This research aimed to determine the trends related to blended learning studies conducted in science education through descriptive content analysis. This study was performed using the document review method. For this purpose, 120 studies on blended learning in science education were determined between 2005 and 2022 in the Web of Science (WoS)…

Even though working with data is as important as coding for understanding and dealing with complex problems across multiple fields, it has received very little attention in the context of Computational Thinking. This paper discusses an approach for bridging the gap between Computational Thinking with Data Science by employing and studying…

A problem exists in NC Montessori schools with effective data analysis for specific learning disabilities (SLD) placement. The purpose of this study was to identify administrators' and teachers' perceptions of data collection and analysis within multitiered systems of support (MTSS) in a Montessori school. Fixsen's implementation science theory…

Data infrastructures are suffused with stories of their past, present, and future that govern their use. This article draws on research into 'OneSchool', the state schooling data infrastructure used to manage student data in Queensland, Australia. The political, social, and technical histories of OneSchool's development are shown to govern its…

The role of faculty in gathering, analyzing and using student learning data is growing and changing, but still underrepresented in the higher education research literature. While faculty are often expected and required to participate in assessment work, some faculty go beyond assessment work as service to take leadership roles. Using data…

The purpose of the DaSy Data System Framework (referred to as DaSy framework) is to assist Part C (Early Intervention) and Part B (School-Aged) 619 programs in developing and enhancing high-quality state data systems for the collection, analysis, reporting, and use of their Individuals with Disabilities Education Act (IDEA) data. The DaSy…

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…

It is meaningful to create a comprehensive score to extract information from mass continuous data when they measure the same latent concept. Therefore, this study adopts the logic of psychometrics to conduct scales on continuous data under the Rasch models. This study also explores the effect of different data discretization methods on scale…

Previous work has demonstrated similarities and differences between aerial and terrestrial image viewing. Aerial scene categorization, a pivotal visual processing task for gathering geoinformation, heavily depends on rotation-invariant information. Aerial image-centered research has revealed effects of low-level features on performance of various…

Methods of network meta-analysis (NMA) can be classified as arm-based and contrast-based approaches. There are several arm-based approaches, and some of these have been criticized because they recover inter-study information and hence do not obey the principle of concurrent control. Here, we point out that recovery of inter-study information in…

Integrating machine learning (ML) methods in educational research has the potential to greatly impact upon research, teaching, learning and assessment by enabling personalised learning, adaptive assessment and providing insights into student performance, progress and learning patterns. To reveal more about this notion, we investigated ML…

In this work, we introduce a novel oversampling technique, the theory of inheritance and Gower distance-based oversampling (TIGO) method, designed to address class imbalance issues in mixed categorical and continuous variables data set. Drawing inspiration from genetic inheritance principles, TIGO synthesizes new minority class data,…

Text and data mining activities -- that is, the automated processing of digital materials to uncover new knowledge -- have become more frequent in all areas of scientific research. Because they require a massive use of copyrighted work, there are evident conflicts with copyright legislation. Countries at the forefront of research and development…

I propose two practical advances to the argument-based approach to validity: developing a living document and incorporating preregistration. First, I present a potential structure for the living document that includes an up-to-date summary of the validity argument. As the validation process may span across multiple studies, the living document…

The paper argues that learning analytics as a research field can benefit from a theory-informed shared language to describe sensemaking of learning and teaching data. To make the case for such shared language, first, I critically review prominent sensemaking theories to then demonstrate how studies in learning analytics do not use coherent…