Analyzing and interpreting data is essential to the practice of scientists and is also an essential science and engineering practice for science teaching and learning. Although working with data has benefits for student learning, it is also challenging, particularly with respect to aspects of work with data that are not yet very common in schools,…

For undergraduate students to be prepared for graduate school and industry, it is imperative that they understand how to merge the theoretical insights gleaned through their undergraduate education with the raw data sets acquired through materials analysis. Thus, the ability to implement data analysis is a vital skill that students should develop.…

Comprehensive and timely data on vocational education and training (VET) is important for increasing the efficiency and transparency of Australia's VET sector, in order to improve understanding of Australia's VET market and management of the national VET system. The National VET Data Policy (the Policy) brings together requirements for collecting…

Technological advances have led to an abundance of widely available data on every aspect of life today. Psychologists today have more information than ever before on human cognition, emotion, attitudes, and behavior. "Big Data in Psychological Research" addresses the opportunities and challenges that this data presents to psychological…

Special education and related professionals often understand the importance of adhering to intervention procedures (i.e., fidelity), but may be less familiar with concepts of intervention intensity. In some cases, professionals may correctly apply an intervention, but with insufficient intensity. This can result in an intervention failing to…

Audience analysis is essential for creating successful messages across communication fields. The audience persona is an effective tool for understanding the characteristics and needs of a target audience. Through this unit activity, students experience the process of persona development, build skills in data collection and analysis, and gain…

It is recommended that teacher-scholars of data science adopt reproducible workflows in their research as scholars and teach reproducible workflows to their students. In this article, we propose a third dimension to reproducibility practices and recommend that regardless of whether they teach reproducibility in their courses or not, data science…

The purpose of this study is to develop a valid and reliable Likert-type scale that can be used to measure the data literacy skills of educators. In the development process of the scale, after reviewing the relevant literature, a pool of 130 items was designed and presented to the experts for their view. After the evaluation of experts, the…

Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…

This paper describes a partnership-based approach for analyzing data from a learning management system (LMS) used by students in grades 6-12. The goal of the partnership was to create indicators for the ways in which students navigated digital learning activities, referred to as playlists, that were comprised of resources, pre-assessments, and…

The purpose of this study was to examine the studies related to augmented reality applications in sports science and to discuss the results based on this. Articles selected for analysis were found through searches journals in the Web of Science database from 1975 to 2018 were examined and searched using the keywords ("physical education"…

The unstructured multiple-attempt (MA) item response data in virtual learning environments (VLEs) are often from student-selected assessment data sets, which include missing data, single-attempt responses, multiple-attempt responses, and unknown growth ability across attempts, leading to a complex and complicated scenario for using this kind of…

Purpose: This study aims to investigate the preferences of 96 educational researchers on the use of digital technologies in scientific research. Design/methodology/approach: The study was designed as a quantitative-dominant sequential explanatory mixed-method research. Findings: Despite the spreading use of advanced technologies of big data and…

In the United States, teachers are expected to analyze data to inform instruction and improve student learning. Despite investments in data tools, researchers find that teachers often interact with data visualizations in limited ways. Researchers have called for data interpretation training for preservice teachers to increase teachers'…

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…