Qualitative comparative analysis (QCA) is an influential methodological approach motivated by set theory and boolean logic. QCA proponents have developed algorithms to analyze quantitative data, in a bid to uncover necessary and sufficient conditions where causal relationships are complex, conditional, or asymmetric. This article uses computer…

One-to-one lessons based on the master-apprentice model are recognised in research and practice as an indispensable foundation for the training of professional musicians including singers. Given its primary importance to musician training, it is essential that researchers of this pedagogical model adopt methodologies and methods well-suited to…

We explored the possibility of publication bias in the sleep and explicit motor sequence learning literature by applying precision effect test (PET) and precision effect test with standard errors (PEESE) weighted regression analyses to the 88 effect sizes from a recent comprehensive literature review (Pan & Rickard, 2015). Basic PET analysis…

Categorical data become increasingly ubiquitous in the modern big data era. In this dissertation, we propose novel statistical learning and inference methods for large-scale categorical data, focusing on latent variable models and their applications to psychometrics. In psychometric assessments, the subjects' underlying aptitude often cannot be…

There is accumulating evidence that readers continually evaluate the consistency, congruence, and coherence of text by processes of validation. Validation is initiated immediately on stimulus presentation, may proceed nonstrategically, and serves as a criterion for representational updating. However, validation exhibits a variety of deficiencies.…

Ethics review of research involving humans has become something of an institution in recent years. It is intended to protect participants from harm and, to that end, follows rigorous standards. Given recent changes in research methodologies utilized in medical research, it may be that ethics review for some kinds of studies needs to be reexamined.…

Regression mixture models are a statistical approach used for estimating heterogeneity in effects. This study investigates the impact of sample size on regression mixture's ability to produce "stable" results. Monte Carlo simulations and analysis of resamples from an application data set were used to illustrate the types of problems that…

Collecting data for cross-cultural research is time consuming and expensive. We report on techniques for efficient and effective cross-cultural data collection, drawn from 18 cross-cultural studies we conducted in 22 countries. We discuss research design, site selection and collaboration building, ethical review, cross-site protocol design, data…

The aim of this paper is to introduce a software that is appropriate for the generalizability theory for not only balanced but also unbalanced data sets. Because it is possible to have unbalanced data sets while conducting a study, the researchers have devised an easy solution, other than deleting data, to balance the design to cope with this…

This article presents the MERITS Plus model, a conceptual framework developed during qualitative research into the process of academic transition and the impact of educational choices upon learner identity. The article considers some of the methodological challenges faced by qualitative researchers, and how effective the use of a conceptual…

The process of pairing a name with representations or peculiar properties permeates many mathematics classroom situations. In school, many practices go under the label 'definition', even though they can be very different from what mathematicians conceive as a formal definition, and in fact there are substantial differences between these different…

Education researchers are increasingly interested in applying data mining approaches, but to date, there has been no overarching exposition of their methodological advantages and disadvantages to the field. This is partly because the use of data mining in education research is relatively new, so its value and consequences are not yet well…

This study investigates the performance of robust maximum likelihood (ML) estimators when fitting and evaluating small sample latent growth models with non-normal missing data. Results showed that the robust ML methods could be used to account for non-normality even when the sample size is very small (e.g., N < 100). Among the robust ML…

Hofmann and Holm's (2019) recent survey on issues of research misconduct with PhD graduates culminated with a notable conclusion by the authors: 'Scientific misconduct seems to be an environmental issue as much as a matter of personal integrity'. Here, we re-emphasise the usefulness of an education-based countermeasure against toxic research…

An increased focus on transparency and replication in science has stimulated reform in research practices and dissemination. As a result, the research culture is changing: the use of preregistration is on the rise, access to data and materials is increasing, and large-scale replication studies are more common. In this article, I discuss two…