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Fleischer, Yannik; Biehler, Rolf; Schulte, Carsten – Statistics Education Research Journal, 2022
This study examines modelling with machine learning. In the context of a yearlong data science course, the study explores how upper secondary students apply machine learning with Jupyter Notebooks and document the modelling process as a computational essay incorporating the different steps of the CRISP-DM cycle. The students' work is based on a…
Descriptors: Statistics Education, Educational Research, Electronic Learning, Secondary School Students
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Fung, Tze-ho; Li, Wing-yi – Practical Assessment, Research & Evaluation, 2022
Rough set theory (RST) was proposed by Zdzistaw Pawlak (Pawlak,1982) as a methodology for data analysis using the notion of discernibility of objects based on their attribute values. The main advantage of using RST approach is that it does not need additional assumptions--like data distribution in statistical analysis. Besides, it provides…
Descriptors: Gifted, Metacognition, Learning Strategies, Programming Languages
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Thompson, JaCoya; Arastoopour Irgens, Golnaz – Journal of Statistics and Data Science Education, 2022
Data science is a highly interdisciplinary field that comprises various principles, methodologies, and guidelines for the analysis of data. The creation of appropriate curricula that use computational tools and teaching activities is necessary for building skills and knowledge in data science. However, much of the literature about data science…
Descriptors: Data Analysis, Middle School Students, Statistics Education, Student Centered Learning
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Podworny, Susanne; Hüsing, Sven; Schulte, Carsten – Statistics Education Research Journal, 2022
Data science surrounds us in contexts as diverse as climate change, air pollution, route-finding, genomics, market manipulation, and movie recommendations. To open the "data-science-black-box" for lower secondary school students, we developed a data science teaching unit focusing on the analysis of environmental data, which we embedded…
Descriptors: Statistics Education, Programming, Programming Languages, Data Analysis
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Bulut, Okan; Yavuz, Hatice Cigdem – International Journal of Assessment Tools in Education, 2019
Educational data mining (EDM) has been a rapidly growing research field over the last decade and enabled researchers to discover patterns and trends in education with more sophisticated methods. EDM offers promising solutions to complex educational problems. Given the rapid increase in the availability of big data in education and software…
Descriptors: Data Analysis, Educational Research, Educational Researchers, Computer Software
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Boutnaru, Shlomi; Hershkovitz, Arnon – Interdisciplinary Journal of e-Skills and Lifelong Learning, 2015
In recent years, schools (as well as universities) have added cyber security to their computer science curricula. This topic is still new for most of the current teachers, who would normally have a standard computer science background. Therefore the teachers are trained and then teaching their students what they have just learned. In order to…
Descriptors: Computer Software, Computer Security, Programming Languages, Computer Science Education