This paper presents a model for developing research questions that are aligned to research aims for research design in e-learning. The model is proposed as a solution to the on-going problem of heterogeneity of research problems. The model is based on Burrell and Morgan's four social paradigms, and integrates four research aims, namely, explore,…

Research on disproportionate representation in special education has potential to influence policy in ways that rectify educational inequities. In this study, we investigated how disproportionality researchers have operationalized dis-ability, identified key themes and theories used in disproportionality research, and evaluated the coherence…

This report aims to showcase the value of implementing a Bayesian framework to analyse and report results from international large-scale surveys and provide guidance to users who want to analyse the data using this approach. The motivation for this report stems from the recognition that Bayesian statistical inference is fast becoming a popular…

Learner engagement correlates with important educational outcomes, including academic achievement and satisfaction. Although research is already exploring learner engagement in blended contexts, no theoretical framework guides inquiry or practice, and little consistency or specificity exists in engagement definitions and operationalizations.…

Standard models for network meta-analysis simultaneously estimate multiple relative treatment effects. In practice, after estimation, these multiple estimates usually pass through a formal or informal selection procedure, eg, when researchers draw conclusions about the effects of the best performing treatment in the network. In this paper, we…

There is strong evidence that children who attend high-quality pre-kindergarten (pre-K) programs learn skills that benefit them in school and life. The price tag of most private programs puts them out of reach for some families, however. In response, many states and school districts fund pre-K programs to expand opportunities for their youngest…

States and localities throughout the United States are expanding their investments in pre-kindergarten (pre-K) programs. Although spending on publicly funded pre-K programs is well documented, relatively less is known about the true cost to deliver the programs, especially considering varying quality standards and accounting for the resources used…

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…

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…

There is increased use of Bayesian networks (BN) in educational assessment. In psychometrics, BN serves as a measurement model with high flexibility, suitable to model educational assessment data with a complex structure. BN is a novel psychometric approach and not all aspects of its application are well-known. The article aims to provide the…

This dissertation developed a new learner corpus of Japanese and introduced an error and linguistic annotation scheme specifically designed for Japanese particles. The corpus contains texts written by learners who are in the first year to fourth year university level Japanese courses. The texts in the corpus were tagged with part-of-speech and…

We encounter variables with little variation often in educational data mining (EDM) due to the demographics of higher education and the questions we ask. Yet, little work has examined how to analyze such data. Therefore, we conducted a simulation study using logistic regression, penalized regression, and random forest. We systematically varied the…

Connecting teachers' perspectives with their practice is an enduring challenge shaping what and how we understand teaching. Researchers tend to bifurcate teachers' work between their private and their public lives. These "worlds" bring particular meanings that are rendered through the analyses of visual documentations of teaching and…

We sought to apply natural language processing to the task of automatic risk of bias assessment in preclinical literature, which could speed the process of systematic review, provide information to guide research improvement activity, and support translation from preclinical to clinical research. We use 7840 full-text publications describing…

The unstructured multiple-attempt (MA) item response data in virtual learning environments (VLEs) are often from student-selected assessment data sets, which include missing data, single-attempt responses, multiple-attempt responses, and unknown growth ability across attempts, leading to a complex and complicated scenario for using this kind of…