Intelligence, Where to Look, Where to Go?
1. Introduction
- What are the most important scientific issues in the domain of human intelligence?
- What are the most promising new ideas and approaches in the study of human intelligence?
2. Agreement
2.1. Neural Substrate and Processes
2.2. Better Measurement
3. No Divergence
4. Divergence
4.1. Definition?
4.2. How Broad?
4.3. Kind of Variation?
4.4. Genetic Basis?
Conflicts of Interest
Appendix
a) Editorial Board Discussion: First Round Contributions
Andrew R. A. Conway (Princeton University; E-Mail: [email protected])
1. What are in your view the most important scientific issues in the domain of human intelligence?
2. What are the most promising new ideas and approaches in the study of human intelligence?
Richard D. Roberts (ETS; E-Mail: [email protected])
- The field could make better use of the wide variety of psychometric techniques available to make better inferences using imputation and cross-lagged panel designs. Sample sizes in the 1000s should be the norm in this field, which will allow more powerful analysis. It is great that Paul De Boeck serves as the Editor, since he gets the importance of marrying psychometrics and substantive theory.
- Carroll [14] did an awesome job summarizing the state-of-the-art in psychometrics by the end of the 1980s, there is a real need to make revisions to his model based on the cumulative body of work conducted since that time. Indeed, extending the range of first- and second-order constructs within the Cattell-Horn-Carroll model should be a major goal of the field. For example, we still need to resolve how maximal social and emotional abilities fit within this model.
- Cognitive assessment is still very much beholden to the Army Alpha, it would be great to use new technologies (e.g., games, virtual reality) to create more authentic assessments. For example, with the advent of NLP, constructed response should be the norm in assessment and represents a fertile domain for exploring constructs like creativity that have been delimited by paper-and-pencil scoring.
- For both research and potential practical applications, it would seem a real need for automatic item generation that is based on substantive theory.
- The range of outcomes that cognitive ability indicators predict is still not well understood. Solving the criterion problem is essential. There is great potential in using big data to get around this problem.
- Research is highly beholden to funding agencies. I have noted the following are emerging as hot topics across the globe (and do not have direct links to neuroscience): Team intelligence/problem solving; cross cultural intelligence; creativity; is it possible to develop individual differences measures of cognitive biases. There are probably many more, but having such a list would be helpful for anticipatin research trends.
- How this field interfaces with applications (policy, labor economics, clinical, neuroscience) -- and promotes itself in so doing -- is going to be vital in the next couple of decades.
Kaarin J. Anstey (The Australian National University; E-Mail: [email protected])
1. What are in your view the most important scientific issues in the domain of human intelligence?
2. What are the most promising new ideas and approaches in the study of human intelligence?
Tim Croudace (University of York, UK; E-Mail: [email protected])
Julie Aitken Schermer (The University of Western Ontario, Canada; E-Mail: [email protected])
1. What are in your view the most important scientific issues in the domain of human intelligence?
2. What are the most promising new ideas and approaches in the study of human intelligence?
Roberto Colom (Universidad Autónoma de Madrid, Spain; E-Mail: [email protected])
1. What are in your view the most important scientific issues in the domain of human intelligence?
2. What are the most promising new ideas and approaches in the study of human intelligence?
Matthias Ziegler (Humboldt-Universität zu Berlin, Germany; E-Mail: [email protected])
1. What are in your view the most important scientific issues in the domain of human intelligence?
2. What are the most promising new ideas and approaches in the study of human intelligence?
Jeremy R. Gray (Michigan State University; E-Mail: [email protected])
1. What are in your view the most important scientific issues in the domain of human intelligence?
2. What are the most promising new ideas and approaches in the study of human intelligence?
Con Stough (Centre for Human Psychopharmacology; Swinburne University, Melbourne, Australia; E-Mail: [email protected])
Scott Barry Kaufman (New York University; E-Mail: [email protected])
Paul De Boeck(The Ohio State University; E-Mail: [email protected])
1. What are in your view the most important scientific issues in the domain of human intelligence?
2. What are the most promising new ideas and approaches in the study of human intelligence?
Oliver Wilhelm (University Ulm; E-Mail: [email protected])
1. What are in your view the most important scientific issues in the domain of human intelligence?
2. What are the most promising new ideas and approaches in the study of human intelligence?
b) Editorial Board Discussion: Second Round Contributions
Con Stough
Andrew R. A. Conway
Scott Barry Kaufman
Andrew R. A. Conway
Matthias Ziegler
Paul De Boeck
- I would not care about a definition of intelligence, I don’t care about what intelligence really means. Scientific progress does not come from definitions but from findings. I would rather study phenomena and regularities in the data and wait with definitions. Construct validity is not really important. We do not start with constructs, we end with constructs, the constructs we need to explain the data. We have far too many constructs in psychology, including the domain of intelligence. Constructs come and go and they have not helped us much when it comes to understanding. For example, does it help us understand anything when we include emotional intelligence in the construct of intelligence compared with when we don’t? It is rather a semantic discussion how we define a construct. Until we would know how things work. Take analogy problems as another example. What is the surplus of considering these tasks as indicators of intelligence, of inductive intelligence? Let us rather find out how people solve analogy tasks and what the related brain processes are. Are these the same or how much are they related with other cognitive tasks? Etc. I don’t mean related in the correlational sense. The nature of the processes is more important. Correlations are fine but should not dominate the field.
- The psychometrics of intelligence tests and intelligence research is somewhat behind compared with personality and clinical. That is somewhat surprising. I did a study on IRT for psychological tests and it appears that it is mainly used for personality and clinical tests. This remark may seem to contradict my previous remark because IRT is primarily seen as a measurement tool, to measure constructs. I would in fact be more interested in non-measurement uses of IRT, it would be IRT for understanding how respondents come to a correct response or why they fail. That is perfectly possible, since IRT means that the item responses are modeled, as a function of .. and here we have the freedom. We happen to fill that in with individual differences, but that is not the only possibility. Measurement has in the first place a practical purpose, until we know what we are measuring. Measurement is a spin-off of understanding how something works. Measurement does not come first, it comes after. We still don’t know yet what we are measuring, all we know is that the measurement has predictive value. Measurement in itself will not help much when it comes to finding out what the cognitive and brain processes are. And that is where to look to find out eventually about something we may want to call intelligence after all (and give a definition) or perhaps we may want to call it differently.
Roberto Colom
Julie Aitken Schermer
Jeremy R. Gray
References
- What is Intelligence? Sternberg, R.J.; Detterman, D.K. (Eds.) Ablex: Norwood, NJ, USA, 1986.
- Intelligence and its measurement – a symposium. J. Educ. Psychol. 1921, 12, 123–133. [CrossRef]
- Marr, D. Vision; Freeman: San Francisco, USA, 1982. [Google Scholar]
- Thomson, G.H. A hierarchy without a general factor. Brit. J. Psychol. 1916, 8, 271–281. [Google Scholar]
- van der Maas, H.L.J.; Dolan, C.V.; Grasman, R.P.; Wicherts, J.M.; Huizenga, H.M.; Raijmakers, M.E. A dynamical model of general intelligence: The positive manifold of intelligence by mutualism. Psychol. Rev. 2006, 113, 842–861. [Google Scholar] [CrossRef]
- Bartholomew, D.J.; Deary, I.J.; Lawn, M. A new lease of life for Thomson’s bonds model of intelligence. Psychol. Rev. 2009, 116, 567–579. [Google Scholar] [CrossRef]
- Borsboom, D.; Mellenbergh, G.J.; van Heerden, J. The theoretical status of latent variables. Psychol. Rev. 2003, 110, 203–219. [Google Scholar] [CrossRef]
- Kievit, R.A.; van Rooijena, H.; Wichertsa, J.M.; Waldorpa, L.J.; Kanb, K.-J.; Scholtea, H.S.; Borsbooma, D. Intelligence and the brain: A model-based approach. Cognitive Neurosci. 2012, 3, 89–97. [Google Scholar] [CrossRef]
- Engle, R.W.; Kane, M.J. Executive attention, working memory capacity, and a two-factor theory of cognitive control. In The Psychology of Learning and Motivation; Ross, B., Ed.; Academic Press: New York, USA, 2004; pp. 145–199. [Google Scholar]
- Conway, A.R.A.; Kovacs, K. A Process Overlap Theory of the Positive Manifold: A Working Memory Approach. In Presented at the 18th Meeting of the European Society of Cognitive Psychology, Budapest, Hungary, 29 August–1 September 2013.
- Molenaar, D.; Dolan, C.V.; Wicherts, J.M.; van der Maas, H.L.J. Modeling differentiation of cognitive abilities within the higher-order factor model using moderated factor analysis. Intelligence 2010, 38, 611–624. [Google Scholar] [CrossRef]
- Gray, J.R.; Chabris, C.F.; Braver, T.S. Neural mechanisms of general intelligence. Nat. Neurosci. 2003, 6, 316–322. [Google Scholar] [CrossRef]
- Burgess, G.C.; Braver, T.S.; Conway, A.R.A.; Gray, J.R. Neural mechanisms of interference control underlie the relationships between fluid intelligence and working memory span. J. Exp. Psychol. Gen. 2011, 140, 674–692. [Google Scholar] [CrossRef]
- Carroll, J.B. Human Cognitive Abilities: A Survey of Factor-analytic Studies; Cambridge University Press: New York, USA, 1993. [Google Scholar]
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De Boeck, P. Intelligence, Where to Look, Where to Go? J. Intell. 2013, 1, 5-24. https://doi.org/10.3390/jintelligence1010005
De Boeck P. Intelligence, Where to Look, Where to Go? Journal of Intelligence. 2013; 1(1):5-24. https://doi.org/10.3390/jintelligence1010005
Chicago/Turabian StyleDe Boeck, Paul. 2013. "Intelligence, Where to Look, Where to Go?" Journal of Intelligence 1, no. 1: 5-24. https://doi.org/10.3390/jintelligence1010005