文章基本信息

标题：EvoGrader: an online formative assessment tool for automatically evaluating written evolutionary explanations
本地全文：下载
作者：Kayhan Moharreri ; Minsu Ha ; Ross H Nehm 等
期刊名称：Evolution: Education and Outreach
印刷版ISSN：1936-6434
出版年度：2014
卷号：7
期号：1
页码：1-14
DOI：10.1186/s12052-014-0015-2
出版社：BioMed Central
摘要：EvoGrader is a free, online, on-demand formative assessment service designed for use in undergraduate biology classrooms.EvoGrader’s web portal is powered by Amazon’s Elastic Cloud and run with LightSIDE Lab’s open-source machine-learning tools.The EvoGrader web portal allows biology instructors to upload a response file (.csv) containing unlimited numbers of evolutionary explanations written in response to 86 different ACORNS (Assessing COntextual Reasoning about Natural Selection) instrument items.The system automatically analyzes the responses and provides detailed information about the scientific and naive concepts contained within each student’s response, as well as overall student (and sample) reasoning model types.Graphs and visual models provided by EvoGrader summarize class-level responses; downloadable files of raw scores (in .csv format) are also provided for more detailed analyses.Although the computational machinery that EvoGrader employs is complex, using the system is easy.Users only need to know how to use spreadsheets to organize student responses, upload files to the web, and use a web browser.A series of experiments using new samples of 2,200 written evolutionary explanations demonstrate that EvoGrader scores are comparable to those of trained human raters, although EvoGrader scoring takes 99% less time and is free.EvoGrader will be of interest to biology instructors teaching large classes who seek to emphasize scientific practices such as generating scientific explanations, and to teach crosscutting ideas such as evolution and natural selection.The software architecture of EvoGrader is described as it may serve as a template for developing machine-learning portals for other core concepts within biology and across other disciplines.
关键词：Online assessment;Computers;Technology;Supervised Machine Learning;Training set;Scoring Model;Classifier;Evolution;Natural Selection;Undergraduates