Researchers may have at their disposal the raw data of the studies they wish to meta-analyze. The goal of this study is to identify, illustrate, and compare a range of possible analysis options for researchers to whom raw data are available, wanting to fit a structural equation model (SEM) to these data. This study illustrates techniques that…

This paper presents the R Analyzer for Large-Scale Assessments (RALSA), a newly developed R package for analyzing data from studies using complex sampling and assessment designs. Such studies are, for example, the IEA's Trends in International Mathematics and Science Study and the OECD's Programme for International Student Assessment. The package…

This article introduces an open-source software package--R for Qualitative Data Analysis (RQDA). RQDA is an R package for analysis of text-formatted data, which is compatible across operating platforms. It is user-friendly and seamlessly integrates with R, which makes it possible to conduct statistical analyses on qualitative coding. Alternative…

Integrating the use of large datasets into our teaching provides critical and unique opportunities to build students' skills and conceptual knowledge. Here, we discuss the core components needed to develop effective activities based on large datasets, which align with the 5E learning cycle. Data-based activities should be structured around a…

Machine learning is a popular topic in data analysis and modeling. Many different machine learning algorithms have been developed and implemented in a variety of programming languages over the past 20 years. In this article, we first provide an overview of machine learning and clarify its difference from statistical inference. Then, we review…

Ten years after the announcement of the "rise of the super experiment" at Educational Data Mining 2012, challenges to implementing "internet scale" educational experiments often persist for educational technology providers, especially when they seek to test substantive instructional interventions. Studies that deploy and test…

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…

For the appraisal of single-case intervention data, school psychologists have been encouraged to focus most, if not all, of their interpretive weight on the visual inspection of graphed data. However, existing software programs provide practitioners with limited features for systematic visual inspection. R (R Development Core Team, 2014) is a…

Configural frequency analysis and log-linear modeling are presented as person-centered analytic approaches for the analysis of categorical or categorized data in multi-way contingency tables. Person-centered developmental psychology, based on the holistic interactionistic perspective of the Stockholm working group around David Magnusson and Lars…

"R" (R Development Core Team, 2011) is a very powerful tool to analyze data, that is gaining in popularity due to its costs (its free) and flexibility (its open-source). This article gives a general introduction to using "R" (i.e., loading the program, using functions, importing data). Then, using data from Canivez, Konold,…

Item Response Theory (IRT) is a ubiquitous model for understanding humans based on their responses to questions, used in fields as diverse as education, medicine and psychology. Large modern datasets offer opportunities to capture more nuances in human behavior, potentially improving test scoring and better informing public policy. Yet larger…

Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…

The authors describe the University of Central Florida's top-down/bottom-up action analytics approach to using data to inform decision-making at the University of Central Florida. The top-down approach utilizes information about programs, modalities, and college implementation of Web initiatives. The bottom-up approach continuously monitors…

A CMI-based online forum is designed to address the need for a system to manage students' online participation. The proposed system may reduce the time required to manage online participation. The system was evaluated by a total of 64 students enrolled in an academic semester. The evaluation has two objectives. The first was to determine the…

Learning Analytics can provide powerful tools for teachers in order to support them in the iterative process of improving the effectiveness of their courses and to collaterally enhance their students' performance. In this paper, we present the theoretical background, design, implementation, and evaluation details of eLAT, a Learning Analytics…