This Toolkit presents lessons learned from the process of implementing a new system for collecting student-level work-based learning (WBL) data in high school career and technical education (CTE) programs. As part of a study on career academies and WBL, a research team worked closely with a district CTE office and school staff to design and…

CODAP is a widely-used programming environment for secondary school data science. Its direct-manipulation-based design offers many advantages to learners, especially younger students. Unfortunately, these same advantages can become a liability when it comes to repeating operations consistently, replaying operations (for reproducibility), and also…

Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…

Dynamic geometry software (DGS), especially GeoGebra, have been used in mathematics lessons around the world since it enables a dynamic learning environment. To date, there exist so many published researches about DGS, which leads to the need for meaningful organisation. This study aims to give a broad picture about researches related to DGS. For…

At the school level statistics begins with exploratory data analysis, or EDA. Statistical learning goes on to include statistical inference, which will be discussed in the second part of this article. In this article, the author will talk about EDA and CODAP. EDA can be thought of as looking for patterns in data using graphs and simple statistics…

Six 7th-grade students engaged with an instructional sequence involving the use of the "TinkerPlots" software to organize data sets in ways intended to help them construe two attributes: the location of quarters of the data within a sub-range of the entire set, and the spread of those portions. We present evidence of students' thinking…

Members of the Data Science Program at George Washington University (GWU) designed and implemented a tuition-free two-week summer camp at GWU for high-school students from the Washington Metro Area. The United States Department of Agriculture (USDA) Office of the Chief Information Officer and his staff were our main partners in the project. The…

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…

Scientific statistical working in a team is a special challenge for students in high schools, especially with a civic statistical problem. Ideally, they are following the PPDAC cycle: they formulate a problem together, plan an investigation, collect the data, use software to analyze the data, and formulate results in a seminar paper. This article…

The aim of this research is to advance in the teaching-learning process of representing quadratic functions, both with pencil and paper and with a technological tool. For this purpose, a didactic experience is presented. Firstly, it is explained in the traditional way how to graph a quadratic function; secondly, students are introduced to the…

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…

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…

This paper explores third-wave post-neoliberalism as an assemblage, fractured and dis/embodied, a mobile tool of governance articulated in various shapes across geopolitical sites. Post-neoliberalism is assembled alongside other key cultural shifts, such as post-truth, posthuman and the computational turn. In light of this Special Issue, this…

Statistical literacy is a skill that will be required by all students, but only limited insights exist into how it can be developed in middle schools. Research is required that identifies design principles and provides didactic materials for developing statistical literacy in actual middle school classrooms, meaning classrooms in which statistics…

In recent years, growing technology has affected people's communication. Not only speaking and listening but also writing has an important role in communication. Particularly, devices have changed and applications have varied thanks to spreading mobile hardware. The aim of this study is to explore the usage status and preferences of students for…