The authors describe a constructionist theory that accounts for the knowledge-based inferences that are constructed when readers comprehend narrative text. Readers potentially generate a rich variety of inferences when they construct a referential situation model of what the text is about. The proposed constructionist theory specifies that some, but not all, of this information is constructed under most conditions of comprehension. The distinctive assumptions of the constructionist theory embrace a principle of search (or effort) after meaning. According to this principle, readers attempt to construct a meaning representation that addresses the reader's goals, that is coherent at both local and global levels, and that explains why actions, events, and states are mentioned in the text. This study reviews empirical evidence that addresses this theory and contrasts it with alternative theoretical frameworks.

Advances in computational linguistics and discourse processing have made it possible to automate many language-and text-processing mechanisms. We have developed a computer tool called Coh-Metrix, which analyzes texts on over 200 measures of cohesion, language, and readability. Its modules use lexicons, part-of-speech classifiers, syntactic parsers, templates, corpora, latent semantic analysis, and other components that are widely used in computational linguistics. After the user enters an English text, CohMetrix returns measures requested by the user. In addition, a facility allows the user to store the results of these analyses in data files (such as Text, Excel, and SPSS). Standard text readability formulas scale texts on difficulty by relying on word length and sentence length, whereas Coh-Metrix is sensitive to cohesion relations, world knowledge, and language and discourse characteristics.

In this article, we propose and test a model of how readers construct representations of the situations described in simple narratives the event-indexing model According to the event-indexing model, events are the focal points of situations conveyed in narratives and are connected in memory along five dimensions time, space, protagonist, causality, and intentionality The results of a verb-clustering task provide strong support for the event-indexing model

Coh-Metrix is among the broadest and most sophisticated automated textual assessment tools available today. Automated Evaluation of Text and Discourse with Coh-Metrix describes this computational tool, as well as the wide range of language and discourse measures it provides. Part I of the book focuses on the theoretical perspectives that led to the development of Coh-Metrix, its measures, and empirical work that has been conducted using this approach. Part II shifts to the practical arena, describing how to use Coh-Metrix and how to analyze, interpret, and describe results. Coh-Metrix opens the door to a new paradigm of research that coordinates studies of language, corpus analysis, computational linguistics, education, and cognitive science. This tool empowers anyone with an interest in text to pursue a wide array of previously unanswerable research questions.

Several factors potentially influence the extent to which readers form a coherent mental representation during story comprehension. The main factors are argument overlap (i.e., connections between text constituents) and situational continuity (i.e., connections between the components of the referential situation model). The authors distinguished 3 dimensions of situational continuity: temporal, spatial, and causal continuity. Results of 2 reading-time studies involving naturalistic stories suggest that readers simultaneously monitor multiple dimensions of the situation model (particularly temporality and causality) under a normal reading instruction. In addition, the construction of a situation model does not critically depend on the presence or absence of argument overlap.