Best linear prediction (BLP) and penalized best linear prediction (PBLP) are techniques for combining sources of information to produce task scores, section scores, and composite test scores. The report examines issues to consider in operational implementation of BLP and PBLP in testing programs administered by ETS [Educational Testing Service].

In this research report, we describe the design and empirical findings for a large-scale study of essay writing ability with approximately 2,500 high school students in Germany and Switzerland on the basis of 2 tasks with 2 associated prompts, each from a standardized writing assessment whose scoring involved both human and automated components.…

In this study, we assessed the invariance in the factor structure underlying English-language proficiency for two groups of adolescent learners in Japan: students in middle school (ages 13-15 years) and students in high school (ages 16-18 years). Language proficiency was measured using the "TOEFL Junior"® Comprehensive test, an…

This report describes the initial automated scoring results that were obtained using the constructed responses from the Writing and Speaking sections of the pilot forms of the "TOEFL Junior"® Comprehensive test administered in late 2011. For all of the items except one (the edit item in the Writing section), existing automated scoring…

This study investigates the value of reporting the reading, listening, speaking, and writing section scores for the "TOEFL iBT"® test, focusing on 4 related aspects of the psychometric quality of the TOEFL iBT section scores: reliability of the section scores, dimensionality of the test, presence of distinct score profiles, and the…

This study assessed the invariance in the factor structure of the "Test of English as a Foreign Language"™ Internet-based test (TOEFL® iBT) across subgroups of test takers who differed in native language and exposure to the English language. The subgroups were defined by (a) Indo-European and Non-Indo-European language family, (b)…

This study examined the construct validity of the "e-rater"® automated essay scoring engine as an alternative to human scoring in the context of TOEFL® essay writing. Analyses were based on a sample of students who repeated the TOEFL within a short time period. Two "e-rater" scores were investigated in this study, the first…

Probabilistic models with more than one latent variable are designed to report profiles of skills or cognitive attributes. Testing programs want to offer additional information beyond what a single test score can provide using these skill profiles. Many recent approaches to skill profile models are limited to dichotomous data and have made use of…