The locus of adult intelligence: Knowledge, abilities, and nonability traits.

Ackerman, Phillip L.; Rolfhus, Eric

doi:10.1037/0882-7974.14.2.314

Cited by 140 publications

(129 citation statements)

References 37 publications

(78 reference statements)

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“…It should be noted that, although older people showed impaired performance on the People Pieces Analogy task, this task does not test crystallized intelligence and semantic knowledge, which appear to be relatively preserved with age (Ackerman & Rolfhus, 1999;Lindenberger & Baltes, 1997). Rather, the task used in the current study taps fluid intelligence, which has been shown to decline with age (Isingrini & Vazou, 1997).…”

Section: Discussionmentioning

confidence: 99%

Relational Integration, Inhibition, and Analogical Reasoning in Older Adults.

Viskontas¹,

Morrison²,

Holyoak³

et al. 2004

Psychology and Aging

123

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The difficulty of reasoning tasks depends on their relational complexity, which increases with the number of relations that must be considered simultaneously to make an inference, and on the number of irrelevant items that must be inhibited. The authors examined the ability of younger and older adults to integrate multiple relations and inhibit irrelevant stimuli. Young adults performed well at all but the highest level of relational complexity, whereas older adults performed poorly even at a medium level of relational complexity, especially when irrelevant information was presented. Simulations based on a neurocomputational model of analogical reasoning, Learning and Inference with Schemas and Analogies (LISA), suggest that the observed decline in reasoning performance may be explained by a decline in attention and inhibitory functions in older adults.Human reasoning depends in part on the ability to integrate multiple relations and inhibit irrelevant information. For example, if Bill is taller than Carl and Abe is taller than Bill, one must integrate the two "taller than" relations to make the inference that Abe is taller than Carl. A relational analysis of reasoning provides a framework that makes it possible to define levels of complexity for particular reasoning tasks. According to Halford (1998;Halford & Wilson, 1980;Halford, Wilson, & Phillips, 1998), the processing load for any step in a task is determined by the number of dimensions, or relations, that must be processed simultaneously to make the decisions required for that step. Dimensions are viewed as analogous to degrees of freedom, or the number of independent sources of variation. At the first level of complexity (Level 1), the reasoner needs to consider only one relation to solve the task correctly.1 At Level 2, the reasoner must integrate two relations, and so on. For example, it is necessary to integrate two relations to correctly solve the transitive inference problem described previously.More generally, we define relational complexity as the number of relations that a reasoner must simultaneously "hold in mind" to generate the solution. This framework makes it possible to study the processing demands of complex reasoning and to better characterize changes in reasoning ability that occur during normal aging. Although it is known that reasoning ability declines with age (for reviews, see Salthouse, 1992aSalthouse, , 2005, the underlying mechanisms of this decline are not well established. In the current study, we investigate the effects of age on the ability to solve a complex analogical reasoning problem and consider possible algorithmic reasons for the observed decline with age.The ability to hold in mind multiple relations relies on working memory capacity. (See Morrison, 2005, for a review of the role of working memory in reasoning.) Miller (1956) originally postulated that the processing capacity of what is now called working memory is seven plus or minus two "chunks," which are independent units of information. This estimate has since bee...

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Section: Discussionmentioning

confidence: 99%

Relational Integration, Inhibition, and Analogical Reasoning in Older Adults.

Viskontas¹,

Morrison²,

Holyoak³

et al. 2004

Psychology and Aging

123

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“…Control beliefs and self-efficacy predict cognitive performance and activities, but they are only one part of a larger set of interrelated traits and attributes that predict activities and cognition and that could account for cognitive-enrichment effects (e.g., Ackerman & Rolfhus, 1999). For example, recent research indicates that goal setting and planning are also important for initiating and maintaining physical-exercise routines (e.g., Armitage & Conner, 2000;Huang, Lee, & Chang, 2007;Scholz, Sniehotta, Schuez, & Oeberst, 2007).…”

Section: Positive Attitudes and Beliefsmentioning

confidence: 99%

“…Individuals select particular areas in which they invest time, energy, and cognitive resources to gain knowledge and experience (Ackerman, 2000;Ackerman & Rolfhus, 1999;Baltes, 1997;Beier & Ackerman, 2005;Cattell, 1971). Some aspects of cognitive function, particularly those heavily imbued with knowledge or experience (what Baltes, 1997, refers to as the pragmatics of cognition), will be relatively well preserved in adulthood, provided that the performance context does not introduce performance-specific constraints due to challenges to impaired processing mechanisms (e.g., Hertzog, 1989).…”

Section: Conceptual Frameworkmentioning

confidence: 99%

Enrichment Effects on Adult Cognitive Development

Hertzog

Kramer

Wilson

et al. 2008

Psychol Sci Public Interest

1,136

464

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SUMMARY-In this monograph, we ask whether various kinds of intellectual, physical, and social activities produce cognitive enrichment effects-that is, whether they improve cognitive performance at different points of the adult life span, with a particular emphasis on old age.We begin with a theoretical framework that emphasizes the potential of behavior to influence levels of cognitive functioning. According to this framework, the undeniable presence of age-related decline in cognition does not invalidate the view that behavior can enhance cognitive functioning. Instead, the course of normal aging shapes a zone of possible functioning, which reflects person-specific endowments and age-related constraints. Individuals influence whether they function in the higher or lower ranges of this zone by engaging in or refraining from beneficial intellectual, physical, and social activities. From this point of view, the potential for positive change, or plasticity, is maintained in adult cognition. It is an argument that is supported by newer research in neuroscience showing neural plasticity in various aspects of central nervous system functioning, neurochemistry, and architecture. This view of human potential contrasts with static conceptions of cognition in old age, according to which decline in abilities is fixed and individuals cannot slow its course. Furthermore, any understanding of cognition as it occurs in everyday life must make a distinction between basic cognitive mechanisms and skills (such as working-memory capacity) and the functional use of cognition to achieve goals in specific situations. In practice, knowledge and expertise are critical for effective functioning, and the available evidence suggests that older adults effectively employ specific knowledge and expertise and can gain new knowledge when it is required.We conclude that, on balance, the available evidence favors the hypothesis that maintaining an intellectually engaged and physically active lifestyle promotes successful cognitive aging. First, cognitive-training studies have demonstrated that older adults can improve cognitive functioning when provided with intensive training in strategies that promote thinking and remembering. The early training literature suggested little transfer of function from specifically trained skills to new cognitive tasks; learning was highly specific to the cognitive processes targeted by training. Recently, however, a new generation of studies suggests that providing structured experience in situations demanding executive coordination of skillssuch as complex video games, task-switching paradigms, and divided attention tasks-train strategic control over cognition that does show transfer to different task environments. These studies suggest that there is considerable reserve potential in older adults' cognition that can be enhanced through training.Second, a considerable number of studies indicate that maintaining a lifestyle that is intellectually stimulating predicts better maintenance of cognitive skills and is a...

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“…Age-related growth in pragmatics and knowledge-based systems is evident in verbal intellectual functions, as well as in world knowledge and acculturation, and particularized knowledge systems that grow as a function of one's choice of engagement (Ackerman & Rolfhus, 1999;Hoyer, Rybash, & Rooodin, 1989;Schaie, 1994;Stanovich, West, & Harrison, 1995). There appears to be a reciprocal relationship between ability and discourse processing.…”

Section: The Nature Of Cognitive Agingmentioning

confidence: 99%

Aging and self-regulated language processing.

Stine‐Morrow

Miller

Hertzog

2006

Psychological Bulletin

164

170

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This paper introduces an adult developmental model of self-regulated language processing (SRLP), in which the allocation policy with which a reader engages text is driven by declines in processing capacity, growth in knowledge-based processes, and age-related shifts in reading goals. Evidence is presented to show that the individual reader's allocation policy is consistent across time and across different types of text, can serve a compensatory function in relation to abilities, and is predictive of subsequent memory performance. As such, it is an important facet of language understanding and learning from text through the adult life span.

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The locus of adult intelligence: Knowledge, abilities, and nonability traits.

Cited by 140 publications

References 37 publications

Relational Integration, Inhibition, and Analogical Reasoning in Older Adults.

Relational Integration, Inhibition, and Analogical Reasoning in Older Adults.

Enrichment Effects on Adult Cognitive Development

Aging and self-regulated language processing.

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