估研究的结果,该研究的重点是系统的感知可用性和易用性。讨论了研究的结果,以及它们的实际意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developing a MOOC experimentation platform: insights from a user study
In 2011, the phenomenon of MOOCs had swept the world of education and put online education in the focus of the public discourse around the world. Although researchers were excited with the vast amounts of MOOC data being collected, the benefits of this data did not stand to the expectations due to several challenges. The analyses of MOOC data are very time-consuming and labor-intensive, and require and require a highly advanced set of technical skills, often not available to the education researchers. Because of this MOOC data analyses are rarely done before the courses end, limiting the potential of data to impact the student learning outcomes and experience. In this paper we introduce MOOCito (MOOC intervention tool), a user-friendly software platform for the analysis of MOOC data, that focuses on conducting data-informed instructional interventions and course experimentations. We cover important design principles behind MOOCito and provide an overview of the trends in MOOC research leading to its development. Although a work-in-progress, in this paper, we outline the prototype of MOOCito and the results of a user evaluation study that focused on system's perceived usability and ease-of-use. The results of the study are discussed, as well as their practical implications.
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