Excellence in research is essential for advancing knowledge, fostering innovation, and addressing societal challenges. This article proposes the INDEX Strategy Framework as a structured, evidence-based guide to optimize the research process. The framework encompasses five critical phases: Identify Focus Areas, Network and Collaborate, Design…

Purpose: Lesson study (LS) is a collaborative form of action research. Collaboration is central to LS methodology, therefore exploring and expanding the understanding of the collaborative features that occur in LS is a priority. This paper explores the features of collaboration in existing publications on LS to consider if, as Quaresma (2020)…

The purpose of this qualitative meta-analysis (QMA) is to provide a concise and comprehensive picture of findings across qualitative studies to answer this question: What factors contribute to systematically closing the opportunity gap for all students, and particularly for students labelled linguistically and culturally diverse? The ultimate goal…

The Israeli contemporary artist, psychoanalyst, philosopher and aesthetics theorist, Bracha L. Ettinger, has made significant impacts with her "Ettingerian Matrixial Theory" since the early 1980s. This feminine-centric post-Lacanian theorizing has been taken up by many scholars and practitioners across diverse countries and disciplines…

This study designed a localized approach to working and writing action research suited for basic education. The researchers used multiphase mixed method research with three analysis stages focused on the identified problem. These stages include identifying the preferred approach in writing action research for basic education, designing a localized…

Purpose: Miniature linguistic systems (also known as matrix training) is a method of organizing learning targets to achieve generative learning or recombinative generalization. This systematic review is aimed at determining whether matrix training is effective for individuals with autism spectrum disorder (ASD) in terms of improving recombinative…

When fitting hierarchical regression models, maximum likelihood (ML) estimation has computational (and, for some users, philosophical) advantages compared to full Bayesian inference, but when the number of groups is small, estimates of the covariance matrix (S) of group-level varying coefficients are often degenerate. One can do better, even from…

When fitting hierarchical regression models, maximum likelihood (ML) estimation has computational (and, for some users, philosophical) advantages compared to full Bayesian inference, but when the number of groups is small, estimates of the covariance matrix [sigma] of group-level varying coefficients are often degenerate. One can do better, even…

Many educational data mining studies have explored methods for discovering cognitive models and have emphasized improving prediction accuracy. Too few studies have "closed the loop" by applying discovered models toward improving instruction and testing whether proposed improvements achieve higher student outcomes. We claim that such…

The uses and methodology of factor analysis are widely debated and discussed, especially the issues of rotational use, methods of confirmatory factor analysis, and adequate sample size. The variety of perspectives and often conflicting opinions can lead to confusion among researchers about best practices for using factor analysis. The focus of the…

Emerging technologies offer an opportunity for the development, at the institutional level, of quality processes with greater capacity to enhance learning in higher education than available through current quality processes. These systems offer the potential to extend use of learning analytics in institutional-level quality processes in addition…

In this literature review, we examined 30 years of play-literacy inquiry through a quantitative lens in order to identify, assemble and summarize studies of sufficient methodological strength to form a corpus of research that encourages meta-analytic thinking. First, a multi-phase search of the literature was conducting yielding 192 studies that…

Introductory thermodynamics is a topic which is covered in a wide variety of science and engineering educations. However, very different teaching traditions have evolved within different scientific specialties. In this study we examine three courses in introductory thermodynamics within three different scientific specialties: physics, chemical…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…