scholarly journals The Relation of Scientific Creativity and Evaluation of Scientific Impact to Scientific Reasoning and General Intelligence

2020 ◽  
Vol 8 (2) ◽  
pp. 17 ◽  
Author(s):  
Robert J. Sternberg ◽  
Rebel J. E. Todhunter ◽  
Aaron Litvak ◽  
Karin Sternberg
Keyword(s):  
Scientific Reasoning ◽  
Fluid Intelligence ◽  
Standardized Test ◽  
General Intelligence ◽  
Number Series ◽  
Scientific Creativity ◽  
Scientific Impact ◽  
Impact Studies ◽  
Selective University ◽  
Alternative Hypotheses

In many nations, grades and standardized test scores are used to select students for programs of scientific study. We suggest that the skills that these assessments measure are related to success in science, but only peripherally in comparison with two other skills, scientific creativity and recognition of scientific impact. In three studies, we investigated the roles of scientific creativity and recognition of scientific impact on scientific thinking. The three studies described here together involved 219 students at a selective university in the Northeast U.S. Participants received assessments of scientific creativity and recognition of scientific impact as well as a variety of previously used assessments measuring scientific reasoning (generating alternative hypotheses, generating experiments, drawing conclusions) and the fluid aspect of general intelligence (letter sets, number series). They also provided scores from either or both of two college-admissions tests—the SAT and the ACT—as well as demographic information. Our goal was to determine whether the new tests of scientific impact and scientific creativity correlated and factored with the tests of scientific reasoning, fluid intelligence, both, or neither. We found that our new measures tapped into aspects of scientific reasoning as we previously have studied it, although the factorial composition of the test on recognition of scientific impact is less clear than that of the test of scientific creativity. We also found that participants rated high-impact studies as more scientifically rigorous and practically useful than low-impact studies, but also generally as less creative, probably because their titles/abstracts were seemingly less novel for our participants. Replicated findings across studies included the correlation of Letter Sets with Number Series (both measures of fluid intelligence) and the correlation of Scientific Creativity with Scientific Reasoning.

Understanding the Relationship Between Rationality and Intelligence: A Latent-Variable Approach

2021 ◽  
Author(s):  
Alexander P. Burgoyne ◽  
Cody Mashburn ◽  
Jason S. Tsukahara ◽  
Zach Hambrick ◽  
Randall W Engle
Keyword(s):  
Working Memory ◽  
Latent Variable ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Equation Modeling ◽  
General Intelligence ◽  
Variable Approach ◽  
The Relationship

A hallmark of intelligent behavior is rationality—the disposition and ability to think analytically to make decisions that maximize expected utility or follow the laws of probability, and therefore align with normative principles of decision making. However, the question remains as to whether rationality and intelligence are empirically distinct, as does the question of what cognitive mechanisms underlie individual differences in rationality. In a large sample of participants (N = 331), we used latent variable analyses to assess the relationship between rationality and intelligence. The results indicated that there was a common ability underpinning performance on some, but not all, rationality tests. Latent factors representing rationality and general intelligence were strongly correlated (r = .54), but their correlation fell well short of unity. Indeed, after accounting for variance in performance attributable to general intelligence, rationality measures still cohered on a latent factor. Confirmatory factor analysis indicated that rationality correlated significantly with fluid intelligence (r = .56), working memory capacity (r = .44), and attention control (r = .49). Structural equation modeling revealed that attention control fully accounted for the relationship between working memory capacity and rationality, and partially accounted for the relationship between fluid intelligence and rationality. Results are interpreted in light of the executive attention framework, which holds that attention control supports information maintenance and disengagement in service of complex cognition. We conclude by speculating about factors rationality tests may tap that other cognitive ability tests miss, and outline directions for further research.

scholarly journals The Relation of Tests of Scientific Reasoning to Each Other and to Tests of General Intelligence

2019 ◽  
Vol 7 (3) ◽  
pp. 20 ◽  
Author(s):  
Robert J. Sternberg ◽  
Chak Haang Wong ◽  
Karin Sternberg
Keyword(s):  
Standardized Tests ◽  
Scientific Reasoning ◽  
Ecological Validity ◽  
Multiple Choice ◽  
General Intelligence ◽  
Psychological Science ◽  
Ability Tests ◽  
The One ◽  
The Cost ◽  
Scientific Reasoning Skills

We conducted two studies to replicate and extend, as well as test, the limits of previous findings regarding an apparent disconnect between scientific-reasoning skills in psychological science, on the one hand, and scores on standardized tests of general intelligence, on the other. In Study 1, we examined whether this disconnect would extend beyond psychological science to additional sciences as well, such as nutrition and agriculture. The results did indeed extend, suggesting that scientific reasoning across various natural sciences is comparable to scientific reasoning in psychological science, but different in kind from the reasoning required on conventional standardized tests. In Study 2, we examined whether these findings were linked to the format of presentation of scientific problems. Whereas real scientific-reasoning problems are open-ended, standardized tests tend to use multiple-choice format. We discovered that using multiple-choice format did indeed result in an apparently closer relation of the scientific-reasoning tests to two of the conventional ability measures (SAT Reading and Number Series) but not to two other tests (Letter Sets and SAT Math). Thus, one can increase the correlations of scientific-reasoning tests with at least some standardized ability tests but at the cost of content validity and ecological validity.

Scientific Reasoning in Higher Education

2015 ◽  
Vol 223 (1) ◽  
pp. 47-53 ◽  
Author(s):  
Stefan Hartmann ◽  
Annette Upmeier zu Belzen ◽  
Dirk Krüger ◽  
Hans Anand Pant
Keyword(s):  
Science Teachers ◽  
Natural Science ◽  
Scientific Reasoning ◽  
Standardized Test ◽  
Multiple Choice ◽  
Natural Sciences ◽  
Preservice Science Teachers ◽  
Reasoning Skills ◽  
Scientific Reasoning Skills ◽  
Better Than

The aim of this study was to develop a standardized test addressed to measure preservice science teachers’ scientific reasoning skills, and to initially evaluate its psychometric properties. We constructed 123 multiple-choice items, using 259 students’ conceptions to generate highly attractive multiple-choice response options. In an item response theory-based validation study (N = 2,247), we applied multiple regression analyses to test hypotheses based on groups with known attributes. As predicted, graduate students performed better than undergraduate students, and students who studied two natural science disciplines performed better than students who studied only one natural science discipline. In contrast to our initial hypothesis, preservice science teachers performed less well than a control group of natural sciences students. Remarkably, an interaction effect of the degree program (bachelor vs. master) and the qualification (natural sciences student vs. preservice teacher) was found, suggesting that preservice science teachers’ learning opportunities to explicitly discuss and reflect on the inquiry process have a positive effect on the development of their scientific reasoning skills. We conclude that the evidence provides support for the criterion-based validity of our interpretation of the test scores as measures of scientific reasoning competencies.

The evolution of fluid intelligence meets formative g

2017 ◽  
Vol 40 ◽  
Author(s):  
Kristof Kovacs ◽  
Andrew R. A. Conway
Keyword(s):  
Working Memory ◽  
Problem Solving ◽  
Executive Functions ◽  
Fluid Intelligence ◽  
General Factor ◽  
General Intelligence ◽  
Common Cause ◽  
General Ability ◽  
Target Article ◽  
The Common

AbstractThe argument by Burkart et al. in the target article relates to fluid (not general) intelligence: a domain-general ability involved in complex, novel problem solving, and strongly related to working memory and executive functions. A formative framework, under which the general factor of intelligence is the common consequence, not the common cause of the covariance among tests is more in line with an evolutionary approach.

Can fluid and general intelligence be differentiated in an older adult population?

2006 ◽  
Vol 29 (2) ◽  
pp. 143-145 ◽  
Author(s):  
Nancy A. Zook ◽  
Deana B. Davalos
Keyword(s):  
Older Adults ◽  
Cognitive Decline ◽  
Frontal Lobe ◽  
Older Adult ◽  
Cognitive Functions ◽  
Fluid Intelligence ◽  
Adult Population ◽  
General Intelligence ◽  
Older Adult Population ◽  
Pattern Of Performance

The question of whether fluid intelligence can be differentiated from general intelligence in older adults is addressed. Data indicate that the developmental pattern of performance on fluid tasks differs from the pattern of general intelligence. These results suggest that it is important to identify changes in fluid cognitive functions associated with frontal lobe decline, as they may be early indicators of cognitive decline.

scholarly journals Fluid Intelligence: Review of Foreign Studies

2018 ◽  
Vol 7 (4) ◽  
pp. 19-43 ◽  
Author(s):  
I.E. Rzhanova ◽  
V.S. Britova ◽  
O.S. Alekseeva ◽  
Yu.A. Burdukova
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Cognitive Deficits ◽  
Cognitive Abilities ◽  
Clinical Evidence ◽  
Fluid Intelligence ◽  
General Intelligence ◽  
Children With Adhd ◽  
Fluid Reasoning ◽  
The Relationship

The present review focuses on modern research of fluid intelligence. The concept of fluid intelligence, the place of fluid intelligence in the structure of cognitive abilities, its relation to general intelligence is revealed. The current models of fluid intelligence are considered, including the current leading Cattell–Horn–Carroll model. The neurobiological processes underlying the flexibility of fluid reasoning processes in solving novel problems are discussed. In particular, studies are presented showing that fluid intelligence is mediated by subregions of the prefrontal cortex. Studies of the relationship between fluid intelligence and working memory, as well as studies of fluid intelligence in clinical groups such as children with ADHD and adults with schizophrenia are also discussed. Clinical evidence suggests that fluid intelligence may be key to understanding the structure of cognitive deficits in ADHD syndrome.

Difficulties differentiating dissociations

2006 ◽  
Vol 29 (2) ◽  
pp. 138-139 ◽  
Author(s):  
Kristof Kovacs ◽  
Kate C. Plaisted ◽  
Nicholas J. Mackintosh
Keyword(s):  
Fluid Intelligence ◽  
General Intelligence ◽  
The Relationship

We welcome Blair's argument that the relationship between fluid cognition and other aspects of intelligence should be an important focus of research, but are less convinced by his arguments that fluid intelligence is dissociable from general intelligence. This is due to confusions between (a) crystallized skills and g, and (b) universal and differential constructs.

scholarly journals Expertise Within Working Memory and Fluid Intelligence

2019 ◽  
Author(s):  
Addie Wikowsky ◽  
Erin Michelle Buchanan
Keyword(s):  
Working Memory ◽  
Fluid Intelligence ◽  
Critical Factor ◽  
Quality Measures ◽  
Psychology Students ◽  
General Intelligence ◽  
State University ◽  
Previous Knowledge ◽  
The Relationship ◽  
Typing Task

Working memory, fluid intelligence, and expertise are all psychological concepts that have been explored in the field. Working memory, defined by Baddeley (1986), is the temporary storage of stimuli presented to a person. The relationship between working memory and fluid intelligence is a common theme among studies. Fluid intelligence is one of the components of general intelligence (g). Specifically, fluid intelligence can be described as being able to adapt thinking, even with no previous knowledge (Jaeggi, Buschkuehl, Jonides, & Perrig, 2008). Expertise is another critical factor in these studies and is the acquisition of knowledge and being able to apply that knowledge (Chi, Glaser, & Rees, 1982). This thesis looks at the inter-relationships of those concepts in Missouri State University psychology students. The researchers confirmed the previously noted relationship between working memory and fluid intelligence (r = .50), but there were no other significant correlations between the tasks. It was interesting that working memory and fluid intelligence had similar correlations for the typing task (r = .23, r = .19), although not significant. These effects disappeared after controlling for the data quality measures used in the study (i.e., ways to show the participants put effort into the study). More research is needed to confirm that the current measures of expertise, or different ones, are related to working memory or fluid intelligence.

Phlogiston, fluid intelligence, and the Lynn–Flynn effect

2006 ◽  
Vol 29 (2) ◽  
pp. 142-143 ◽  
Author(s):  
Martin Voracek
Keyword(s):  
Fluid Intelligence ◽  
General Intelligence ◽  
Phlogiston Theory ◽  
Flynn Effect ◽  
Cumulative Evidence

Blair's assertion that fluid intelligence (gF) is distinct from general intelligence (g) is contradictory to cumulative evidence from intelligence research, including extant and novel evidence about generational IQ gains (Lynn–Flynn effect). Because of the near unity of gF and g, his hypothetical concept of gF' (gF “purged” of g variance) may well be a phlogiston theory.

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