自动图像处理技术在科学论证研究中的探索

Bo Pei, Henglv Zhao, Wanli Xing, Hee-Sun Lee
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引用次数: 1

摘要

科学论证是提出、完善和反驳科学理论的认知实践,也是为支持主张提供证据的基于语言的实践。本章探讨了计算机图像处理技术如何帮助研究人员识别图像特征与科学论证中使用的书面人工制品质量之间的关系。在本章中,中学生在一个交互模拟模型中工作,并对雨水是否被困在地下提出要求。采用自动图像处理来精确量化与学生索赔相关的几个图像特征。使用卡方检验和独立样本t检验来确定提取的特征与论证之间的关系。结果显示,学生的快照上的一条线的存在对学生的陈述和解释分数有显著影响,学生的线的起点和终点显著影响他们的解释分数,但对他们的陈述分数没有影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Exploration of Automated Image Processing Techniques in the Study of Scientific Argumentation
Scientific argumentation is an epistemic practice where scientific theories are proposed, refined, and refuted, and also a language-based practice where evidence is provided in support of claims. This chapter explores how techniques of computerized image processing can help researchers to identify relationships between features of images and the quality of written artifacts used in scientific argumentation. In this chapter, secondary school students worked in an interactive simulation model and made claims about whether rain water was trapped underground. Automated image processing was employed to precisely quantify several image features relevant to the students' claims. Chi-square tests and independent samples t-tests were used to determine the relationships between the extracted features and the argumentation. The results revealed that the presence of a line on a student's snapshot had a significant effect on that student's claim and explanation scores and the starting and endpoints of the students' lines significantly influenced their explanation scores, but not their claim scores.
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