Publications

Abstract

Incremental sentence generation imposes special constraints on the representation of the grammar and the design of the formulator (the module which is responsible for constructing the syntactic and morphological structure). In the model of natural speech production presented here, a formalism called Segment Grammar is used for the representation of linguistic knowledge. We give a definition of this formalism and present a formulator design which relies on it. Next, we present an object- oriented implementation of Segment Grammar. Finally, we compare Segment Grammar with other formalisms.

Abstract

Two experiments examined the nature of access, storage, and comprehension of idiomatic phrases. In both studies a Phrase Classification Task was utilized. In this, reaction times to determine whether or not word strings constituted acceptable English phrases were measured. Classification times were significantly faster to idiom than to matched control phrases. This effect held under conditions involving different categories of idioms, different transitional probabilities among words in the phrases, and different levels of awareness of the presence of idioms in the materials. The data support a Lexical Representation Hypothesis for the processing of idioms.

Abstract

This paper presents a cognitive theory on the production and shaping of selfrepairs during speaking. In an extensive experimental study, a new technique is tried out: artificial elicitation of self-repairs. The data clearly indicate that two mechanisms for computing the shape of self-repairs should be distinguished. One is based on the repair strategy called reformulation, the second one on lemma substitution. W. Levelt’s (1983, Cognition, 14, 41- 104) well-formedness rule, which connects self-repairs to coordinate structures, is shown to apply only to reformulations. In case of lemma substitution, a totally different set of rules is at work. The linguistic unit of central importance in reformulations is the major syntactic constituent; in lemma substitutions it is a prosodic unit. the phonological phrase. A parametrization of the model yielded a very satisfactory fit between observed and reconstructed scores.

Abstract

An essential phenomenon in the development towards syntactic maturity after early childhood is the increasing use of so-called sentence-combining transformations. Especially by using subordination, complex sentences are produced. The research reported here is an attempt to arrive at a more adequate characterization and explanation. Our starting point was an analysis of 280 texts written by Dutch-speaking pupils of the two highest grades of the primary school and the four lowest grades of three different types of secondary education. It was examined whether systematic shifts in the use of certain groups of so-called function words could be traced. We concluded that the development of the syntactic formulating ability can be characterized as an increase in connectivity: the use of all kinds of function words which explicitly mark logico-semantic relations between propositions. This development starts by inserting special adverbs and coordinating conjunctions resulting in various types of coordination. In a later stage, the syntactic patterning of the sentence is affected as well (various types of subordination). The increase in sentence complexity is only one aspect of the entire development. An explanation for the increase in connectivity is offered based upon a distinction between narrative and expository language use. The latter, but not the former, is characterized by frequent occurrence of connectives. The development in syntactic formulating ability includes a high level of skill in expository language use. Speed of development is determined by intensity of training, e.g. in scholastic and occupational settings.

Abstract

This paper reports two experiments with vowels and consonants as phoneme detection targets in real words. In the first experiment, two relatively distinct vowels were compared with two confusible stop consonants. Response times to the vowels were longer than to the consonants. Response times correlated negatively with target phoneme length. In the second, two relatively distinct vowels were compared with their corresponding semivowels. This time, the vowels were detected faster than the semivowels. We conclude that response time differences between vowels and stop consonants in this task may reflect differences between phoneme categories in the variability of tokens, both in the acoustic realisation of targets and in the' representation of targets by subjects.

Abstract

Computer simulations in an instructional context can be characterized according to four aspects (themes): simulation models, learning goals, learning processes and learner activity. The present paper provides an outline of these four themes. The main classification criterion for simulation models is quantitative vs. qualitative models. For quantitative models a further subdivision can be made by classifying the independent and dependent variables as continuous or discrete. A second criterion is whether one of the independent variables is time, thus distinguishing dynamic and static models. Qualitative models on the other hand use propositions about non-quantitative properties of a system or they describe quantitative aspects in a qualitative way. Related to the underlying model is the interaction with it. When this interaction has a normative counterpart in the real world we call it a procedure. The second theme of learning with computer simulation concerns learning goals. A learning goal is principally classified along three dimensions, which specify different aspects of the knowledge involved. The first dimension, knowledge category, indicates that a learning goal can address principles, concepts and/or facts (conceptual knowledge) or procedures (performance sequences). The second dimension, knowledge representation, captures the fact that knowledge can be represented in a more declarative (articulate, explicit), or in a more compiled (implicit) format, each one having its own advantages and drawbacks. The third dimension, knowledge scope, involves the learning goal's relation with the simulation domain; knowledge can be specific to a particular domain, or generalizable over classes of domains (generic). A more or less separate type of learning goal refers to knowledge acquisition skills that are pertinent to learning in an exploratory environment. Learning processes constitute the third theme. Learning processes are defined as cognitive actions of the learner. Learning processes can be classified using a multilevel scheme. The first (highest) of these levels gives four main categories: orientation, hypothesis generation, testing and evaluation. Examples of more specific processes are model exploration and output interpretation. The fourth theme of learning with computer simulations is learner activity. Learner activity is defined as the ‘physical’ interaction of the learner with the simulations (as opposed to the mental interaction that was described in the learning processes). Five main categories of learner activity are distinguished: defining experimental settings (variables, parameters etc.), interaction process choices (deciding a next step), collecting data, choice of data presentation and metacontrol over the simulation.

Abstract

The use of computer simulations in education and training can have substantial advantages over other approaches. In comparison with alternatives such as textbooks, lectures, and tutorial courseware, a simulation-based approach offers the opportunity to learn in a relatively realistic problem-solving context, to practise task performance without stress, to systematically explore both realistic and hypothetical situations, to change the time-scale of events, and to interact with simplified versions of the process or system being simulated. However, learners are often unable to cope with the freedom offered by, and the complexity of, a simulation. As a result many of them resort to an unsystematic, unproductive mode of exploration. There is evidence that simulation-based learning can be improved if the learner is supported while working with the simulation. Constructing such an instructional environment around simulations seems to run counter to the freedom the learner is allowed to in ‘stand alone’ simulations. The present article explores instructional measures that allow for an optimal freedom for the learner. An extensive discussion of learning goals brings two main types of learning goals to the fore: conceptual knowledge and operational knowledge. A third type of learning goal refers to the knowledge acquisition (exploratory learning) process. Cognitive theory has implications for the design of instructional environments around simulations. Most of these implications are quite general, but they can also be related to the three types of learning goals. For conceptual knowledge the sequence and choice of models and problems is important, as is providing the learner with explanations and minimization of error. For operational knowledge cognitive theory recommends learning to take place in a problem solving context, the explicit tracing of the behaviour of the learner, providing immediate feedback and minimization of working memory load. For knowledge acquisition goals, it is recommended that the tutor takes the role of a model and coach, and that learning takes place together with a companion. A second source of inspiration for designing instructional environments can be found in Instructional Design Theories. Reviewing these shows that interacting with a simulation can be a part of a more comprehensive instructional strategy, in which for example also prerequisite knowledge is taught. Moreover, information present in a simulation can also be represented in a more structural or static way and these two forms of presentation provoked to perform specific learning processes and learner activities by tutor controlled variations in the simulation, and by tutor initiated prodding techniques. And finally, instructional design theories showed that complex models and procedures can be taught by starting with central and simple elements of these models and procedures and subsequently presenting more complex models and procedures. Most of the recent simulation-based intelligent tutoring systems involve troubleshooting of complex technical systems. Learners are supposed to acquire knowledge of particular system principles, of troubleshooting procedures, or of both. Commonly encountered instructional features include (a) the sequencing of increasingly complex problems to be solved, (b) the availability of a range of help information on request, (c) the presence of an expert troubleshooting module which can step in to provide criticism on learner performance, hints on the problem nature, or suggestions on how to proceed, (d) the option of having the expert module demonstrate optimal performance afterwards, and (e) the use of different ways of depicting the simulated system. A selection of findings is summarized by placing them under the four themes we think to be characteristic of learning with computer simulations (see de Jong, this volume).

Abstract

Meermalen is getracht om syntactische formuleenuuirdigheid direct en objectief te meten aan de hand van gesproken of geschreven teksten. Uitgangspunt hierbij vormde in de regel de syntactische complexiteit van de geproduceerde taaluitingen. Dit heeft echter niet geleid tot een plausibele, duidelijk omschreven en praktisch bruikbare index. N.a.v. een kritische bespreking van de notie complexiteit wordt in dit artikel als nieuw criterium voorgesteld de connectiviteit van de taaluitingen; de expliciete aanduiding van logiscli-scmantische relaties tussen proposities. Connectiviteit is gemakkelijk scoorbaar aan de hand van functiewoorden die verschillende vormen van nevenschikkend en onderschikkend zinsverband markeren. Deze nieuwe index ondetrangt de kritiek die op complexiteit gegeven kon worden, blijkt duidelijk te discrimineren tussen groepen leerlingen die van elkaar verschillen naar leeftijd en opleidingsniveau, en sluit aan bij recente taalpsychologische en sociolinguïstische theorie. Tot besluit worden enige onderwijskundige implicaties aangegeven.

Abstract

Referential expressions that refer to entities that occur in a text differ in lexical specificity. It is claimed that if these anaphoric expressions are more specific than necessary for their identificational function, they not only relate the current information to the intended referent, but also contribute to the expression of the thematic structure of the discourse and to the comprehension of the thematic structure. In two controlled production experiments, it is demonstrated that thematic shifts are produced when one has to make use of such an overspecified expression, and that overspecified referential expressions are produced when one has to formulate a thematic shift. In two comprehension experiments, using a probe recognition technique, it is shown that an overspecified referential expression decreases the availability of information contained in a sentence that precedes the overspecification. This finding is interpreted in terms of the thematic structuring function of referential expressions in the understanding of discourse.