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…

Written with faculty in mind, "Assessment by Design" is a practical resource that will also be useful to student affairs staff and administrators dedicated to using assessment to improve learning in curricular and co-curricular settings. This book presents the Cycle of Assessment as a framework that supports assessment in service of…

With sport now fully immersed in the era of big data, there is a need for sport managers who are data literate and, therefore, capable of collecting, managing, evaluating, and applying data to the range of problems and scenarios encountered by industry personnel. However, many in the sport management academy remain unacquainted with the…

Purpose: The aim of this study was to map the use of implementation science frameworks, models, and theories in intervention research targeting learning needs in the classroom. Method: A scoping review was conducted. Electronic database and manual searches were conducted. Two reviewers independently completed screening, data extraction, and…

This dissertation will address the questions: In what ways can MBR theory be applied to design training that will improve the capacity of Citizen scientists to collect and analyze high quality scientific data?; To what degree does this training impact their ability to formulate complex understandings of environmental problems in their Citizen? The…

This conceptual framework aims to build a shared and comprehensive understanding of what constitute EiE data and of the concepts and processes that underpin and guide work on education in emergencies data across a range of contexts, including acute emergencies, protracted crises, and displacement. The framework also presents a number of strategic…

The purpose of this quantitative causal-comparative study is an empirical examination of the differences in business intelligence capability and the value and competitive advantage of mid-level higher education academia professionals from community colleges, four-year public, and four-year private institutions within the United States.…

The main aim of this study was to introduce the ConQuest program, which is used in the analysis of multivariate and multidimensional data structures, and to show its applications on example data structures. To achieve this goal, a basic research approach was applied. Thus, how to use the ConQuest program and how to prepare the data set for…

Blended learning, which is the "thoughtful fusion of face-to-face and online learning experiences" (Garrison & Vaughan, 2008), is a pedagogical paradigm used in courses across numerous disciplines. In this paper, the use of LinkedIn Learning modules as the primary technological component is described; the focus of this first-time use…

The design and analysis of experiments (DOE) has historically been an important part of an education in statistics, and with the increasing complexity of modern production processes and the advent of large-scale online experiments, it continues to be highly relevant. In this article, we provide an extensive review of the literature on DOE…

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…

Using secondary data has many advantages, but there are also many limitations, including the lack of relevant information. This article draws on a previous study that used secondary data to investigate substance use in young, elite athletes. Three types of missing data appeared: missing data, lack of information about the data collection process,…

A growing body of literature has focused on missing data methods that factorize the joint distribution into a part representing the analysis model of interest and a part representing the distributions of the incomplete predictors. Relatively little is known about the utility of this method for multilevel models with interactive effects. This study…

Preprocessing is a critical step in the analysis pipeline of spectroscopic data. However, students are rarely introduced to preprocessing when learning spectral techniques in laboratory courses which in turn may affect and delay their progress in the field. Despite its undoubtable importance, students will be mainly performing spectroscopic…

Education plays a major role in the development of the consciousness of the whole society. Education has been improved by analyzing educational data related to student academic performance. By using data mining techniques and algorithms on data from the educational environment, students' performances can be predicted. In this study, a novel Hybrid…