Generating Scripts From Memory

A variation of the Raaijmaker and Shiffrin (1981) retrieval model is proposed to account for typical script generation data. In our model, knowledge is represented as an associative network with propositions as the nodes. A control process which utilizes temporal information in these propositions supplements the probabilistic memory retrieval process to produce ordered retrieval of scriptal events. Simulations are reported which provide a good qualitative fit to data collected from subjects in both script generation and free association tasks. These results support a view of memory as an unorganized knowledge base rather than a stable, organized structur

Working Memory in Text Comprehension: Interrupting Difficult Text

We compare the effects of interrupting text dealing with familiar or unfamiliar domains with either arithmetic or sentence reading tasks. Readers were interrupted after each of the eight sentences, at the end of each sentence, or in the middle of each sentence. Previous findings of minimal effects of interruptive tasks on comprehension measures (eg . fllanzer & Nolan, 1986) were replicated in this study. Also, as found by Glanzer and his colleagues, interruptions after each sentence of a familiar text by an unrelated sentence increased reading times by approximately 400 ms per sentence. In contrast, for difficult, unfamiliar texts, mid-scnience interruptions significantly lengthened reading times by 1262 ms for sentence and 1784 ms for arithmetic interruptions. These findings arc explained in terms of Enesson and Kintsch's (1995) memory model which proposes that skilled memory performance relies on the use of long-term memory as an extension of working memory, or long-term working memory

Learning with Diagrams: Effects on Inferences and the Integration of Information

Abstract. Students studied materials about the human heart and circulatory system using either (a) text only, (b) text with simple diagrams, or (c) text with detailed diagrams. During learning, students self-explained [1] the materials. Explanations were transcribed, separated into propositions, and analyzed according to the type of learning process they represented. Results demonstrated that diagrams promoted inference generation but did not affect other learning processes (such as elaboration or comprehension monitoring). However, only simple diagrams promoted generation of inferences that integrated domain information. Results indicate that diagrams may be useful because they guide the learner to engage in the cognitive processes required for deep understanding

Latent Problem Solving Analysis as an explanation of expertise effects in a complex, dynamic task

Abstract Latent Problem Solving Analysis (LPSA) is a theory of knowledge representation in complex problem solving that argues that problem spaces can be represented as multidimensional spaces and expertise is the construction of those spaces from immense amounts of experience. The model was applied using a dataset from a longitudinal experiment on control of thermodynamic systems. When the system is trained with expert-level amounts of experience (3 years), it can predict the end of a trial using the first three quarters with an accuracy of .9. If the system is prepared to mimic a novice (6 months) the prediction accuracy falls to .2. If the system is trained with 3 years of practice in an environment with no constraints, performance is similar to the novice baseline