Understanding Science Through Knowledge Organizers: An Introduction

We propose, in this paper, a teaching program based on a grammar of scientific language borrowed mostly from the area of knowledge representation in computer science and logic. The paper introduces an operationizable framework for understanding knowledge using knowledge representation (KR) methodology. We start with organizing concepts based on their cognitive function, followed by assigning valid and authentic semantic relations to the concepts. We propose that in science education, students can understand better if they organize their knowledge using the KR principles. The process, we claim, can help them to align their conceptual framework with that of experts which we assume is the goal of science education

LOGICAL AND PSYCHOLOGICAL PARTITIONING OF MIND: DEPICTING THE SAME MAP?

The aim of this paper is to demonstrate that empirically delimited structures of mind are also differentiable by means of systematic logical analysis. In the sake of this aim, the paper first summarizes Demetriou's theory of cognitive organization and growth. This theory assumes that the mind is a multistructural entity that develops across three fronts: the processing system that constrains processing potentials, a set of specialized structural systems (SSSs) that guide processing within different reality and knowledge domains, and a hypecognitive system that monitors and controls the functioning of all other systems. In the second part the paper focuses on the SSSs, which are the target of our logical analysis, and it summarizes a series of empirical studies demonstrating their autonomous operation. The third part develops the logical proof showing that each SSS involves a kernel element that cannot be reduced to standard logic or to any other SSS. The implications of this analysis for the general theory of knowledge and cognitive development are discussed in the concluding part of the paper

Platonic model of mind as an approximation to neurodynamics

Hierarchy of approximations involved in simplification of microscopic theories, from sub-cellural to the whole brain level, is presented. A new approximation to neural dynamics is described, leading to a Platonic-like model of mind based on psychological spaces. Objects and events in these spaces correspond to quasi-stable states of brain dynamics and may be interpreted from psychological point of view. Platonic model bridges the gap between neurosciences and psychological sciences. Static and dynamic versions of this model are outlined and Feature Space Mapping, a neurofuzzy realization of the static version of Platonic model, described. Categorization experiments with human subjects are analyzed from the neurodynamical and Platonic model points of view

Self-directedness, integration and higher cognition

In this paper I discuss connections between self-directedness, integration and higher cognition. I present a model of self-directedness as a basis for approaching higher cognition from a situated cognition perspective. According to this model increases in sensorimotor complexity create pressure for integrative higher order control and learning processes for acquiring information about the context in which action occurs. This generates complex articulated abstractive information processing, which forms the major basis for higher cognition. I present evidence that indicates that the same integrative characteristics found in lower cognitive process such as motor adaptation are present in a range of higher cognitive process, including conceptual learning. This account helps explain situated cognition phenomena in humans because the integrative processes by which the brain adapts to control interaction are relatively agnostic concerning the source of the structure participating in the process. Thus, from the perspective of the motor control system using a tool is not fundamentally different to simply controlling an arm

Second order isomorphism: A reinterpretation and its implications in brain and cognitive sciences

Shepard and Chipman's second order isomorphism describes how the brain may represent the relations in the world. However, a common interpretation of the theory can cause difficulties. The problem originates from the static nature of representations. In an alternative interpretation, I propose that we assign an active role to the internal representations and relations. It turns out that a collection of such active units can perform analogical tasks. The new interpretation is supported by the existence of neural circuits that may be implementing such a function. Within this framework, perception, cognition, and motor function can be understood under a unifying principle of analogy

(Mind)-Reading Maps

In a two-system theory for mind-reading, a flexible system (FS) enables full-blown mind-reading, and an efficient system (ES) enables early mind-reading (Apperly and Butterfill 2009). Efficient processing differs from flexible processing in terms of restrictions on the kind of input it can take and the kinds of mental states it can ascribe (output). Thus, systems are not continuous, and each relies on different representations: the FS on beliefs and other propositional attitudes, and the ES on belief-like states or registrations. There is a conceptual problem in distinguishing the representations each system operates with. They contend that they can solve this problem by appealing to a characterization of registrations based on signature limits, but this does not work. I suggest a solution to this problem. The difference between registration and belief becomes clearer if each vehicle turns out to be different. I offer some reasons in support of this proposal related to the performance of spontaneous-response false belief tasks.Fil: Velazquez Coccia, Fernanda Maria Soledad. Universidad de Buenos Aires. Facultad de Filosofía y Letras. Instituto de Filosofía "Dr. Alejandro Korn"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Wayfinding in Complex Multi-storey Buildings: A vision-simulation-augmented wayfinding protocol study

Wayfinding in complex multi-storey buildings often brings newcomers and even some frequent visitors uncertainty and stress. However, there is little understanding on wayfinding in 3D structure which contains inter-storey and inter-building travelling. This paper presents the method of vision-simulation-augmented wayfinding protocol for the study of such 3D structure to find its application from investigating pedestrians’ wayfinding behaviour in general-purpose complex multi-storey buildings. Based on Passini’s studies as a starting point, an exploratory quasi-experiment was developed during the study and then conducted in a daily wayfinding context, adopting wayfinding protocol method with augmentation by the real-time vision simulation. The purpose is to identify people’s natural wayfinding strategies in natural settings, for both frequent visitors and newcomers. It is envisioned that the findings of the study can inspire potential design solutions for supporting pedestrian’s wayfinding in 3D indoor spaces. From the new method developed and new analytic framework, several findings were identified which differ from other wayfinding literature, such as (1) people seem to directly “make sense” of wayfinding settings, (2) people could translate recurring actions into unconscious operational behaviours, and (3) physical rotation and constrained views, instead of vertical travelling itself, should be problems for wayfinding process, etc. Keywords: Wayfinding Protocol; Real-time Vision Simulation; 3D Indoor Space; Activity Theory; Structure of Wayfinding process</p

Solving Tree Problems with Category Theory

Artificial Intelligence (AI) has long pursued models, theories, and techniques to imbue machines with human-like general intelligence. Yet even the currently predominant data-driven approaches in AI seem to be lacking humans' unique ability to solve wide ranges of problems. This situation begs the question of the existence of principles that underlie general problem-solving capabilities. We approach this question through the mathematical formulation of analogies across different problems and solutions. We focus in particular on problems that could be represented as tree-like structures. Most importantly, we adopt a category-theoretic approach in formalising tree problems as categories, and in proving the existence of equivalences across apparently unrelated problem domains. We prove the existence of a functor between the category of tree problems and the category of solutions. We also provide a weaker version of the functor by quantifying equivalences of problem categories using a metric on tree problems.Comment: 10 pages, 4 figures, International Conference on Artificial General Intelligence (AGI) 201