Missing data are common with large scale assessments (LSAs). A typical approach to handling missing data with LSAs is the use of listwise deletion, despite decades of research showing that approach can be a suboptimal strategy resulting in biased estimates. In order to help researchers account for missing data, we provide a tutorial using R and…

Computer-based learning environments (CBLEs) are powerful tools to support student learning. Increasingly of interest is the data that is recorded as learners interact with a CBLE. This "process data" yields opportunities for researchers to examine learners' engagement with a CBLE and explore whether specific interactions are associated…

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…

The last decade has seen a rise in big data approaches, including in the humanities, whereby large quantities of data are collected and analysed. In this paper, we discuss long-form audio recordings that result from individuals wearing a recording device for many hours. Linguists, psychologists and anthropologists can use them, for example, to…

With the rapid advancement of information technology, online education based on big data and artificial intelligence is a hot research topic in education. This study focuses on applying big data and AI in online vocal wisdom classes to enhance personalized teaching and effectiveness. It aims to address issues in traditional vocal education like…

Purpose: The purpose of this paper is to analyse data literacy in the new Digital Competence Framework for Citizens (DigComp 2.2). Mid-2022 the Joint Research Centre of the European Commission published a new version of the DigComp (EC, 2022). This new version focusses more on the datafication of society and emerging technologies, such as…

Drawing on annual, nationally representative survey data from 2007-2022, I demonstrate that partisan gaps - the average differences in public opinion between Democrats and Republicans - have widened on many education issues. This pattern consistently exceeds what would be expected due to the changing demographic compositions of the parties alone.…

Formal achievement data such as test scores and school performance feedback from standardised assessments can be a powerful tool for data-based decision making and school improvement. However, teachers' and school leaders' usage of these data is not necessarily straightforward or predictable. In order to illuminate how educational professionals…

Students, families, colleges, and lawmakers need clearer information on postsecondary outcomes to make informed decisions. By leveraging data available at institutions and federal agencies, a nationwide student-level data network (SLDN) would close information gaps that persist in our higher education landscape to answer critical questions about…

Despite increased efforts to assess the adoption rates of open science and robustness of reproducibility in sub-disciplines of education technology, there is a lack of understanding of why some research is not reproducible. Prior work has taken the first step toward assessing reproducibility of research, but has assumed certain constraints which…

Educational data mining is an emerging interdisciplinary research area involving both education and informatics. It has become an imperative research area due to many advantages that educational institutions can achieve. Along these lines, various data mining techniques have been used to improve learning outcomes by exploring large-scale data that…

The combination of the quantitative turn in linguistics and the emergence of text analytics has created a demand for new methodological skills among linguists and data scientists. This paper introduces KNIME as a low-code programming platform for linguists interested in learning text analytic methods, while highlighting the considerations…

With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation…

Visual data have dramatically increased in quantity in the digital age, presenting new opportunities for social science research. However, the extensive time and labor costs to process and analyze these data with existing approaches limit their use. Computer vision methods hold promise but often require large and nonexistent training data to…

This study provides a picture of the impact the novel Coronavirus (COVID-19) had on action research performed by graduate students at a small Midwest university. A qualitative case study was conducted to examine how the participants' abilities to implement their research, gather data, and analyze the results was impacted by COVID-19. Research…