In the boxplot, the box always represents -- regardless of its area -- the middle half of the data and thus a measure of variability (interquartile range). However, when students first learn about boxplots, they are usual already familiar with other forms of statistical representations (e.g., bar or circle graphs) in which a larger area represents…

Interest in understanding creativity through Programme for International Student Assessment (PISA) data is on the rise, yet researchers face methodological challenges in synthesizing findings across various constructs, measures, and datasets. Meta-analysis--a valuable methodology for synthesizing quantitative data--remains underutilized in…

Scientific inquiry skills are crucial for scientific literacy and cognitive development in the 21st century. Prior research has identified key inquiry skills-- data analytics (DA), control of variables (COV), and scientific reasoning (SR)--but has not validated these skills through comprehensive assessments. The aim of this study was to validate…

With notions of data visualization expanding to include contemporary art and design, data visualization represents an important new dimension for transdisciplinary art education. The pedagogical potential of these practices has begun to be recognized in many fields, including art education. However, despite substantial interest, little research…

It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…

This study aims to determine the graphical literacy levels of middle school mathematics teachers. The participants of the study consisted of 33 middle school mathematics teachers working in different provinces. The data of the study were collected with the help of the graphical literacy test created by the researchers. The data were analyzed by…

The increasing availability of digital tools in science classrooms can provide students with more frequent and easier access to large amounts of data. Large data sets have considerable epistemological potential, as they enable, for instance, the observation of otherwise unobservable phenomena, but it must be assumed that handling them places…

The purpose of this essay is to discuss the impact of the EdD experience on one teacher's understanding of data and research. From a first-person narrative, the author shares how learning to collect and analyze qualitative data has the potential to change the way teachers can engage with "data-driven decision making" in a high school…

This report is focused on the uptake of General Certificate of Secondary Education (GCSE) subjects in England in 2023. Uptake in a GCSE subject is defined as the number or percentage of students at the end of Key Stage 4 (KS4) taking the subject. This report was produced using publicly available data from the Department for Education's (DfE). The…

Simulations were conducted to establish best practice in hyperparameter optimization and accounting for clustering in Generalized Linear Mixed-Effects Model Trees (GLMM trees). Using data-driven best practices, the relationship between a 9th Grade On-Track to Graduate (9G-OTG) indicator and observed high school graduation within four years was…

As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…

This research aimed to investigate the components of digital information fluency (DIF) skills among high school students. The sample comprised 354 teachers from schools supervised by the Office of the Basic Education Commission (OBEC) Secondary Educational Service Area Offices (SEAOs), selected through multiple-stage random sampling. Their…

In the context of an afterschool program in which students explore relatively large authentic datasets, we investigated how 11- to 14-year old students worked with categorical variables. During the program, students learned to use the Common Online Data Analysis Platform (CODAP), a statistical analysis platform specifically designed for middle and…

The issue of missing data raises concerns in all statistical and educational research. In this study, we focus on missing data in school-based assessment data generated by progressed high school learners (those who did not meet the promotional requirements for their current grades but were allowed to move to the next grade because of policy…

The objectives of this research were 1) to study the problems of stress and depression among Grade 12 students; 2) to investigate the machine learning technique in analyzing and predicting stress, depression, and academic performance among Grade 12 students; and 3) to evaluate the stress and depression prediction platform. Students from schools in…