In the boxplot, the box always represents -- regardless of its area -- the middle half of the data and thus a measure of variability (interquartile range). However, when students first learn about boxplots, they are usual already familiar with other forms of statistical representations (e.g., bar or circle graphs) in which a larger area represents…

Developmental scientists are often interested in subgroups of people who share commonalities in aspects of development; these subgroups often cannot be captured directly but instead must be inferred from other information. Mixture models can be used in these situations. Two specific types of mixture models, latent profile transition analyses and…

This study aimed to visualize self-regulated learning (SRL) behaviors performed by users from an online teacher professional development platform called the EdHub Library using the pm4py algorithm in Python to parse event data during the first 30 days of the school year and the first 90 days of the COVID-19 pandemic in March 2020. Process mining…

In standard statistical data analysis, the effects of intervention or prevention efforts are evaluated in terms of variable relations. Results from application of regression-type methods suggest whether, overall, intervention is successful. In this article, we propose using configural frequency analysis (CFA) either in tandem with regression-type…

This study sought to establish educational psychologists' (EPs) views on their experiences of using a personal skills profile (PSP), created to support post-16 transition. Two focus groups were held with EPs working in local authorities in the UK. Discussions focused on participants' experiences of using the PSP with young people (YP), its value,…

Web recommendation systems are ubiquitous in the world used to overcome the product overload on e-commerce websites. Among various filtering algorithms, Collaborative Filtering and Content Based Filtering are the best recommendation approaches. Being popular, these filtering approaches still suffer from various limitations such as Cold Start…

In this research, our objective is to characterize the problem-solving procedures of primary and lower secondary students when they solve problems in real class conditions. To do so, we rely first on the concept of heuristics. As this term is very polysemic, we exploit the definition proposed by Rott (2014) to develop a coding manual and thus…

Purpose: This paper aims to investigate the relationship between the students' digital activities and their academic performance through two stages. In the first stage, students' digital activities were studied and clustered based on the attributes of their activity log of learning management system (LMS) data set. In the second stage, the…

Citizen science has proven to be a useful paradigm both to contribute to science and to increase the public understanding of science. Thus the connection between citizen science and schools offers an interesting approach to explore. However, a lot of questions and challenges remain unclear, such as the balance between scientific and educational…

Student dropout is a significant concern for university administrators, students and other stakeholders. Dropout is recognised as highly complex due to its multi-causality, which is expressed in the existing relationship in its explanatory variables associated with students, their socio-economic and academic conditions, and the characteristics of…

Developmental surveillance tools are used to closely monitor the early development of infants and young children. This study provides a novel implementation of a multidimensional item response model, using Bayesian hierarchical priors, to construct developmental profiles for a small sample of children (N = 115) with sparse data collected through…

The ubiquitous use of social platforms across the globe makes them attractive options for investigating social phenomena including migration. However, the use of social media data raises several crucial ethical issues around the areas of informed consent, anonymity and profiling of individuals, which are particularly sensitive when looking at a…

Text mining techniques have become popular in many disciplines in the era of big data. Author profiling analysis, a method of text mining, is useful for identifying the intellectual structures of research fields and the latest research topics that did not appear from author co-citation analysis. This study analyzed the changing intellectual…

This paper discusses empirical comparisons of higher education institutions across world regions. It argues that institutional data systems have the potential for complementing global comparisons promoted by rankings by providing sensible information on institutional size, budgets, staffing, enrolments and activity profiles. With this perspective…

This article explores and presents various statistics regarding permanent school exclusions in England. Publically available national data, e.g. "Permanent" and "fixed-period exclusions in England" (Department for Education, 2021a), are used to identify patterns and thus provide an overview of the number, profile and…