Assessments of natural language can provide vast information about individuals' thoughts and cognitive process, but they often rely on time-intensive human scoring, deterring researchers from collecting these sources of data. Natural language processing (NLP) gives researchers the opportunity to implement automated textual analyses across a…

Survey instruments and assessments are frequently used in many domains of social science. When the constructs that these assessments try to measure become multifaceted, multidimensional item response theory (MIRT) provides a unified framework and convenient statistical tool for item analysis, calibration, and scoring. However, the computational…

In this study we developed and evaluated a crowdsourcing-based latent semantic analysis (LSA) approach to computerized summary scoring (CSS). LSA is a frequently used mathematical component in CSS, where LSA similarity represents the extent to which the to-be-graded target summary is similar to a model summary or a set of exemplar summaries.…

In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…

The Learning Target Rating Scale (LTRS) is a measure designed to evaluate the quality of teacher-developed learning targets for embedded instruction for early learning. In the present study, we examined the measurement dependability of LTRS scores by conducting a generalizability study (G-study). We used a partially nested, three-facet model to…

The framework and tools used for classroom assessment can have significant impacts on teacher practices and student achievement. Getting assessment right is an important component in creating positive learning experiences and academic success. Recent government reports (e.g., United States, Australia) call for the development of systems that use…

In this paper, we present a flexible full-information approach to modeling multiple userdefined response styles across multiple constructs of interest. The model is based on a novel parameterization of the multidimensional nominal response model that separates estimation of overall item slopes from the scoring functions (indicating the order of…

Assessing reading fluency is critical because it functions as an indicator of comprehension and overall reading achievement. Although theory and research demonstrate the importance of ORF proficiency, traditional ORF assessment practices are lacking as sensitive measures of progress for educators to make instructional decisions. The purpose of…

The standard scoring of the CLASS PreK produces three domain scores that are widely used in research, practice and policy. Despite these domains being based on developmental theory and research, limited empirical evidence exists for the three-domain structure as operationalized in the CLASS PreK. Using the 2009 and 2014 Head Start Family and Child…

The development of strong writing skills is a critical (and somewhat obvious) goal within the classroom. Individuals across the world are now expected to reach a high level of writing proficiency to achieve success in both academic settings and the workplace (Geiser & Studley, 2001; Powell, 2009; Sharp, 2007). Unfortunately, strong writing…

Recent advances in cognitive science and psychometrics have expanded the possibilities for the next generation of literacy assessment as an integrated domain (Bennett, 2011a; Deane, Sabatini, & O'Reilly, 2011; Leighton & Gierl, 2011; Sabatini, Albro, & O'Reilly, 2012). In this paper, we discuss four key areas supporting innovations in…

We propose a novel unsupervised extractive approach for summarizing online reviews by exploiting review helpfulness ratings. In addition to using the helpfulness ratings for review-level filtering, we suggest using them as the supervision of a topic model for sentence-level content scoring. The proposed method is metadata-driven, requiring no…

This study investigates a new approach to automatically assessing essay quality that combines traditional approaches based on assessing textual features with new approaches that measure student attributes such as demographic information, standardized test scores, and survey results. The results demonstrate that combining both text features and…