Computerized Learning Environments That Incorporate Research in Discourse Psychology, Cognitive Science, and Computational Linguistics.

2006 ◽  
pp. 183-194 ◽  
Author(s):  
Arthur C. Graesser ◽  
Xiangen Hu ◽  
Danielle S. McNamara
Keyword(s):  
Cognitive Science ◽  
Learning Environments ◽  
Computational Linguistics ◽  
Discourse Psychology ◽  
Computerized Learning

scholarly journals Definiteness

Linguistics ◽  
2011 ◽  
Author(s):  
Klaus von Heusinger
Keyword(s):  
Cognitive Science ◽  
Computational Linguistics ◽  
Proper Names ◽  
Analytic Philosophy ◽  
Noun Phrases ◽  
Definite Descriptions ◽  
Definite Article ◽  
Personal Pronouns ◽  
Linguistic Structure ◽  
Definite Expressions

Definiteness is a semantic-pragmatic notion that is closely associated with the use of the definite article (or determiner) in languages like English, Hungarian, Hebrew, and Lakhota. The definite article can be used in different conditions: deictic, anaphoric, unique, and certain indirect uses, often also called “bridging uses.” Accordingly, there are different semantic theories of definiteness, such as the salience theory, the familiarity or identifiability theory, and the uniqueness or inclusiveness theory. Definite expressions cover personal pronouns, proper names, demonstratives, definite noun phrases, and universally quantified expressions. Noun phrases with the definite article, known as “definite descriptions,” are a key issue in semantics and analytic philosophy with respect to the interaction of reference and description in identifying an object. The research and analysis of definiteness is of great importance not only for the linguistic structure of languages but also for our understanding of reference and referring in philosophy, cognitive science, computational linguistics, and communication science.

scholarly journals iWordNet: A New Approach to Cognitive Science and Artificial Intelligence

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Mark Chang ◽  
Monica Chang
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Science ◽  
Computational Linguistics ◽  
Word Meaning ◽  
External Representation ◽  
New Approach ◽  
Complex Concept ◽  
Statistical Property ◽  
Circular Definitions ◽  
State Of Mind

One of the main challenges in artificial intelligence or computational linguistics is understanding the meaning of a word or concept. We argue that the connotation of the term “understanding,” or the meaning of the word “meaning,” is merely a word mapping game due to unavoidable circular definitions. These circular definitions arise when an individual defines a concept, the concepts in its definition, and so on, eventually forming a personalized network of concepts, which we call an iWordNet. Such an iWordNet serves as an external representation of an individual’s knowledge and state of mind at the time of the network construction. As a result, “understanding” and knowledge can be regarded as a calculable statistical property of iWordNet topology. We will discuss the construction and analysis of the iWordNet, as well as the proposed “Path of Understanding” in an iWordNet that characterizes an individual’s understanding of a complex concept such as a written passage. In our pilot study of 20 subjects we used a regression model to demonstrate that the topological properties of an individual’s iWordNet are related to his IQ score, a relationship that suggests iWordNets as a potential new methodology to studying cognitive science and artificial intelligence.

Spazi di parole: metafore e rappresentazioni semantiche

PARADIGMI ◽  
2009 ◽  
pp. 83-100
Author(s):  
Alessandro Lenci
Keyword(s):  
Cognitive Science ◽  
Semantic Similarity ◽  
Computational Linguistics ◽  
Computational Models ◽  
Dimensional Space ◽  
High Dimensional ◽  
Semantic Representations ◽  
Topological Relations ◽  
Cognitive Sciences ◽  
Context Sensitive

- The aim of this paper is to analyse the analogy of the lexicon with a space defined by words, which is common to a number of computational models of meaning in cognitive science. This can be regarded as a case of constitutive scientific metaphor in the sense of Boyd (1979) and is grounded in the so-called Distributional Hypothesis, stating that the semantic similarity between two words is a function of the similarity of the linguistic contexts in which they typically co-occur. The meaning of words is represented in terms of their topological relations in a high-dimensional space, defined by their combinatorial behaviour in texts. A key consequence of adopting the metaphor of word spaces is that semantic representations are modelled as highly context-sensitive entities. Moreover, word space models promise to open interesting perspectives for the study of metaphorical uses in language, as well as of lexical dynamics in general. Keywords: Cognitive sciences, Computational linguistics, Distributional models of the lexicon, Metaphor, Semantics, Word spaces.

Learn from Experience to Build Competence

2017 ◽  
pp. 1-14
Author(s):  
Roberto Trinchero
Keyword(s):  
Experiential Learning ◽  
Cognitive Science ◽  
Instructional Strategies ◽  
Learning Environments ◽  
Virtual Learning Environments ◽  
Research Issues ◽  
Effective Learning ◽  
Instructional Activities ◽  
Effective Learning Environments ◽  
Science And Research

This chapter explore the research issues about effective learning environments and propose a model for designing instructional activities for Virtual Learning Environments (VLEs), based on doing meaningful experience and proficient paths of: reflection on experience, abstraction of principles, practice and automatization of principles application, transferring of the principle to other contexts and situations. The model is inspired from classical experiential learning cycles and propose activities with four key-moments: Challenge - Debriefing - Abstracting/Generalizing - Automatization/Transfer (CDAA). As discussed, the model can meet many instances drawn either from research on learning in cognitive science and research in the effectiveness of instructional strategies.

Natural language processing and the Now-or-Never bottleneck

2016 ◽  
Vol 39 ◽  
Author(s):  
Carlos Gómez-Rodríguez
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Cognitive Science ◽  
Computational Linguistics ◽  
Language Processing ◽  
Human Language ◽  
Additional Support ◽  
Scale Data

AbstractResearchers, motivated by the need to improve the efficiency of natural language processing tools to handle web-scale data, have recently arrived at models that remarkably match the expected features of human language processing under the Now-or-Never bottleneck framework. This provides additional support for said framework and highlights the research potential in the interaction between applied computational linguistics and cognitive science.

scholarly journals Reviews

2011 ◽  
Vol 3 (2) ◽  
Author(s):  
Ian Benest
Keyword(s):  
Educational Technology ◽  
Graduate Students ◽  
Cognitive Science ◽  
Learning Environments ◽  
Special Programme ◽  
Series Books ◽  
Present Volume ◽  
Educational Foundations ◽  
Research Findings ◽  
Study Institute

This publication is one of a collection of texts that has been produced within the NATO ASI F series - books published as a result of the activities of the special programme on advanced educational technology. Currently, the list of books in this series totals over 35. The present volume contains 37 papers that were contributed to the Advanced Study Institute (ASI) on Educational Technology held in Crete in the summer of 1992. The purpose of the Institute was to bring together lecturers and graduate students in order to investigate and discuss the psychological and educational foundations of technology-based learning environments, and to debate the implications of recent research findings in the area of cognitive science for the development of educational technology.DOI:10.1080/0968776950030208

Was zeichnet eine moderne Auffassung von Geist aus?

2015 ◽  
Vol 18 (1) ◽  
pp. 114-128
Author(s):  
Achim Stephan
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Science ◽  
Computational Linguistics ◽  
Computer Model ◽  
Situated Cognition ◽  
Natural Sciences ◽  
Artificial Agent ◽  
Cognitive Capacities ◽  
Disciplinary Perspective ◽  
Aristotelian Tradition

‘Having a mind’ is construed as having a variety of mental capacities such as perceiving, memorizing, learning, or reasoning. In cognitive science, these capacities are studied from an integrative trans-disciplinary perspective that combines anthropology, artificial intelligence, computational linguistics, neuroscience, philosophy and psychology. To approach mental phenomena by combining philosophical insights with those from the natural sciences is part of the Aristotelian tradition. Accordingly, the paper also portrays the most salient models of mental processing – the computer model, connectionism and situated cognition. Eventually, an example of an artificial agent – Affective AutoTutor – is introduced that exhibits striking cognitive capacities, but still seems to lack what is expected from someone who ‘has a mind’.

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