Knowing the Name of Something Versus Knowing Something Ye Wang (bio) Assessing Literacy in Deaf Individuals: Neurocognitive Measurement and Predictors. Donna Morere and Thomas Allen (Eds.). Springer, 2013. 268 pp. $129.00 (hardcover), $99.00 (e-book). The American physicist Richard Feynman once said, “I learned very early the difference between knowing the name of something and knowing something.” In an educational context, simply knowing a child’s label or diagnosis might not be the same as understanding the child’s experience or the areas where additional support might be needed. In the case of students who are d/Deaf or hard of hearing, then, can we predict a child’s literacy proficiency based on measures of hearing loss? That is, should we profile the literacy proficiency of students who are d/Deaf or hard of hearing based solely on their hearing loss? If hearing loss alone cannot fully predict the literacy proficiency of students who are d/Deaf or hard of hearing, what are other predictors? In Assessing Literacy in Deaf Individuals: Neurocognitive Measurement and Predictors, editors Donna Morere and Thomas Allen, along with a large group of contributing authors, describe and report the findings of a Toolkit project undertaken at the Science of Learning Center in Visual Language and Visual Learning (VL2), at Gallaudet University. The purpose of the Toolkit project was to investigate the predictors of literacy proficiency among a garden variety of cognitive, linguistic, and academic factors with 90 deaf Gallaudet students whose primary mode of communication was American Sign Language (ASL). It was one of the most comprehensive literacy measurements with the same group of deaf individuals to date. One of the most valuable contributions of the project was the wide range of predictors of literacy proficiency that were involved (see below). Chapters 1 and 2 of the book introduce the rationale for the Toolkit project, its procedures, and the background characteristics of the participants. Chapters 3–12 present the Toolkit measures from three major categories: cognitive functioning, academic achievement, and linguistic functioning. Each Toolkit measure is described, and a statistical analysis of the psychometric properties of the measure is provided. Chapter 13 presents the results of a factor analysis of the Toolkit measures, combining the results with data from the background questionnaire in an investigation of the interrelationships among the selected background characteristics and the participants’ performance on the psychometric measures. Factor analysis was used in the project (a) to reduce the wide range of measures in the Toolkit to a set of cohesive factors relating to cognition, achievement, and language; and (b) to detect underlying structure in the relationships among these factors and identify their potential role in the learning and development of the participants. The factor analysis of Toolkit measures revealed 10 factors related to literacy proficiency of the participants, ranging from 15.4% to 4.6% of the variance, in the following descending order: (1) letter and word knowledge, (2) academic fluency, (3) working memory/executive functioning, (4) speech-based phonology/short-term memory, (5) sign-based linguistic learning and memory, (6) visuospatial short-term memory, (7) visuospatial reasoning/nonverbal intelligence, (8) visuospatial working memory, (9) ASL-based retrieval, and (10) mental rotation. The project also included a multivariate analysis of variance to identify variables’ demonstrated multivariate significance in participants’ early communication and language experience. Predictably, early [End Page 468] exposure to spoken English, ASL, or both yielded significant boosts in multiple factors. Dishearteningly, however, only 5 of the 90 participants reported that they had learned both English and ASL before starting school. The findings confirm many long-standing conclusions about the general cognitive functioning of individuals who are d/Deaf or hard of hearing, the role of working memory in literacy and academic skill development, and the interrelationship between language and reading. For example, measures of general cognitive functioning suggested that the participants performed in a manner similar to hearing populations instead of demonstrating characteristics unique to deaf populations. Furthermore, measures of memory and learning revealed that all aspects of working memory were important for academic skill development. And, significantly for this population, reading in all of its forms, including word recognition, reading fluency, and text comprehension, was undoubtedly associated...