Open-ended questions in mathematics are commonly used by teachers to monitor and assess students' deeper conceptual understanding of content. Student answers to these types of questions often exhibit a combination of language, drawn diagrams and tables, and mathematical formulas and expressions that supply teachers with insight into the processes…

Process Analysis is an emerging approach to discover meaningful knowledge from temporal educational data. The study presented in this paper shows how we used Process Analysis methods on the National Assessment of Educational Progress (NAEP) test data for modeling and predicting student test-taking behavior. Our process-oriented data exploration…

Background: In low-stakes educational assessments, test takers might show a performance decline (PD) on end-of-test items. PD is a concern in educational assessments, especially when groups of students are to be compared on the proficiency variable because item responses gathered in the groups could be differently affected by PD. In order to…

This study explores student attitudes to the use of substantive on-line assessments that require mathematical answers. Since there is limited guidance available for their use in a university setting, our goal is to learn what are the important aspects in student acceptance of e-assessments that support learning of mathematical subjects in higher…

This article presents a new perspective on measuring gender differences in the large-scale assessment study Trends in International Science Study (TIMSS). The suggested empirical model is directly based on the theoretical competence model of the domain mathematics and thus includes the interaction between content and cognitive sub-competencies.…

We present a logistic function of a monotonic polynomial with a lower asymptote, allowing additional flexibility beyond the three-parameter logistic model. We develop a maximum marginal likelihood based approach to estimate the item parameters. The new item response model is demonstrated on math assessment data from a state, and a computationally…

The present study aimed to represent the innovative assessments that support students' learning in STEM education through using the integrative framework for Cognitive Diagnostic Modeling (CDM). This framework is based on three components, cognition, observation, and interpretation (National Research Council, 2001). Specifically, this dissertation…

In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…

This study examines student growth on mathematics and reading assessments across academic years (Spring 2006 through Spring 2009) using three different growth models: hierarchical linear model (HLM), value-added model (VAM), and student growth percentile model (SGP). Comparisons across these three growth models were conducted to investigate the…

Mixture item response theory models have been suggested as a potentially useful methodology for identifying latent groups formed along secondary, possibly nuisance dimensions. In this article, we describe a multilevel mixture item response theory (IRT) model (MMixIRTM) that allows for the possibility that this nuisance dimensionality may function…

The purpose of this study was to investigate the relationship between student mathematics performance of 4th, 8th, and 11th grade students in Nebraska and the mode of test administration, online and paper-pencil. Schools were allowed to select the mode of test administration for their school with some exceptions for students needing…

Significant momentum exists for next-generation assessments to increasingly utilize technology to develop and deliver performance-based assessments. Many traditional challenges with this assessment approach still apply, including psychometric concerns related to performance-based tasks (PBTs), which include low reliability, efficiency of…

Mathematical word problems represent a common item format for assessing student competencies. Automatic item generation (AIG) is an effective way of constructing many items with predictable difficulties, based on a set of predefined task parameters. The current study presents a framework for the automatic generation of probability word problems…

The traditional kappa statistic in assessing interrater agreement is not adequate when multiraters and multiattributes are involved. In this article, latent trait models are proposed to assess the multirater multiattribute (MRMA) agreement. Data from the Third International Mathematics and Science Studies (TIMSS) are used to illustrate the…

The basis of test anxiety expressed by 219 university students (43 percent males) in a statistics course was explored, and a structural model was developed. The data indicated that anxiety felt for the statistics test differed from general test anxiety. The variables revealed as important by the model are discussed. (SLD)