Large-scale assessments are rich sources of data that can inform a diverse range of research questions related to educational policy and practice. For this reason, datasets from large-scale assessments are available to enable secondary analysts to replicate and extend published reports of assessment results. These datasets include multiple imputed…

Egocentric networks represent a popular research design for network research. However, to what extent and under what conditions egocentric network centrality can serve as reasonable substitutes for their sociocentric counterparts are important questions to study. The answers to these questions are uncertain simply because of the large variety of…

Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…

Although various academic disciplines use data papers to support effective research practices, data papers are still uncommon in the educational sciences. Main goals of data papers are enhancing transparency regarding research processes and supporting data sharing among researchers and thus, open science. As many educational research projects…

In this study, we propose a MOOC Analytic Statistical Visual model (MOOC-ASV) to explore students' engagement in MOOC courses and predict their performance on the basis of their behaviors logged as big data in MOOC platforms. The model has multifunctions, which performs on visually analyzing learners' data by state-of-the-art techniques. The model…

Today, the use of software in qualitative research analysis is rapidly becoming widespread among researchers. Researchers manage large data sets using features such as editing data, transcribing, creating codes, and searching within data. However, while the data analysis uses software in a format, the analysis of the essence of the data is done by…

Data literacy is the ability to collect, manage, evaluate, and apply data, in a critical manner. It is a relatively new field of study, dating only from the 2010s. It includes the skills necessary to discover and access data, manipulate data, evaluate data quality, conduct analysis using data, interpret results of analyses, and understand the…

Facebook is widely used and researched. However, though the data generated by educational technology tools and social media platforms other than Facebook have been used for research purposes, very little research has used Facebook posts as a data source--with most studies relying on self-report studies. While it has historically been impractical…

In response to the problem of inaccurate classification of big data information in traditional English teaching ability evaluation algorithms, this paper proposes an English teaching ability estimation algorithm based on big data fuzzy K-means clustering. Firstly, the article establishes a constraint parameter index analysis model. Secondly,…

There has been a great deal of news, discussion, and outcry regarding the lack of diversity in science, technology, engineering, and math (STEM) related fields, be it industry or academia. On many comparative lists regarding STEM students and workers, African American males are an unacceptably low percentage of the population. The problem is quite…

This systematic review presents the first synthesis of the scientific literature on estimating school and teacher/class effects on student academic performance using random-effects (RE) models with three or more levels. The review delves into the theoretical framework underpinning the estimation of educational effects, the associated statistical…

Artificial intelligence (AI) has been put forth as a technological innovation which can change the way in which healthcare will be delivered in the near future. AI developers plan to deploy tools that will aid diagnosis, improve therapy, minimize errors, increase safety, and optimize systems and bring down costs. In addition, a paradigmatic shift…

The "Building Your Research Data Management Toolkit" was developed to provide introductory research data management skills training to liaisons in academic libraries. This paper assesses the participants' perceived change in knowledge, behaviors and attitudes as a result of participation in the RoadShow program. Long term changes in…

The application of big data in education sparks debates on its effects. Researchers explore its impact on learning outcomes, with divergent views on neural networks' potential and negative consequences. This study assesses big data's influence on basic literacy skills in music education for 5th graders. Using clustering and k-density analyses,…

Undergraduate research is considered to be a high-impact practice; however, research into the data literacy of students conducting undergraduate research is lacking. In addition, institutionwide assessments of data practices are challenging because of varied disciplinary approaches to data. This study investigates the data practices of…