A computational model for simulating text comprehension (original) (raw)
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Toward a Model of Text Comprehension and Production
The semantic structure of texts can be described both at the local microlevel and at a more global macrolevel. A model for text comprehension based on this notion accounts for the formation of a coherent semantic text base in terms of a cyclical process constrained by limitations of working memory. Furthermore, the model includes macro-operators, whose purpose is to reduce the information in a text base to its gist, that is, the theoretical macrostructure. These operations are under the control of a schema, which is a theoretical formulation of the comprehender's goals. The macroprocesses are predictable only when the control schema can be made explicit. On the production side, the model is concerned with the generation of recall and summarization protocols. This process is partly reproductive and partly constructive, involving the inverse operation of the macro-operators. The model is applied to a paragraph from a psychological research report, and methods for the empirical testing of the model are developed. The main goal of this article is to describe the system of mental operations that underlie the processes occurring in text comprehension and in the production of recall and summariza-tion protocols. A processing model will be outlined that specifies three sets of operations. First, the meaning elements of a text become organized into a coherent whole, a process that results in multiple processing of some elements and, hence, in differential retention. A second set of operations condenses the full meaning of the text into its gist. These processes are complemented by a third set of operations that generate new texts from the memorial consequences of the comprehension processes. These goals involve a number of more concrete objectives. We want first to be able to go through a text, sentence by sentence, specifying the processes that these sentences undergo in comprehension as well as the outputs of these processes at various stages of comprehension. Next, we propose to analyze recall protocols and summaries in the same way and to specify for each sentence the operations required to produce such a sentence. The
Text comprehension as a problem solving situation
Universitas Psychologica
Research in text comprehension has provided details as to how text features and cognitive processes interact in order to build comprehension and generate meaning. However, there is no explicit link between the cognitive processes deployed during text comprehension and their place in higher-order cognition, as in problem solving. The purpose of this paper is to propose a cognitive model in which text comprehension is made analogous to a problem solving situation and that relies on current research on well-known cognitive processes such as inference generation, memory, and simulations. The key characteristic of the model is that it explicitly includes the formulation of questions as a component that boosts representational power. Other characteristics of the model are specified and its extensions to basic and applied research in text comprehension and higher-order cognitive processes are outlined.
Psychological and Computational Models of Language Comprehension
2011
In this paper, I argue for a modifi ed version of what Devitt (2006) calls the Representational Thesis (RT). According to RT, syntactic rules or principles are psychologically real, in the sense that they are represented in the mind/brain of every linguistically competent speaker/hearer. I present a range of behavioral and neurophysiological evidence for the claim that the human sentence processing mechanism constructs mental representations of the syntactic properties of linguistic stimuli. I then survey a range of psychologically plausible computational models of comprehension and show that they are all committed to RT. I go on to sketch a framework for thinking about the nature of the representations involved in sentence processing. My claim is that these are best characterized not as propositional attitudes but, rather, as subpersonal states. Moreover, the representational properties of these states are determined by their functional role, not solely by their causal or nomological relations to mind-independent objects and properties. Finally, I distinguish between explicit and implicit representations and argue, contra Devitt (2006), that the latter can be drawn on "as data" by the algorithms that constitute our sentence processing routines. I conclude that Devitt's skepticism concerning the psychological reality of grammars cannot be sustained.
Why are computational models of text comprehension useful
Higher level language …, 2007
Text comprehension is a complicated process. Phenomena such as word perception, syntactical analysis, semantic analysis, and inference making are essential components of the text comprehension process. Not surprisingly, most empirical research and theories ...
An automatic text comprehension classifier based on mental models and latent semantic features
Proceedings of the …, 2011
Reading comprehension is one of the main concerns for educational institutions, as it forges the students' ability to comprehend and learn accurately a given information source (e.g. textbooks, articles, papers, etc.). However, there are few approaches that integrates digital sources of educational information with automated systems to detect whether an individual has comprehended a given reading task. This work main contribution is a text comprehension classification methodology for the detection of reading comprehension failures in educational institutions. The proposed approach relates situational model theories and latent semantic analysis from fields of psycholinguistics and natural language processing respectively. A numerical characterization of students' documents using structural information, such as the usage of text connectors, and latent semantic features are used as input for traditional classification algorithms. Therefore, an automated classifier is built to determine whether a given student could or not comprehend the information in the given stimulus documents. For the evaluation of the proposed methodology, using a set of stimulus documents, a set of questions must be answered by an experimental group of students. We have performed experiments using first year students from Engineering and Linguistics undergraduate schools at the University of Chile with promising results.
Memory, 2014
Text interpretation -the main interest of discourse analysts -is a central component of the text understanding process. In this article we introduce the Landscape Model, which describes the cognitive processes underlying reading comprehension in a detailed and precise manner. Moreover, this model captures the interpretative processes in which the human mind engages during reading. Within the context of the Landscape Model, we describe the relation between discourse understanding and discourse interpretation, and explain some of the phenomena that are central to the field of discourse analysis as seen from a cognitive perspective. In the first section we describe the basic cognitive processes that underlie discourse understanding, as captured by the Landscape Model. In the following section we illustrate the way that the Landscape Model can be applied to the work of discourse analysts. We conclude by discussing the usefulness of the cognitive Landscape Model for the field of discourse analysis.
Behavior research methods, 2016
It is a well-accepted view that the prior semantic (general) knowledge that readers possess plays a central role in reading comprehension. Nevertheless, computational models of reading comprehension have not integrated the simulation of semantic knowledge and online comprehension processes under a unified mathematical algorithm. The present article introduces a computational model that integrates the landscape model of comprehension processes with latent semantic analysis representation of semantic knowledge. In three sets of simulations of previous behavioral findings, the integrated model successfully simulated the activation and attenuation of predictive and bridging inferences during reading, as well as centrality estimations and recall of textual information after reading. Analyses of the computational results revealed new theoretical insights regarding the underlying mechanisms of the various comprehension phenomena.
Comprehension and recall of text as a function of content variables
Journal of Verbal Learning and Verbal Behavior, 1975
Short English texts, controlled for number of words and number of propositions, but differing in the number of word concepts in the text base (many versus few), were read and recalled immediately. Reading times were longer and recall was less for texts with many different word concepts than for texts with fewer word concepts. Superordinate propositions were recalled better than subordinate propositions and forgotten less when recall was delayed. The probability that a word concept was recalled increased as a function of both the number of repetitions of that concept in the text base and the number of repetitions of the corresponding word in the actual text. These results also obtained when subjects listened to the experimental paragraphs. Our knowledge about the processes involved in remembering prose lags far behind that about memory for word lists. Inability to represent explicitly the meaning of texts has probably been the restricting factor in this area. There is, of course, more to memory for text than just the memory for its meaning, with important concerns ranging from memory for surface features of a text to the pragmatic aspects of the communication act, but the problem of meaning is a fundamental one. Attempts to bypass this problem, by scoring recall protocols for verbatim recall or ill-defined idea units, have proven to be inadequate and, by their very lack of success, demonstrate the need for a theory-based approach. In recent years there have been several detailed proposals for the representation of meaning which might help psychological research out of this impasse. In the present paper a theory for the representation of meaning proposed by Kintsch (1974) will be used to explore some aspects of memory for text. The theory assumes that the basic units of meaning are propositions. Propositions are n-tuples of word concepts, one of which serves as a predieator, and the remaining ones as arguments, each fulfilling a unique semantic
Understanding Reading Comprehension: Current and Future Contributions of Cognitive Science
Contemporary Educational Psychology, 1997
The ability to read and comprehend text is crucial for success in our society and its development has been a main component of instructional practice. In the past 2 decades, psychologists have devoted a good deal of attention to the question of how competent, adult readers comprehend text. Influenced by work in linguistics and artificial intelligence, the efforts of these cognitive scientists have dramatically increased our understanding of the psychological mechanisms underlying reading comprehension. In this article, we provide an overview of the contributions of cognitive research on text comprehension and an agenda for future research. Our specific interest is in understanding the processes by which skilled adult readers comprehend text.