Recent investigations on how people derive meaning from language have focused on task-dependent shifts between two cognitive systems. The symbolic (amodal) system represents meaning as the statistical relationships between words. The embodied (modal) system represents meaning through neurocognitive simulation of perceptual or sensorimotor systems…

This article provides a conceptual framework for considering both the theoretical and methodological factors that underpin the successful validation of a competency framework. Drawing on educational assessment literature, this article argues that a valid competency framework relates to an interpretive judgement of the credibility of the claims…

This article presents the consensus of an National Council on Measurement in Education Presidential Task Force on Foundational Competencies in Educational Measurement. Foundational competencies are those that support future development of additional professional and disciplinary competencies. The authors develop a framework for foundational…

To improve the validity of self-report measures, researchers should control for response style (RS) effects, which can be achieved with IRTree models. A traditional IRTree model considers a response as a combination of distinct decision-making processes, where the substantive trait affects the decision on response direction, while decisions about…

Bayesian Knowledge Tracing, a model used for cognitive mastery estimation, has been a hallmark of adaptive learning research and an integral component of deployed intelligent tutoring systems (ITS). In this paper, we provide a brief history of knowledge tracing model research and introduce pyBKT, an accessible and computationally efficient library…

In recent years, some models for binary and graded format responses have been proposed to assess unipolar variables or "quasi-traits." These studies have mainly focused on clinical variables that have traditionally been treated as bipolar traits. In the present study, we have made a proposal for unipolar traits measured with continuous…

Cognitive diagnosis models (CDMs) are latent class multidimensional statistical models that help classify people accurately by using a set of discrete latent variables, commonly referred to as attributes. These models require a Q-matrix that indicates the attributes involved in each item. A potential problem is that the Q-matrix construction…

This study aimed to address the need for a comprehensive assessment tool to evaluate the mathematical abilities of first-grade students through cognitive diagnostic assessment (CDA). The primary challenge involved in this endeavor was to delineate the specific cognitive skills and sub-skills pertinent to first-grade mathematics (FG-M) and to…

Acid-base chemistry is a key reaction motif taught in postsecondary organic chemistry courses. More specifically, concepts from the Lewis acid-base model are broadly applicable to understanding mechanistic ideas such as electron density, nucleophilicity, and electrophilicity; thus, the Lewis model is fundamental to explaining an array of reaction…

To draw valid and reliable conclusions from child studies involving facial expressions, well-controlled and validated (child) facial stimuli are necessary. The current study is the first to validate the facial emotional expressions of child models in school-aged children. In this study, we validated the Radboud Faces Database child models in a…

Theories of grounded and embodied cognition offer a range of accounts of how reasoning and body-based processes are related to each other. To advance theories of grounded and embodied cognition, we explore the "cognitive relevance" of particular body states to associated math concepts. We test competing models of action-cognition…

Theories of grounded and embodied cognition offer a range of accounts of how reasoning and body-based processes are related to each other. To advance theories of grounded and embodied cognition, we explore the "cognitive relevance" of particular body states to associated math concepts. We test competing models of action-cognition…

In recent years, there has been a proliferation of adaptive learner models that seek to predict student correctness. Improvements on earlier models have shown that separate predictors for prior successes, failures, and recent performance further improve fit while remaining interpretable. However, students who engage in "gaming" or other…

In recent years, there has been a proliferation of adaptive learner models that seek to predict student correctness. Improvements on earlier models have shown that separate predictors for prior successes, failures, and recent performance further improve fit while remaining interpretable. However, students who engage in "gaming" or other…

Automated scoring of free drawings or images as responses has yet to be used in large-scale assessments of student achievement. In this study, we propose artificial neural networks to classify these types of graphical responses from a TIMSS 2019 item. We are comparing classification accuracy of convolutional and feed-forward approaches. Our…