Decision consistency (DC) is the reliability of a classification decision based on a test score. In professional credentialing, the decision is often a high-stakes pass/fail decision. The current methods for estimating DC are computationally complex. The purpose of this research is to provide a computationally and conceptually simple method for…

This review covers the core concepts and design decisions of TensorFlow. TensorFlow, originally created by researchers at Google, is the most popular one among the plethora of deep learning libraries. In the field of deep learning, neural networks have achieved tremendous success and gained wide popularity in various areas. This family of models…

Nondichotomous response models have been of greater interest in recent years due to the increasing use of different scoring methods and various performance measures. As an important alternative to dichotomous scoring, the use of continuous response formats has been found in the literature. To assess finer-grained skills or attributes and to…

Research shows that frequent, high-quality mathematics talk that is shared between parents and children can increase mathematics achievement. This article describes ways in which teachers can support parents in increasing the frequency and quality of parent-child mathematics interactions, leading to better outcomes for students.

Whenever classification decisions are made on educational tests, such as pass/fail, or basic, proficient, or advanced, the consistency and accuracy of those decisions should be estimated and reported. Methods for estimating the reliability of classification decisions made on the basis of educational tests are well-established (e.g., Rudner, 2001;…

There are two main lines of research in estimating classification accuracy (CA) and classification consistency (CC) under Item Response Theory (IRT). The R package cacIRT provides computer implementations of both approaches in an accessible and unified framework. Even with available implementations, there remains decisions a researcher faces when…

This classroom activity is designed to help students practice calculating percentiles. The approach of the activity involves physical sorting and full classroom participation in each calculation. The design encourages a more engaged approach than simply having students make a calculation with numbers on a paper.

The Reduced Reparameterized Unified Model (Reduced RUM) is a diagnostic classification model for educational assessment that has received considerable attention among psychometricians. However, the computational options for researchers and practitioners who wish to use the Reduced RUM in their work, but do not feel comfortable writing their own…

The recent surge of interests in cognitive assessment has led to developments of novel statistical models for diagnostic classification. Central to many such models is the well-known "Q"-matrix, which specifies the item-attribute relationships. This article proposes a data-driven approach to identification of the "Q"-matrix and…

Test scores are commonly reported in a small number of ordered categories. Examples of such reporting include state accountability testing, Advanced Placement tests, and English proficiency tests. This paper introduces and evaluates methods for estimating achievement gaps on a familiar standard-deviation-unit metric using data from these ordered…

Test scores are commonly reported in a small number of ordered categories. Examples of such reporting include state accountability testing, Advanced Placement tests, and English proficiency tests. This article introduces and evaluates methods for estimating achievement gaps on a familiar standard-deviation-unit metric using data from these ordered…

Diagnostic classification models (aka cognitive or skills diagnosis models) have shown great promise for evaluating mastery on a multidimensional profile of skills as assessed through examinee responses, but continued development and application of these models has been hindered by a lack of readily available software. In this article we…

This article describes a comprehensive and novel approach to assessment in early numeracy. Topics include the significance of early numeracy, developing a nomenclature for early numeracy, and describing the context for the development of this approach to assessment. The largely unrealised importance of numerals and numeral sequences in early…

Computational models are tools for testing mechanistic theories of learning and development. Formal models allow us to instantiate theories of cognitive development in computer simulations. Model behavior can then be compared to real performance. Connectionist models, loosely based on neural information processing, have been successful in…

The First Grade Pre-Screening is designed to be used at the start of the first grade school year so that teachers can obtain information about their incoming students. This information is intended to give teachers insight about what math and reading skills a student may or may not have at the beginning of the year. The information can aid teachers…