The EdSurvey package helps users download, explore variables in, extract data from, and run analyses on large-scale assessment data. The analysis functions in EdSurvey account for the use of plausible values for test scores, survey sampling weights, and their associated variance estimator. We describe the capabilities of the package in the context…

The five SEERNet digital learning platforms (DLPs) present unique opportunities for researchers by offering tools, processes, and infrastructure to make research more efficient, scalable, and relevant. However, conducting research within a DLP may require a shift in a researcher's orientation or mindset in how they think about potential research…

Accurate data extraction is a key component of evidence synthesis and critical to valid results. The advent of publicly available large language models (LLMs) has generated interest in these tools for evidence synthesis and created uncertainty about the choice of LLM. We compare the performance of two widely available LLMs (Claude 2 and GPT-4) for…

Extracting data from studies is the norm in meta-analyses, enabling researchers to generate effect sizes when raw data are otherwise not available. While there has been a general push for increased reproducibility in meta-analysis, the transparency and reproducibility of the data extraction phase is still lagging behind. Unfortunately, there is…

A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…

Existing toolkits for analyzing movement dynamics in animal ecology primarily focus on individual or group behavior in habitats without predefined boundaries, while methods for studying human activity often cater to bounded environments, such as team sports played on defined fields. This leaves a gap in tools for modeling and analyzing human group…

As organizations' reliance on data increases, the prevalence of data analytics programs in universities likewise increases. However, despite this specialized education, scholars still report a gap between the knowledge and skills students graduate with and those required by industry upon beginning work as an entry-level data analyst. We draw on…

The purpose of this study was to develop and measure the usability of the software prototype of formative assessment in the LMS. This study was applied in terms of research objective and mixed method (qualitative-quantitative) in terms of data collection in which an exploratory sequential mixed methods design was used. In addition, in order to…

The COVID pandemic highlighted the increasing deployment of digital technologies in educational institutions, defined as 'edtech'. The most visible edtech was video conferencing software, but a swathe of edtech startups have sought to roll out their products and services to educational institutions. We focus specifically on the deployment of…

The system architecture of big data in massive open online courses (BD-MOOCs System Architecture) is composed of six components. The first component was comprised of big data tools and technologies such as Hadoop, YARN, HDFS, Spark, Hive, Sqoop, and Flume. The second component was educational data science, which is composed of the following four…

Purpose: Mobile learning has seen tremendous growth over the years. Like any other software application, usability is one of the key concerns in its successful implementation. There is a lack of study that provides a comprehensive overview of usability testing of mobile learning applications. Motivated by this a mapping study is conducted.…

Interrupted time series (ITS) studies are frequently used to examine the impact of population-level interventions or exposures. Systematic reviews with meta-analyses including ITS designs may inform public health and policy decision-making. Re-analysis of ITS may be required for inclusion in meta-analysis. While publications of ITS rarely provide…

Background/Context: Application Programming Interfaces (APIs) are becoming a core means to collect and disseminate data for education research and policy. Surveys can be costly, slow, and burden respondents, and manually downloading data files is slow and cumbersome when many files are needed. APIs provide a programmatic way to collect data or…

Searching for trials is a key task in systematic reviews and a focus of automation. Previous approaches required knowing examples of relevant trials in advance, and most methods are focused on published trial articles. To complement existing tools, we compared methods for finding relevant trial registrations given a International Prospective…

Students with disabilities represent 15% of U.S. public school students. Individualized Education Programs (IEPs) inform how students with disabilities experience education. Very little is known about the aspects of IEPs as they are historically paper-based forms. In this study, we develop a coding taxonomy to categorize IEP goals into 10 subjects…