Intelligence
It is one of the most solid and useful psycological concepts used in order to predict success and performance, not only regarding academy, but also at work and in life.
But it is equally misunderstood by laymen, and even by professionals from psycology, coaching, HR, etc. And surprisingly, not commonly used as an important criterium for selection and promotion.(See Las empresas prefieren la inteligencia emocional al cociente intelectual)
So if you really want to have a good basis to understand intelligence, here is a great lecture by Jordan Peterson. He tells us many interesting scientific studies regarding this polemic issue.
If you work of have an interest in human performance you cannot miss it. Give yourself some time for this free lecture and you’ll feel more intelligent after it! 😉
- What is and what is not intelligence?
- Why is it important?
- What is its structure? Are there many independent intelligences or is there a common G factor?
- How can we measure intelligence?
- What are the 2 main predictors of success?
- How does it relate to the Big Five personality traits?
- Why later and more fashionable theories like «emotional intelligence», «multiple intelligences», etc. are questionable to say the least?
- Can we improve intelligence through training?
- What are the most suitable jobs for different levels of intelligence?
If you want a broader overview on psycology, you may also be interested in this post: Revolución en la psicología
As much as I admire Peterson, I must also suggest other models of intelligence. A short summary (source Wikipedia):
Fluid and crystallized intelligence
According to the theory published in 1971 by the psychologist Raymond Cattell,[1][2] general intelligence (g) is subdivided into fluid intelligence (gf) and crystallized intelligence (gc). 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.[3] Crystallized intelligence on the other hand is the ability to deduce secondary relational abstractions by applying primary relational abstractions to each other.[4]
Carroll’s three stratum theory
The three-stratum theory is a theory of cognitive ability proposed by the American psychologist John Carroll in 1993.[1][2] It is based on a factor-analytic study of the correlation of individual-difference variables from data such as psychological tests, school marks and competence ratings. These analyses suggested a three-layered model where each layer accounts for the variations in the correlations within the previous layer.
The three layers (strata) are defined as representing narrow, broad, and general cognitive ability. The factors describe stable and observable differences among individuals in the performance of tasks. Carroll argues further that they are not mere artifacts of a mathematical process, but likely reflect physiological factors explaining differences in ability (e.g., nerve firing rates). This does not alter the effectiveness of factor scores in accounting for behavioral differences.
By Tim bates – Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=24564663
Cattell–Horn–Carroll
The Cattell–Horn–Carroll theory is an integration of two previously established theoretical models of intelligence: the Gf-Gc theory of fluid and crystallised intelligence (Cattell, 1941; Horn 1965), and Carroll’s three-stratum theory (1993), a hierarchical, three-stratum model of intelligence.
Today, the Cattell–Horn–Carroll theory is considered by some to be the most comprehensive and empirically supported theory of cognitive abilities, informing a substantial body of research and the ongoing development of IQ (Intelligence Quotient) tests.[4]
The broad abilities are:[22]
- Comprehension-Knowledge (Gc): includes the breadth and depth of a person’s acquired knowledge, the ability to communicate one’s knowledge, and the ability to reason using previously learned experiences or procedures.
- Fluid reasoning (Gf): includes the broad ability to reason, form concepts, and solve problems using unfamiliar information or novel procedures.
- Quantitative knowledge (Gq): is the ability to comprehend quantitative concepts and relationships and to manipulate numerical symbols.[22]
- Reading & Writing Ability (Grw): includes basic reading and writing skills.
- Short-Term Memory (Gsm): is the ability to apprehend and hold information in immediate awareness and then use it within a few seconds.
- Long-Term Storage and Retrieval (Glr): is the ability to store information and fluently retrieve it later in the process of thinking.
- Visual Processing (Gv): is the ability to perceive, analyze, synthesize, and think with visual patterns, including the ability to store and recall visual representations.
- Auditory Processing (Ga): is the ability to analyze, synthesize, and discriminate auditory stimuli, including the ability to process and discriminate speech sounds that may be presented under distorted conditions.[22]
- Processing Speed (Gs): is the ability to perform automatic cognitive tasks, particularly when measured under pressure to maintain focused attention.
- Decision/Reaction Time/Speed (Gt): reflects the immediacy with which an individual can react to stimuli or a task (typically measured in seconds or fractions of seconds; not to be confused with Gs, which typically is measured in intervals of 2–3 minutes).
McGrew proposes a number of extensions to CHC theory, including Domain-specific knowledge (Gkn), Psychomotor ability (Gp), and Psychomotor speed (Gps). In addition, additional sensory processing abilities are proposed, including tactile (Gh), kinesthetic (Gk), and olfactory (Go).[1]
The narrow abilities are:
| Quantitative knowledge | Reading & writing | Comprehension-Knowledge | Fluid reasoning | Short-term memory | Long term storage and retrieval | Visual processing | Auditory processing | Processing speed |
|---|---|---|---|---|---|---|---|---|
| Mathematical knowledge | Reading decoding | General verbal information | Inductive reasoning | Memory span | Associative memory | Visualization | Phonetic coding | Perceptual speed |
| Mathematical achievement | Reading comprehension | Language development | General sequential reasoning | Working memory capacity | Meaningful memory | Speeded rotation | Speech sound discrimination | Rate of test taking |
| Reading speed | Lexical knowledge | Deductive reasoning | Free-recall memory | Closure speed | Resistance to auditory stimulus distortion | Number facility | ||
| Spelling ability | Listening ability | Piagetian reasoning | Ideational fluency | Flexibility of closure | Memory for sound patterns | Reading speed/fluency | ||
| English usage | Communication ability | Quantitative reasoning | Associative fluency | Visual memory | Maintaining and judging rhythms | Writing speed/fluency | ||
| Writing ability | Grammatical sensitivity | Speed of reasoning | Expressional fluency | Spatial scanning | Musical discrimination and judgement | |||
| Writing speed | Oral production & fluency | Originality | Serial perceptual integration | Absolute pitch | ||||
| Cloze ability | Foreign language aptitude | Naming facility | Length estimation | Sound localization | ||||
| Word fluency | Perceptual illusions | Temporal tracking | ||||||
| Figural fluency | Perceptual alternations | |||||||
| Figural flexbility | Imagery | |||||||
| Learning ability |
G-VPR
The g-VPR model is a model of human intelligence published in 2005 by psychology professors Wendy Johnson[1] and Thomas J. Bouchard Jr. (Johnson & Bouchard, 2005)[2] They developed the model by analyzing Gf-Gc theory, John Carroll’s Three-stratum theory and Vernon’s verbal-perceptual model.[2]
The g-VPR model is a four stratum model:
- First stratum: Primary traits.
- Second stratum: Broader than stratum I, but still narrow abilities.
- Third stratum: Verbal, perceptual and rotation factors.
- Fourth stratum: g factor.
