To identify the ways teachers and educational systems can improve learning, researchers need to make causal inferences. Analyses of existing datasets play an important role in detecting causal patterns, but conducting experiments also plays an indispensable role in this research. In this article, we advocate for experiments to be embedded in real…

The chapters in this online volume comprise the TIMSS & PIRLS International Study Center's technical report of the methods and procedures used to develop, implement, and report the results of TIMSS 2019. There were various technical challenges because TIMSS 2019 was the initial phase of the transition to eTIMSS, with approximately half the…

This exploratory analysis of smart partnerships identifies the risk of increasing the digital divide with the deployment of data analytics. Smart partnerships in education appear to include a process of evolution into a synergy of strategic and holistic approaches that enhance the quality of education with digital technologies, harnessing ICT…

Assessing complex constructs such as those discussed under the umbrella of 21st century constructs highlights the need for a principled assessment design and validation approach. In our discussion, we made a case for three considerations: (a) taking construct complexity into account across various stages of assessment development such as the…

Previous investigations on the subjective scale of numerical representations assumed that the scale type can be inferred directly from stimulus-response mapping. This is not a valid assumption, as mapping from the subjective scale into behavior may be nonlinear and/or distorted by response bias. Here we present a method for differentiating between…

Analyzing a conference, especially one as young and focused as LAK, provides the opportunity to observe the structure and contributions of the scientific community around it. This work will perform a Scientometric analysis, coupled with a more in-depth manual content analysis, to extract this insight from the proceedings and program of LAK 2013.…

When using IRT models in Educational Achievement Testing, the model is as a rule too simple to catch all the relevant dimensions in the test. It is argued that a simple model may nevertheless be useful but that it can be complemented with additional analyses. Such an analysis, called profile analysis, is proposed and applied to the reading data of…

In this paper, we propose a cluster-MDS model for two-way one-mode continuous rating dissimilarity data. The model aims at partitioning the objects into classes and simultaneously representing the cluster centers in a low-dimensional space. Under the normal distribution assumption, a latent class model is developed in terms of the set of…

Introduction: The main purpose of this study is to explore the correlation between dimensions of perfectionism and self-concepts among school aged students in Egypt. Method: Two hundred-eighty four children (fifth and sixth graders) participated in this study. The mean age of the participants was 144.37 months, SD 6.36. Pearson correlation…

Using the cluster generation procedure proposed by D. Steinley and R. Henson (2005), the author investigated the performance of K-means clustering under the following scenarios: (a) different probabilities of cluster overlap; (b) different types of cluster overlap; (c) varying samples sizes, clusters, and dimensions; (d) different multivariate…

Alternating least squares and optimal scaling are presented as two approaches to the quantitative analysis of qualitative data. A variety of statistical approaches to this problem are discussed. Three examples are presented. (JKS)

Attachment Q-Sort (AQS) is a tool for quantifying observations about toddler/caregiver relationships. Previous studies have applied factor analysis to the full 90 AQS item set to explore the structure underlying them. Here we explore that structure by applying multidimensional scaling (MDS) to judgements of inter-item similarity. AQS items are…

TSCALE, a multidimensional scaling procedure based on the contrast model of A. Tversky for asymmetric three-way, two-mode proximity data, is presented. TSCALE conceptualizes a latent dimensional structure to describe the judgmental stimuli. A Monte Carlo analysis and two consumer psychology applications illustrate the procedure. (SLD)

A latent-class scaling approach is presented for modeling paired comparison and "pick any/t" data obtained in preference studies. The utility of this approach is demonstrated through analysis of data from studies involving consumer preference and preference for political candidates. (SLD)

Given "T" joint observations on "K" variables, it is frequently useful to consider the weighted average or scaled score. L-scaling is introduced as a technique for determining the weights. The technique is so named because of its resemblance to the Leontief matrix of mathematical economics. L-scaling is compared to two…