This paper adds an algorithmic epistemology perspective to previous works that examine the datafication of subjective social and emotional characteristics, perceptions, and behaviours. The paper employs a comparative epistemological approach to explore two behavioural educational platforms: RedCritter Teacher and Panorama Education. We unpack…

In the context of higher education's growing significance and the persistence of inequalities in it, the article aims to further develop the understanding of higher education as a public good and to explore its association with social cohesion in a European comparative perspective. It shifts the focus from the content of higher education as a…

As data are 'numbers with context' (Cobb & Moore, 1997), contextual knowledge plays a prominent role in dealing with statistics. While insights about a specific context can further the depth of interpreting and evaluating outcomes of data analysis, research shows how it can also hinder relying on data especially if results differ from…

In the current study, we compare propensity score (PS) matching methods for data with a cross-classified structure, where each individual is clustered within more than one group, but the groups are not hierarchically organized. Through a Monte Carlo simulation study, we compared sequential cluster matching (SCM), preferential within cluster…

The majority of adolescents communicate via text-based messaging, particularly through WhatsApp, a widely used free communication application. Written content on WhatsApp has the methodological potential to provide rich qualitative interview data. This study compares data collected using text-based WhatsApp versus face-to-face interview…

Meta-analysts often encounter missing covariate values when estimating meta-regression models. In practice, ad hoc approaches involving data deletion have been widely used. The current study investigates the performance of different methods for handling missing covariates in meta-regression, including complete-case analysis (CCA), shifting-case…

Purpose: Comparative data of autism-sensitive standardized measures of emotion regulation and lability, describing percentage change over time for populations of young autistic children, are currently publicly unavailable. We propose publication of such data as a support for future therapeutic intervention studies. Methods: We generate and present…

To develop competency in science practices, such as data analysis and interpretation, chemistry learners must develop an understanding of what makes an analysis and interpretation "good" (i.e., the criteria for success). One way that individuals extract the criteria for success in a novel situation is through making social comparisons,…

Mixed-mode surveys are popular as they can save costs and maintain (or improve) response rates relative to single-mode surveys. Nevertheless, it is not yet clear how design decisions like survey mode or questionnaire length impact measurement quality. In this study, we compare measurement quality in an experiment of three distinct survey designs…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

In the last few years, Qualitative Comparative Analysis (QCA) has become one of the most important data analysis methods in comparative research. According to the guidelines of this method, there are certain steps that a researcher needs to follow, before causally analyzing the data for necessary and sufficient conditions. One of these steps is…

A commonly used metric for measuring college costs, drawn from data in the Integrated Postsecondary Education Data System (IPEDS), is expenditure per full-time equivalent (FTE) student. This article discusses an error in this per FTE calculation when using IPEDS data, especially with regard to community colleges. The problem is that expenditures…

Systematic reviews with meta-analyses are powerful tools that can answer research questions based on data from published studies. Ideally, all relevant data is directly available in the text or tables, but often it is only presented in graphs. In those cases, the data can be extracted from graphs, but this potentially introduces errors. Here, we…

Systematic reviews are vital for guiding practice, research and policy, although they are often slow and labour-intensive. Large language models (LLMs) could speed up and automate systematic reviews, but their performance in such tasks has yet to be comprehensively evaluated against humans, and no study has tested Generative Pre-Trained…

Diversity audits are frequently used as an assessment method to measure the diversity of a library collection. Yet, there is not frequent research on the aftermath of diversity audits, especially in the context of comparing data from several audits to assess the difference in the makeup of a library collection. In this article, the author…