Catálogo de publicaciones - libros

Existing diagrams for tense use as presented in grammar surveys for foreign learners have been analyzed from a semantic theoretic point of view. The analysis reveals that the notational systems used in the diagrammatic representations of the tense rules dealt with are defective in that they can give rise to incorrect interpretations and ambiguities. Moreover, they do not allow the learner to get a coherent view of the tense system. The flaws of the existing diagrams are mainly caused by the lack of a clear delimitation and description of the critical information to be conveyed to the learner. In this paper, we try to avoid these defects by proposing a notational system that relies on a formal semantic approach of tensed discourse.

This paper describes the evaluation of ERST, an adaptive system which is designed to improve its users’ external representation (ER) selection accuracy on a range of database query tasks. The design of the system was informed by the results of experimental studies. Those studies examined the interactions between the participants’ background knowledge-of-external representations, their preferences for selecting particular information display forms, and their performance across a range of tasks involving database queries. The paper describes how ERST’s adaptation is based on predicting users’ ER-to-task matching skills and performance at reasoning with ERs, via a Bayesian user model. The model drives ERST’s adaptive interventions in two ways – by 1. hinting to the user that particular representations be used, and/or 2. by removing from the user the opportunity to select display forms which have been associated with prior poor performance for that user. The results show that ERST does improve an individual’s ER reasoning performance. The system is able to successfully predict users’ ER-to-task matching skills and their ER reasoning performance via its Bayesian user model.

While the educational effectiveness of static diagrams is underpinned by a long heritage of manipulating visuospatial characteristics of the depicted content to improve explanatory power, no corresponding evolution has occurred regarding temporal manipulation of animated diagrams. When complex dynamic subject matter is presented using animations that depict temporal information in a behaviorally realistic manner, the perceptual properties of the display may be poorly matched to the learner’s information processing capacities. An exploration of the effect on information extraction of manipulating the speed and presentation frequency of an animation depicting dynamically–complex subject matter suggests that such manipulations may be used to improve perception of thematically relevant information.

In this study, students’ expression of understanding of structure and function in three systems of the body through visual (drawn) and verbal (written and spoken) modes was probed. Those with good comprehension had high scores in both modes. Pedagogical practices must emphasise explicit use of drawings and words to link structure and function concepts. This can help students of lower ability to form an integrated mental model which will aid understanding and expression.

Schematic diagrams (e.g., circuit diagrams, Euler circles), which depict abstract concepts, are important tools for thinking. Three interrelated diagrams that belong in this category—hierarchies, matrices, and networks—are common in both everyday and scientific contexts. For example, a hierarchy can be used to represent relations among members of the animal kingdom or the search space at a given point in a chess game; a matrix can be used to represent the grade sheet for a class or possible item pairings in a deductive-reasoning problem; and a network can be used to represent the food web for an ecosystem or the alliances among nations. Because these diagrams highlight structural similarities across situations that are superficially very different, by successfully constructing these diagrams, solvers would be led to see deep (i.e., structural) similarities among diverse situations that otherwise might not be salient (Novick, 2001). Structural understanding is a key factor underlying expertise. Thus, it is important to understand when hierarchies, matrices, and networks are each most appropriate to use, how they should be constructed, and what makes them easier or harder to understand (Hurley & Novick, 2006; Novick & Hurley, 2001).

This study sought to address the problem of novices not being able to select the appropriate diagrams to suit given tasks. It investigated the usefulness of providing teaching sessions that involved active comparison of diagrams and review of lessons learnt following problem solving. Fifty-eight 8th grade participants were assigned to one of two instruction conditions. In both, traditional math classes were provided in which diagrams were used to explain how to solve math word problems. However, participants in the experimental group were additionally provided with sessions that required them to actively compare diagrams used, and consider and articulate the lessons they learnt from the problem solving exercises. The results showed that participants in the experimental condition subsequently constructed more appropriate diagrams in solving math word problems. In an assessment of conditional knowledge, these participants also provided more abstract and detailed descriptions about the uses of diagrams in problem solving.

A diagrammatic problem-solver requires a library of visual routines (VRs) and action routines (ARs) – the VRs are used to obtain information of specified types from the diagram and ARs to modify the diagram in specified ways. The VRs/ARs required are unbounded – a new domain may call for new perceptions and actions. We report on progress on our research in building an automated VR/AR synthesis system that would take as input the definition of a new routine in terms of existing routines in the library and well-defined mathematical/logical constraints and synthesize the program for the desired routine using constraint programming. We illustrate the ideas by means of an example.

Two studies evaluated the effectiveness of Euler circles in aiding participants in drawing conclusions to deductive reasoning problems. The problems were the ones that typically cause reasoners the most difficulty because their prior beliefs about conclusions interfere with their judgments of deductive validity. The use Euler circles reliably contributed to reasoners’ inability to solve the problems. This pattern was shown for both young, university students and elderly retired people.

We discuss a variety of roles for diagrams in helping with reasoning, focusing in particular on their role as physical models of states of affairs, much like an architectural model of a building or a 3-D molecular model of a chemical compound. We discuss the concept of a physical model for a logical sentence, and the role played by the causal structure of the physical medium in making the given sentence as well as a set of implied sentences true. This role of a diagram is consistent with a widely-held intuition that diagrams exploit the fact that 2-D space is an analog of the domain of discourse. One line of research in diagrammatic reasoning is that diagrams, rather then being models, are formal representations with specialized rules of inference that generate new diagrams. We reconcile these contrasting views by relating the usefulness of diagrammatic systems as formal representations to the fact that their rewrite rules take advantage of the diagrams’ model-like character. When the physical model is prototypical , it supports the inference of certain other sentences for which it provides a model as well. We also informally discuss a proposal that diagrams and similar physical models help to explicate a certain sense of relevance in inference, an intuition that so-called Relevance Logics attempt to capture.

This paper presents the new framework for visual computational design in which emergence is a key to creativity. Visual shape grammar computations proceeded with the use of diagrams are situated in a design context indirectly through the designer working with the application or more explicitly through curious agents. Curiosity of intelligent agents is applied to search for novel and plausible design solutions. The approach is illustrated by designing decorative patterns.