Remote Experimentation with Massively Scalable Online Laboratories

被引：8

作者：

Neustock, Lars Thorben ^{[1
]}

Herring, George K. ^{[1
]}

Hesselink, Lambertus ^{[1
]}

机构：

[1] Stanford Univ, Stanford, CA 94305 USA

来源：

ONLINE ENGINEERING & INTERNET OF THINGS | 2018年 / 22卷

关键词：

Online laboratory; Education; Experimentation; Scalability;

D O I：

10.1007/978-3-319-64352-6_24

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper we present a solution for highly scalable online laboratories at low cost. The Massively Scalable Online Laboratories (MSOL) is an online platform that enables the virtualization of real experiments in a fashion that very closely mimics a physical experiment. Moreover, it includes social features to enable peer-to-peer learning and facilitates the creation of an online community. To add an experiment to the MSOL platform, an existing setup is automatically turned into a data set, accessible through data base queries. In this way, MSOL provides an effective and scalable solution to add an important element to current online education systems at low costs. The MSOL platform might also accompany scientific and engineering papers to add another domain to disseminate qualitative and quantitative data.

引用

页码：258 / 265

页数：8