Traditional validation approaches fail to account for the ways oppressive systems (e.g. racism, radical nationalism) impact the test design and development process. To disrupt this legacy of white supremacy, we illustrate how justice-oriented, antiracist validation (JAV) framework can be applied to construct articulation and validation, data…

Participatory modeling (PM) is an engaged research methodology for creating analog or computer-based models of complex systems, such as socio-environmental systems. Used across a range of fields, PM centers stakeholder knowledge and participation to create more internally valid models that can inform policy and increase engagement and trust…

Cognitive diagnosis models (CDMs) allow for the extraction of fine-grained, multidimensional diagnostic information from appropriately designed tests. In recent years, interest in such models has grown as formative assessment grows in popularity. Many dichotomous as well as several polytomous CDMs have been proposed in the last two decades, but…

Drawing upon his experience, more than 60 years ago, as a psychometric support person to a very special teacher of brain damaged children, the author of this article reflects on the productive use of educational assessments and data from them to educate - assessment in the service of learning. Findings from the Gordon Commission on the Future of…

Data analysis is a significant methodological component when conducting quantitative education studies. Guidelines for conducting data analyses in quantitative education studies are common but often underemphasize four important methodological components impacting the validity of inferences: quality of constructed measures, proper handling of…

Knowledge tracing is a fundamental area of educational data modeling that aims at gaining a better understanding of the learning occurring in tutoring systems. Knowledge tracing models fit various parameters on observed student performance and are evaluated through several goodness of fit metrics. Fitted parameter values are of crucial interest in…

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…

This study proposes a structured constructs model (SCM) to examine measurement in the context of a multidimensional learning progression (LP). The LP is assumed to have features that go beyond a typical multidimentional IRT model, in that there are hypothesized to be certain cross-dimensional linkages that correspond to requirements between the…

Quantitative research on sexual minority youths (SMYs) has likely contributed to misperceptions about the risk and deviance of this population. In part because it often relies on self-reported data from population-based self-administered questionnaires, this research is susceptible to misclassification bias whereby youths who are not SMYs are…

A great deal of research in educational data mining is geared towards predicting student performance. Bayesian Knowledge Tracing, Performance Factors Analysis, and the different variations of these have been introduced and have had some success at predicting student knowledge. It is worth noting, however, that very little has been done to…

Automatic assessment of dialogic properties of classroom discourse would benefit several widespread classroom observation protocols. However, in classrooms with low incidences of dialogic discourse, assessment can be highly biased against detecting dialogic properties. In this paper, we present an approach to addressing this imbalanced class…

This discussion paper for this special issue examines co-regulation of learning in computer-supported collaborative learning (CSCL) environments extending research on self-regulated learning in computer-based environments. The discussion employs a socio-cognitive perspective focusing on social and collective views of learning to examine how…

This paper addresses a relatively unexplored area in the field of learning analytics: how analytics are taken up and used as part of teaching and learning processes. Initial steps are taken towards developing design knowledge for this "middle space," with a focus on students as analytics users. First, a core set of challenges for…

With the widespread use of learning analytics (LA) tools, there is a need to explore how these technologies can be used to enhance teaching and learning. Little research has been conducted on what human processes are necessary to facilitate meaningful adoption of LA. The research problem is that there is a lack of evidence-based guidance on how…

With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…