The fear of technology replacing jobs can be traced back to Aristotle, who, before great technological advances existed, ventured that machines may one day end the need for human labor (Campa 2014). In the current era, there is overwhelming evidence of technological unemployment. This evidence comes in the form of jobs that were once common, but…

This paper reports on an approximate or partial replication of a study by Salsbury, Crossley & McNamara (2011) that examined the longitudinal developmental of a number of core lexical features related to word imageability, concreteness, familiarity, and meaningfulness in a spoken corpus of English second language (L2) learners. Salsbury et al.…

Indices of lexical diversity have been used to estimate the size of a writer's vocabulary and/or a writer's lexical proficiency for some time. One issue with many commonly used indices of lexical diversity (e.g., TTR and index) is that they vary as a function of text length. Accordingly, much research has been devoted to the development of indices…

Lexical items that are encountered more frequently and in varying contexts have important effects on second language (L2) development because frequent and contextually diverse words are learned faster and become more entrenched in a learner's lexicon (Ellis 2002a, b). Despite evidence that L2 learners are generally exposed to non-native input,…

Limited health literacy is a barrier to optimal healthcare delivery and outcomes. Current measures requiring patients to self-report limitations are time-consuming and may be considered intrusive by some. This makes widespread classification of patient health literacy challenging. The objective of this study was to develop and validate…

This study investigates the relative efficacy of using linguistic micro-features, the aggregation of such features, and a combination of micro-features and aggregated features in developing automatic essay scoring (AES) models. Although the use of aggregated features is widespread in AES systems (e.g., e-rater; Intellimetric), very little…

Objective: To develop novel, scalable, and valid literacy profiles for identifying limited health literacy patients by harnessing natural language processing. Data Source: With respect to the linguistic content, we analyzed 283 216 secure messages sent by 6941 diabetes patients to physicians within an integrated system's electronic portal.…

A corpus of 313 freshman college essays was analyzed in order to better understand the forms and functions of humor in academic writing. Human ratings of humor and wordplay were statistically aggregated using Factor Analysis to provide an overall "Humor" component score for each essay in the corpus. In addition, the essays were also…

Research has identified a number of linguistic features that influence the reading comprehension of young readers; yet, less is known about whether and how these findings extend to adult readers. This study examines text comprehension, processing, and familiarity judgment provided by adult readers using a number of different approaches (i.e.,…

The current study examined the effects of text-based relational (i.e., cohesion), propositional-specific (i.e., lexical), and syntactic features in a source text on subsequent integration of the source text in spoken responses. It further investigated the effects of word integration on human ratings of speaking performance while taking into…

This study examines frequency, contextual diversity, and contextual distinctiveness effects in predicting produced versus not-produced frequent nouns and verbs by early second language (L2) learners of English. The study analyzes whether word frequency is the strongest predictor of early L2 word production independent of contextual diversity and…

This study investigates the potential for linguistic microfeatures related to length, complexity, cohesion, relevance, topic, and rhetorical style to predict L2 writing proficiency. Computational indices were calculated by two automated text analysis tools (Coh- Metrix and the Writing Assessment Tool) and used to predict human essay ratings in a…

This paper provides an agenda for replication studies focusing on second language (L2) writing and the use of natural language processing (NLP) tools and machine learning algorithms. Specifically, it introduces a range of the available NLP tools and machine learning algorithms and demonstrates how these could be used to replicate seminal studies…

This study investigates a novel approach to automatically assessing essay quality that combines natural language processing approaches that assess text features with approaches that assess individual differences in writers such as demographic information, standardized test scores, and survey results. The results demonstrate that combining text…

This study identifies multiple profiles of successful essays via a cluster analysis approach using linguistic features reported by a variety of natural language processing tools. The findings from the study indicate that there are four profiles of successful writers for the samples analyzed. These four profiles are linguistically distinct from one…