We present a bias-adjusted three-step estimation approach for multilevel latent class models (LC) with covariates. The proposed approach involves (1) fitting a single-level measurement model while ignoring the multilevel structure, (2) assigning units to latent classes, and (3) fitting the multilevel model with the covariates while controlling for…

Educational assessment is inherently uncertain, where physiological, psychological and social factors play an important role in establishing judgements which are assumed to be "absolute". AI and other algorithmic approaches to grading of student work strip-out uncertainty, leading to a lack of inspectability in machine judgement and…

In recent years, proponents of configurational comparative methods (CCMs) have advanced various dimensions of robustness as instrumental to model selection. But these robustness considerations have not led to computable robustness measures, and they have typically been applied to the analysis of real-life data with unknown underlying causal…

In carrying out surveys involving sensitive characteristics, randomized response models have been considered among the best techniques since they provide the maximum privacy protection to the respondents and procure honest responses. Over the years, researchers have carried out studies on the estimation of proportions of the population possessing…

Higher education institutions (HEIs) have long embraced a path towards sustainability and engaged in supporting sustainable development. The adoption of the sustainability development goals has forced HEIs to assess how they engage with these goals and how they address societal challenges head on. However, the emergence of sustainability rankings…

Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be called random effects or…

As a research field geared toward understanding and improving learning, Learning Analytics (LA) must be able to provide empirical support for causal claims. However, as a highly applied field, tightly controlled randomized experiments are not always feasible nor desirable. Instead, researchers often rely on observational data, based on which they…

Research-based assessments (RBAs) measure how well a course achieves discipline-specific outcomes. Educators can use outcomes from RBAs to guide instructional choices and to request resources to implement and sustain instructional transformations. One challenge for using RBAs, however, is a lack of comparative data, particularly given the skew in…

In the literature on intercultural competence, such competence, or set of competencies, is desirable precisely because a globalized world needs world citizens who are at home everywhere and can deal effectively with alterity -- presumably in order to be agents of positive change. To remain relevant, we as teachers in German Studies need…

Researchers in many disciplines work with ranking data. This data type is unique in that it is often deterministic in nature (the ranks of items "k"-1 determine the rank of item "k"), and the difference in a pair of rank scores separated by "k" units is equivalent regardless of the actual values of the two ranks in…

Classroom assessment and large-scale assessment have, for the most part, existed in mutual isolation. Some experts have felt this is for the best and others have been concerned that the schism limits the potential contribution of both forms of assessment. Margaret Heritage has long been a champion of best practices in classroom assessment. Neal…

Analytic rubrics are promoted as important tools to assess learner performance and to improve learning outcomes. Rubrics, however, are not appropriate for every classroom assessment, particularly given the time and effort required to construct well-designed rubrics. In classroom assessment, instructors must balance the beneficial consequences of…

Comparative Judgement (CJ) has emerged as a technique that typically makes use of holistic judgement to assess difficult-to-specify constructs such as production (speaking and writing) in Modern Foreign Languages (MFL). In traditional approaches, markers assess candidates' work one-by-one in an absolute manner, assigning scores to different…

This article utilises theories, methods and tools from the fields of Social Psychology and Education to suggest new metrics for the analysis of competitive sport. The hope is that these metrics will encourage cooperation to exist alongside of the dominant feelings of competition. The main theory from Social Psychology involved here is Social…

The recent popularity of models that capture the dynamic coevolution of both network structure and behavior has driven the need for summary indices to assess the adequacy of these models to reproduce dynamic properties of scientific or practical importance. Whereas there are several existing indices for assessing the ability of the model to…