Search results
Results from the WOW.Com Content Network
Fluid intelligence is the ability to solve novel reasoning problems and is correlated with a number of important skills such as comprehension, problem-solving, and learning. [4] Crystallized intelligence, on the other hand, involves the ability to deduce secondary relational abstractions by applying previously learned primary relational ...
The worked-example effect is a learning effect predicted by cognitive load theory. [1] [full citation needed] Specifically, it refers to improved learning observed when worked examples are used as part of instruction, compared to other instructional techniques such as problem-solving [2] [page needed] and discovery learning.
Historical examples show that the greater the distance, the less the contacted civilization perceives a threat to itself and its culture. [23] Therefore, contact occurring within the Solar System, and especially in the immediate vicinity of Earth, is likely to be the most disruptive and negative for humanity. [ 23 ]
Wolfgang Köhler's research on the intelligence of apes is an example of research in this area, as is Stanley Coren's book, The Intelligence of Dogs. [42] Non-human animals particularly noted and studied for their intelligence include chimpanzees , bonobos (notably the language-using Kanzi ) and other great apes , dolphins , elephants and to ...
Reading is the process of taking in the sense or meaning of symbols, often specifically those of a written language, by means of sight or touch. [1] [2] [3] [4]For educators and researchers, reading is a multifaceted process involving such areas as word recognition, orthography (spelling), alphabetics, phonics, phonemic awareness, vocabulary, comprehension, fluency, and motivation.
Verbal intelligence is the ability to understand and reason using concepts framed in words. More broadly, it is linked to problem solving , abstract reasoning , [ 1 ] and working memory . Verbal intelligence is one of the most g -loaded abilities.
Intelligence analysis is the application of individual and collective cognitive methods to weigh data and test hypotheses within a secret socio-cultural context. [1] The descriptions are drawn from what may only be available in the form of deliberately deceptive information; the analyst must correlate the similarities among deceptions and extract a common truth.
Many of the early approaches to knowledge represention in Artificial Intelligence (AI) used graph representations and semantic networks, similar to knowledge graphs today. In such approaches, problem solving was a form of graph traversal [2] or path-finding, as in the A* search algorithm. Typical applications included robot plan-formation and ...