This article reviews research on the use of situation models in lnguage comprehension and memory retrieval over the past 15 years. Situation models are integrated mental representations of a described state of affairs. Significant progress has been made in the scientific understanding of how situation models are involved in language comprehension and memory retrieval. Much of this research focuses on establishing the existence of situation models, often by using tasks that assess one dimension of a situation model. However, the authors argue that the time has now come for researchers to begin to take the multidimensionality of situation models seriously. The authors offer a theoretical framework and some methodological observations that may help researchers to tackle this issue.

Two experiments, theoretically motivated by the construction-integration model of text comprehension ( W. Kintsch, 1988), investigated the role of text coherence in the comprehension of science texts. In Experiment 1, junior high school students' comprehension of one of three versions of a biology text was examined via free recall, written questions, and a key-word sorting task. This study demonstrates advantages for globally coherent text and for more explanatory text. In Experiment 2, interactions among local and global text coherence, readers' background knowledge, and levels of understanding were examined. Using the same methods as in Experiment 1, we examined students' comprehension of one of four versions of a text, orthogonally varying local and global coherence. We found that readers who know little about the domain of the text benefit from a coherent text, whereas high-knowledge readers benefit from a minimally coherent text. We argue that the poorly written text forces the knowledgeable readers to engage in compensatory processing to infer unstated relations in the text. These findings, however, depended on the level of understanding, text base or situational, being measured by the three comprehension tasks. Whereas the free-recall measure and text-based questions primarily tapped readers' superficial understanding of the text, the inference questions, problem-solving questions, and sorting task relied on a situational understanding of the text. This study provides evidence that the rewards to be gained from active processing are primarily at the level of the situation model rather than at the superficial level of text-base understanding.

ABSTRACT Previous studies on program comprehension were carried out largely in the context of procedural languages. Our purpose is to develop and evaluate a cognitive model of object-oriented (OO) program understanding. Our model is based on the van Dijk and Kintsch's model of text understanding (1983). One key aspect of this theoretical approach is the distinction between two kinds of representation the reader might construct from a text: the textbase and the situation model. On the basis of results of an experiment we have conducted, we evaluate the cognitive validity of this distinction in OO program understanding. We examine how the construction of these two representations is differentially affected by the programmer's expertise and how they evolve differentially over time. KEY WORDS mental representation, situation model, program model, object-oriented programming, program comprehension, text comprehension, expertise 1. OBJECTIVES The object-oriented (OO) paradigm is growing fast in popularity, but not enough scientific evidence has been amassed about it. The research that exists is mostly focused on program design and reuse (see for example: Détienne, 1995; Pennington, Lee and Rehder, 1995).

The objective of this study was to determine whether the mental representation of object-oriented programs differs from imperative programs for novice programmers. In our study novices who had little or no previous programming experience studied and answered questions about three imperative and three object-oriented programs. The questions targeted information categories making up the program model and the domain model representations of the programs. It was found that there was a sharp contrast between the mental representations of the imperative and object-oriented programs. While the comprehension of the imperative programs was better overall than that of the object-oriented programs, the mental representations of the imperative programs focused on program-level knowledge. On the other hand, the mental representations of the object-oriented programs focused more strongly on domain-level knowledge. The results tend to support the view that language notations differ in how well they support the extraction of various kinds of information. 1.

Abstract. The goal of our study is to evaluate the effect on program comprehension of three factors that have not previously been studied in a single experiment. These factors are programmer expertise (expert versus novice), programming task (documentation versus reuse), and the development of understanding over time (phase 1 versus phase 2). This study is carried out in the context of the mental model approach to comprehension based on van Dijk and Kintsch’s model [(1983) Strategies of Discourse Comprehension. New York: Academic]. One key aspect of this model is the distinction between two kinds of representation the reader might construct from a text: (1) the textbase, which refers to what is said in the text and how it is said, and (2) the situation model, which represents the situation referred to by the text. We have evaluated the effect of the three factors mentioned above on the development of both the textbase (or program model) and the situation model in object-oriented program comprehension. We found a four-way interaction of expertise, phase, task and type of model. For the documentation group we found that experts and novices differ in the elaboration of their situation model but not their program model. There was no interaction of expertise with phase and type of model in the documentation group. For the reuse group, there was a three-way interaction between phase, expertise and type of model. For the novice reuse group, the effect of the phase was to increase the construction of the situation model but not the program model.

Many of the object-oriented metrics that have been developed by the research community are believed to measure some aspect of complexity. As such, they can serve as leading indicators of problematic classes, for example, those classes that are most fault-prone. If faulty classes can be detected early in the development project's life cycle, mitigating actions can be taken, such as focused inspections. Prediction models using design metrics can be used to identify faulty classes early on. In this paper, we present a cognitive theory of object-oriented metrics and an empirical study which has as objectives to formally test this theory while validating the metrics and to build a post-release fault-proneness prediction model. The cognitive mechanisms which we apply in this study to object-oriented metrics are based on contemporary models of human memory. They are: familiarity, interference, and fan effects. Our empirical study was performed with data from a commercial Java application. We found that Depth of Inheritance Tree (DIT) is a good measure of familiarity and, as predicted, has a quadratic relationship with fault-proneness. Our hypotheses were confirmed for Import Coupling to other classes, Export Coupling and Number of Children metrics. The Ancestor based Import Coupling metrics were not associated with fault-proneness after controlling for the confounding effect of DIT. The prediction model constructed had a good accuracy. Finally, we formulated a cost savings model and applied it to our predictive model. This demonstrated a 42% reduction in post-release costs if the prediction model is used to identify the classes that should be inspected.

To account for the large demands of working memory during text comprehension and expert problem solving it is proposed that the traditional models of working memory involving temporary storage have to be extended to include a long-term working-memory portion. According to the proposed theoretical framework cognitive processes are viewed as a sequence of stable states representing end products of processing. In skilled activities these end products are stored in long-term memory and kept directly accessible by retrieval cues in short-term memory as proposed by skilled memory theory. These

We have been developing tutors to help students learn programming concepts by solving problems. In this paper, we will discuss the use of problem-solving in Computer Science, the effectiveness of using problem-solving tutors to learn programming concepts, and the pedagogical relationship between solving problems and learning to write programs. We will also present the design and results from the evaluation of one of our tutors. 2. PROBLEM-SOLVING AND COMPUTER SCIENCE Problem-based learning improves long-term retention [13], and is better than traditional instruction for improving the ability of students to solve real-life problems. In Computer Science, various researchers have advocated the use of self-paced exercises [27], practice to build problem-solving skills [38], and the use of frequent, graded assignments in a course [10]. It is reported that “students universally want to see more examples both in class and in

Inferential power and barriers to understanding i

authors are senior members of staff; the others are working on their doctoral dissertation. A selection of papers was presented at the annual Uiltjesdagen, a conference that brings together junior researchers of UiL-OTS. The research covers language acquisition, phonetics, phonology, morphology, psycholinguistics, syntax, text-linguistics and interfaces of these areas. In a phonetic study, Heeren investigated the development of the classification of a vowel continuum based on duration. She found that children’s phoneme boundary was put at approximately the same point along the duration axis as that of adults. However, some children did not use duration as a cue and listened to spectral information only. Escudero presents data from cross-linguistic vowel perception to illustrate that speech perception is dependent on language-specific linguistic input, leading her to claim that speech perception is phonological in nature. Mahanta and Grijzenhout describe vowel harmony in Assamese, a language spoken in Northeastern India. They show that locality issues are more substantive and grounded in phonetics than they have been given credit for in current theoretical phonological