
Matthew J. MadisonUniversity of Georgia | UGA · Department of Educational Psychology
Matthew J. Madison
About
18
Publications
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Introduction
I'm an assistant professor of quantitative methodology at the University of Georgia. My research goals lie in the advancement of multivariate psychometric models. Specifically, I have focused my research on a class of contemporary item response models called diagnostic classification models (DCMs). In addition to methodological research, I collaborate with applied researchers to use DCMs and other psychometric models to answer critical questions in educational contexts.
www.matthewmadison.com
Skills and Expertise
Publications
Publications (18)
Introduction
Diagnostic classification models (DCMs) have received increasing attention in cross-sectional studies. However, L2 learning studies, tracking skill development over time, require models suited for longitudinal analyses. Growth DCMs offer a promising framework for such analyses.
Method
This study utilizes writing data from two learner...
What are foundational competencies in educational measurement? We published a framework for these foundational competencies in this journal (Ackerman et al. 2024) and were grateful to receive eight commentaries raising a number of important questions about the framework and its implications. We identified five cross‐cutting recommendations among th...
Diagnostic classification models (DCMs) have grown in popularity as stakeholders increasingly desire actionable information related to students’ skill competencies. Longitudinal DCMs offer a psychometric framework for providing estimates of students’ proficiency status transitions over time. For both cross-sectional and longitudinal DCMs, it is imp...
Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or nonproficiency of specified latent characteristics. These models are well suited for providing diagnostic and actionable feedback to support intermediate and formative assessment efforts. Several DCMs have been developed...
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 compete...
Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or non-proficiency of specified latent characteristics. These models are well-suited for providing diagnostic and actionable feedback to support formative assessment efforts. Several DCMs have been developed and applied in d...
Recent developments have enabled the modeling of longitudinal assessment data in a diagnostic classification model (DCM) framework. These longitudinal DCMs were developed to provide measures of student growth on a discrete scale in the form of attribute mastery transitions, thereby supporting categorical and criterion-referenced interpretations of...
Data science and computational thinking (CT) skills are important STEM literacies necessary to make informed daily decisions. In elementary schools, particularly in rural areas, there is little instruction and limited research towards understanding and developing these literacies. Using a Research-Practice Partnership model (RPP; Coburn & Penuel, 2...
Research-Practice Partnerships (RPP) bridge the gap between schools and universities. However, few have embraced the co-design process through a communities of practice lens and investigated how knowledge is co-constructed and negotiated. This mixed-method study explored how elementary school teachers co-construct knowledge with researchers to unde...
Recent advances have enabled diagnostic classification models (DCMs) to accommodate longitudinal data. These longitudinal DCMs were developed to study how examinees change, or transition, between different attribute mastery statuses over time. This study examines using longitudinal DCMs as an approach to assessing growth and serves three purposes:...
A common assessment research design is the single-group pre-test/post-test design in which examinees are administered an assessment before instruction and then another assessment after instruction. In this type of study, the primary objective is to measure growth in examinees, individually and collectively. In an item response theory (IRT) framewor...
The evaluation of intervention effects is an important objective of educational research. One way to evaluate the effectiveness of an intervention is to conduct an experiment that assigns individuals to control and treatment groups. In the context of pretest/posttest designed studies, this is referred to as a control-group pretest/posttest design....
In item response theory (IRT), the invariance property states that item parameter estimates are independent of the examinee sample, and examinee ability estimates are independent of the test items. While this property has long been established and understood by the measurement community for IRT models, the same cannot be said for diagnostic classif...
Diagnostic classification models are psychometric models that aim to classify examinees according to their mastery or non-mastery of specified latent characteristics. These models are well-suited for providing diagnostic feedback on educational assessments because of their practical efficiency and increased reliability when compared with other mult...
The images portrayed in textbooks have the ability to influence students' beliefs about self, ethnicity, social class, and gender. Several studies in the 1970s and 1990s documented the lack of equity in mathematics textbooks with respect to gender; however, few studies have been conducted recently. Research with a focus on minority representation i...