In comparative VET research, a model developed from the perspective of comparative politics, the so-called 'skill formation systems typology' developed by Busemeyer and Trampusch, dominates the discourse. However, models to compare VET systems often rely on a narrow set of assumptions and fail to account for their complexity. We therefore review…

Student academic performance prediction is a significant area of study in the realm of education that has drawn the interest and investigation of numerous scholars. The current approaches for student academic performance prediction mainly rely on the educational information provided by educational system, ignoring the information on students'…

Self-regulated learning (SRL) theory comprises cognitive, metacognitive, and affective aspects that enable learners to autonomously manage their learning processes. This article presents a systematic literature review on the measurement of SRL in digital platforms, that compiles the 53 most relevant empirical studies published between 2015 and…

We propose an innovative, effective, and data-agnostic method to train a deep-neural network model with an extremely small training dataset, called VELR (Voting-based Ensemble Learning with Rejection). In educational research and practice, providing valid labels for a sufficient amount of data to be used for supervised learning can be very costly…

Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or nonproficiency of specified latent characteristics. These models are well suited for providing diagnostic and actionable feedback to support intermediate and formative assessment efforts. Several DCMs have been developed…

Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or nonproficiency of specified latent characteristics. These models are well suited for providing diagnostic and actionable feedback to support intermediate and formative assessment efforts. Several DCMs have been developed…

Research that employs theory provides a framework and structure in which complex phenomenon, can be understood. While many theories have been developed to study people's technology usage, the plurality of perspectives offered are complex to navigate due to the diverse range of problems and topics addressed and the varied theoretical foundations…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…

The present study illustrates the utility of applying multilevel mixture models in educational research, using data on the homework behavior of 1,812 Swiss eighth-grade students in French as a second language. A previous person-centered study identified 5 homework learning types characterized by different patterns of high or low homework time and…

The themes in higher education research in different countries vary to some extent. This research takes 15 SSCI journals of higher education as examples. A scientometric method was used to classify the themes in higher education research, and a vector space model was employed to calculate the similarities in different countries active in the…

Since the 1950s in the USA and a bit later in Europe, researchers have started publishing results of systematic research on the learning of older adults. Some have also contributed to constructing theoretical definitions within this theme of research. The perception of older adults as potential learners is a widely shared paradigm. However, there…

Extended education flourishes all over the world. Within different cultures and sociopolitical backgrounds, it takes different terms, forms, and developments across nations. Without identifying the common concepts of extended education, we may not expect further developments in extended education research. This study examined the terms that are…

Analyses of student data in post-secondary education should be sensitive to the fact that there are many different topics of study. These different areas will interest different kinds of students, and entail different experiences and learning activities. However, it can be challenging to identify the distinct academic themes that students might…

Gathering labeled data in educational data mining (EDM) is a time and cost intensive task. However, the amount of available training data directly influences the quality of predictive models. Unlabeled data, on the other hand, is readily available in high volumes from intelligent tutoring systems and massive open online courses. In this paper, we…