The history of vocabulary research has specified a rich and complex construct, resulting in calls for vocabulary research, assessment, and instruction to take into account the complex problem space of vocabulary. At the intersection of vocabulary theory and assessment modeling, this paper suggests a suite of modeling techniques that model the…

The history of vocabulary research has specified a rich and complex construct, resulting in calls for vocabulary research, assessment, and instruction to take into account the complex problem space of vocabulary. At the intersection of vocabulary theory and assessment modeling, this paper suggests a suite of modeling techniques that model the…

The pseudoword effect is the finding that pseudowords (i.e., rare words or pronounceable nonwords) give rise to more hits and false alarms than words. Using the retrieving effectively from memory (REM) model of recognition memory, we tested a familiarity-based account of the pseudoword effect: Specifically, the pseudoword effect arises because…

There is growing interest in the use of semantic collections in order to identify and analyse domain knowledge. This paper describes some technical issues to consider when contemplating research which incorporates small-to-medium domain-specific word sets. The purpose of the corpus construction described was to provide an external word collection…

Plaut and Booth developed a distributed connectionist model of written word comprehension and evaluated it against empirical findings on individual and developmental differences in semantic priming in visual lexical decision. Borowsky and Besner raised a number of challenges for this model. First, the model was not shown to be capable of…

This article presents a theory of visual word recognition that assumes that, in the tasks of word identification, lexical decision, and semantic categorization, human readers behave as optimal Bayesian decision makers. This leads to the development of a computational model of word recognition, the Bayesian reader. The Bayesian reader successfully…

Previous work indicates that semantic categorization decisions for nonexemplars (e.g., deciding that TURBAN is not an animal name) are faster for high-frequency words than low-frequency words. However, there is evidence that this result might depend on category size. When narrow categories are used (e.g., Months, Numbers), there is no frequency…

Reports on the development of a prototype computerized abstractor's assistant called TEXNET, a text network management system. Features of the system discussed include semantic dependency links; displays of text structure; basic text editing; extracting; weighting methods; and listings of frequent words. (Contains 25 references.) (LRW)

D. C. Plaut and J. R. Booth presented a parallel distributed processing model that purports to simulate human lexical decision performance. This model (and D. C. Plaut, 1995) offers a single mechanism account of the pattern of factor effects on reaction time (RT) between semantic priming, word frequency, and stimulus quality without requiring a…

This article contrasts aphasic patients' performance of word naming and lexical decision with that of intact college-aged readers. We discuss this contrast within a framework of self-organization; word recognition by aphasic patients is destabilized relative to intact performance. Less stable performance shows itself as an increase in the…

This working paper summarizes the results of an expert panel review of the Lexile Framework (LF). The review was conducted by five panel members through readings, the preparation of brief individual reports, and participation in a meeting held on April 26, 2001 in Washington, D.C. The list of panel members and invited observers, along with brief…

Considers previous research and data regarding the relative frequencies of a wide variety of lexical items expressing doubt and certainty in written and spoken corpuses and uses the data to evaluate the adequacy of some well-known English as a second language textbooks. (Author/CB)

Compares the success of lexical statistics, content analysis, and function words in determining the true author of "The Federalist." The function word approach proved most successful in attributing the papers to James Madison. Lexical statistics contributed nothing, while content analytic measures resulted in some success. (MJP)