Career-related abilities: Conceptual issues and general intelligence.

2022 ◽  
pp. 127-145
Author(s):  
Rodney L. Lowman
Keyword(s):  
General Intelligence

The Effect of Retest Practice on the Speed-Ability Relationship

2004 ◽  
Vol 9 (1) ◽  
pp. 24-31 ◽  
Author(s):  
Sybille Rockstroh ◽  
Karl Schweizer
Keyword(s):  
Reaction Time ◽  
Skill Acquisition ◽  
Reaction Times ◽  
Cognitive Tasks ◽  
General Intelligence ◽  
Attention Switching ◽  
Letter Comparison ◽  
Sternberg Paradigm ◽  
The Relationship ◽  
Elementary Cognitive Tasks

Effects of four retest-practice sessions separated by 2 h intervals on the relationship between general intelligence and four reaction time tasks (two memory tests: Sternberg's memory scanning, Posner's letter comparison; and two attention tests: continuous attention, attention switching) were examined in a sample of 83 male participants. Reaction times on all tasks were shortened significantly. The effects were most pronounced with respect to the Posner paradigm and smallest with respect to the Sternberg paradigm. The relationship to general intelligence changed after practice for two reaction time tasks. It increased to significance for continuous attention and decreased for the Posner paradigm. These results indicate that the relationship between psychometric intelligence and elementary cognitive tasks depends on the ability of skill acquisition. In the search for the cognitive roots of intelligence the concept of learning seems to be of importance.

Beérkezett könyvek

2005 ◽  
Vol 60 (3) ◽  
pp. 425-427
Author(s):  
Csaba Pléh
Keyword(s):  
Social Interaction ◽  
Cognitive Science ◽  
Evolutionary Psychology ◽  
Well Being ◽  
General Intelligence ◽  
Human Thought ◽  
Number Of Genes ◽  
History Of ◽  
Origin Of Mind ◽  
The Mind

Ádám György: A rejtozködo elme. Egy fiziológus széljegyzetei Carpendale, J. I. M. és Müller, U. (eds): Social interaction and the development of knowledge Cloninger, R. C.: Feeling good. The science of well being Dunbar, Robin, Barrett, Louise, Lycett, John: Evolutionary psychology Dunbar, Robin: The human story. A new history of makind's evolution Geary, D. C.: The origin of mind. Evolution of brain, cognition and general intelligence Gedeon Péter, Pál Eszter, Sárkány Mihály, Somlai Péter: Az evolúció elméletei és metaforái a társadalomtudományokban Harré, Rom: Cognitive science: A philosophical introduction Horváth György: Pedagógiai pszichológia Marcus, G.: The birth of the mind. How a tiny number of genes creates the complexities of human thought Solso, R. D.: The psychology of art and the evolution of the conscious brain Wray, A. (ed.): The transition to language

The Story Of Computational Narratology

2018 ◽  
Author(s):  
Sharath Srivatsa ◽  
Shyam Kumar V N ◽  
Srinath Srinivasa
Keyword(s):  
Natural Language ◽  
Computational Modeling ◽  
Narrative Structure ◽  
Complex Problem ◽  
General Intelligence ◽  
Language Understanding ◽  
Language Generation ◽  
Narrative Generation ◽  
Growing Body ◽  
Computational Narratology

In recent times, computational modeling of narratives has gained enormous interest in fields like Natural Language Understanding (NLU), Natural Language Generation (NLG), and Artificial General Intelligence (AGI). There is a growing body of literature addressing understanding of narrative structure and generation of narratives. Narrative generation is known to be a far more complex problem than narrative understanding [20].

scholarly journals General Environment Description Language

2021 ◽  
Vol 11 (2) ◽  
pp. 740
Author(s):  
Krzysztof Zatwarnicki ◽  
Waldemar Pokuta ◽  
Anna Bryniarska ◽  
Anna Zatwarnicka ◽  
Andrzej Metelski ◽  
...  
Keyword(s):  
Intelligent Systems ◽  
General Purpose ◽  
The Other ◽  
Potential Fields ◽  
General Intelligence ◽  
Language Usage ◽  
Description Language ◽  
It Systems ◽  
New Research ◽  
Future Work

Artificial intelligence has been developed since the beginning of IT systems. Today there are many AI techniques that are successfully applied. Most of the AI field is, however, concerned with the so-called “narrow AI” demonstrating intelligence only in specialized areas. There is a need to work on general AI solutions that would constitute a framework enabling the integration of already developed narrow solutions and contribute to solving general problems. In this work, we present a new language that potentially can become a base for building intelligent systems of general purpose in the future. This language is called the General Environment Description Language (GEDL). We present the motivation for our research based on the other works in the field. Furthermore, there is an overall description of the idea and basic definitions of elements of the language. We also present an example of the GEDL language usage in the JSON notation. The example shows how to store the knowledge and define the problem to be solved, and the solution to the problem itself. In the end, we present potential fields of application and future work. This article is an introduction to new research in the field of Artificial General Intelligence.

scholarly journals Revisiting the Role of Worries in Explaining the Link Between Test Anxiety and Test Performance

2021 ◽  
Author(s):  
Frieder L. Schillinger ◽  
Jochen A. Mosbacher ◽  
Clemens Brunner ◽  
Stephan E. Vogel ◽  
Roland H. Grabner
Keyword(s):  
University Students ◽  
Standardized Tests ◽  
Test Anxiety ◽  
Test Performance ◽  
Inverse Relationship ◽  
Curvilinear Relationship ◽  
General Intelligence ◽  
Mathematical Competencies ◽  
And Performance

AbstractThe inverse relationship between test anxiety and test performance is commonly explained by test-anxious students’ tendency to worry about a test and the consequences of failing. However, other cognitive facets of test anxiety have been identified that could account for this link, including interference by test-irrelevant thoughts and lack of confidence. In this study, we compare different facets of test anxiety in predicting test performance. Seven hundred thirty university students filled out the German Test Anxiety Inventory after completing a battery of standardized tests assessing general intelligence and mathematical competencies. Multiple regressions revealed that interference and lack of confidence but not worry or arousal explained unique variance in students’ test performance. No evidence was found for a curvilinear relationship between arousal and performance. The present results call for revisiting the role of worries in explaining the test anxiety-performance link and can help educators to identify students who are especially at risk of underperforming on tests.

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