在“IT学院”项目中分析开发探究技能和计算思维的数据科学工具

J. Hanč, M. Hančová, V. Jurková, D. Sveda
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引用次数: 0

摘要

我们提出了如何应用现代数据科学技术和方法来有效地准备和统计分析大型教育数据集的想法,在我们的案例中,在“信息技术学院- 21世纪教育”项目中,斯洛伐克全国范围内的中小学学生开发了探究技能和计算思维。结合两个顶级的开源数据科学工具,Python(在Jupyter笔记本中)和R(在R studio软件中),我们展示了用于小学探究技能诊断测试的数据预处理(清理、整理)的一些结果,其中Python工具(例如Pandas库)变得更有优势。对于后续的密集统计分析,R环境更适合。我们对中小学计算机思维诊断测试的统计分析结果进行总结论证,最后在SPSS软件中进行交叉检验。鉴于当前的COVID-19形势,我们仍在收集ITA项目影响的数据,并最终展示了我们计划如何与我们的同事——教育研究人员合作,实施进一步的数据收集、分析和实施方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data science tools in the analysis of developing inquiry skills and computational thinking within the “IT Academy” Project
We present our ideas how to apply modern data science technology and methodology to effectively prepare and statistically analyze large educational datasets which in our case map inquiry skills and computational thinking developed by students in primary and secondary schools at the Slovak national scale, within the project “IT Academy - Education for the 21st Century”. Combining the top two open-source data science tools, Python (within Jupyter notebooks) and R (within R studio software), we illustrate some of results from data preprocessing (cleaning, wrangling) for the diagnostic primary-school test of inquiry skills where Python tools (e.g. Pandas library) became more advantageous. As for the subsequent intensive statistical analysis, R environment was more suitable. We demonstrate summary results of the statistical analysis of the computer thinking diagnostic test for primary and secondary schools, finally cross-checked in SPSS software. Due to the current COVID-19 situation, we are still collecting data from ITA project impacts for which we finally show how we plan to implement further methods for data collecting, analysis and implementation in collaboration with our colleagues - education researchers.
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