1 - The Interplay of Growth and Decline: Theoretical and Empirical Aspects of Plasticity of Intellectual and Memory Performance in Normal Old Age
Editors: Backman, Lars; Hill, Robert D.; Neely, Anna Stigsdotter
Title: Cognitive Rehabilitation in Old Age, 1st Edition
Copyright 2000 Oxford University Press
> Table of Contents > Part I - Theory-Driven Guidelines for Cognitive Rehabilitation Strategies in Older Adults > 3 - Cognitive Skill Acquisition, Maintenance, and Transfer in the Elderly
3
Cognitive Skill Acquisition, Maintenance, and Transfer in the Elderly
Michael K. Gardner
David L. Strayer
Dan J. Woltz
Robert D. Hill
Skills refer to knowledge of how to perform some action rather than knowledge of some facts or events (Schmidt & Bjork, 1992). These two forms of knowledge are in some cases independent of one another. A person can know how to drive an automobile without factual knowledge of how the automobile works. Conversely, a person could study technical manuals and learn about how the various components of an automobile function, but this knowledge would not be of much help in driving if that person had not practiced the skill of driving. People often do not think of everyday skills as knowledge, and older individuals may be much more conscious of their memory for factual information than of their memory for skills (see Kausler, 1991). Yet, it is likely that their proficiency in relatively simple cognitive skills is a greater determinant of their life satisfaction than is the extent of their factual knowledge base.
As the population ages, the problem of skill usage becomes abundantly clear. In order to maintain a normal, active life, older individuals need to do three things: (a) maintain skills acquired during earlier life, (b) transfer these skills to new settings and situations, and (c) acquire new skills to deal with problems that existing skills cannot handle. Some examples will make these categories clear.
Most individuals learn to find their way around their neighborhood during their younger years. During later years, the navigation skills that they developed earlier are equally important. Indeed, with retirement, one could assume that older individuals may spend more time out and about in their local neighborhoods. Thus, they must maintain their implicit knowledge of local geography and transportation systems (see Atchley, 1980).
Likewise, during young adulthood, individuals acquire a knowledge of how to
P.43
create a schedule and monitor adherence to it. During later adulthood, this skill may need to be maintained even though the demand for scheduling formal appointments and meetings may not be as high. For example, an older adult may require one or more medications to control various medical conditions. In this regard, scheduling and timing of the taking of medications may require the application of the learned skills described above.
Banking and financial management is another area where skills are acquired during youth and middle age and must continue to be applied during old age. The ability to budget spending is often most important in later life, when income is more limited and fixed (see Atchley, 1980). These are just a few everyday examples that demonstrate the importance of skill maintenance. Skills acquired early in life must be kept active and well honed so that they can continue to be used in later life.
Sometimes changes in the environment and situation require more than simple skill maintenance: They require that a skill be slightly modified and/or transferred to conditions that differ to some degree from the conditions that existed when the original skills were acquired (Salomon & Perkins, 1989). Finding one's way around the neighborhood requires developing a cognitive map of the neighborhood, including salient landmarks. One who later moves to a retirement community will need to develop a new cognitive map to find his or her way about. Failure to develop one may result in a significant decrease in the enjoyment of a new environment. As noted, the schedule-monitoring skill may also require some updating. Declines in health may increase the number and frequency of medication administrations. Not only will the actual medications change, but the skills that relied on internal cues ( remembering to take a pill) may need to be supplemented by external cues (a digital watch that beeps as a reminder to take a pill; see Park et al, 1994). Likewise, banking and financial management skills may need to be transferred to new institutions and situations. An example of a common financial task frequently encountered by most people is withdrawing money from an automatic teller machine (ATM). Because ATMs have replaced many of the person-to-person banking processes (e.g., providing a paper withdrawal request to a bank teller), older adults must transfer their traditional banking skills to this new context (inserting an ATM card into a machine and entering a personal access code number) if they desire maximum access to their money.
Skill transfer may also occur in subtle situations. Older adults may need to change the way they interact with those around them as caregivers change and friends move or die. Interpersonal skills that were effective in dealing with one individual may be ineffective with another. In short, an older person may be required to adapt to his or her environment, and adaptation often means transferring skills to new and different situations.
Sometimes skills learned long ago must be called upon or relearned. After the loss of a spouse, an older widower may find that he has responsibilities in everyday life that were taken care of by the departed spouse (e.g., cooking, banking). These may be skills that he learned and used decades earlier but has used infrequently in recent years.
Even if individuals can maintain and transfer their existing skills, changes in the environment will require that new skills be learned. The ever-quickening pace of change in our society, especially in the area of technology, requires that we learn to do things that were unheard of only 20 years ago (Michio, 1997; Pickover, 1992).
P.44
Computers now permeate almost all areas of commerce and information dispersal. Finding books in many libraries requires a computer search. Many individuals communicate via electronic mail, use the Internet to arrange travel plans and lodging, and conduct electronic banking. These operations require an understanding of how to operate a computer: how to log on, how to use a modem, and how to save and print files. For many older adults, these are new skills that must be acquired.
Technology and the new skill it requires, has also spilled over into how citizens (including older adults) interact with the government. Many businesses and government agencies are experimenting with new technologically based means of dispersing payments and services (e.g., smart cards ; see Fancer, 1996; Gauthier, 1996). These changes will require that older adults learn how utilize the new technologies or possibly miss out on their fair share of opportunities for obtaining goods and services.
As the population not only ages but also expands, transportation systems change. Those who once drove on highways may find themselves taking light rail systems instead of more familiar buses. These new transportation systems may require understanding how to get and use fare cards, such as those used in Washington's Metro railway, and reading maps of systemwide connections and transfers.
New skills will also be required as the elderly engage in new hobbies and work endeavors. As their interests and employment opportunities shift, they will be faced with new challenges that their current skill repertoire may only partially address. Thus, the ability to acquire new skills will in part determine the degree of satisfaction (e.g., the ability to engage in hobbies) and the standard of living (e.g., the ability to make changes that allow one to remain in the workforce) of older individuals.
The Distinction Between Declarative and Procedural Knowledge
To understand cognitive skills, it's important to understand the distinction between declarative knowledge and procedural knowledge. We introduced this distinction earlier as knowledge of and how to. This distinction (using slight variants in terminology) is made in several prominent theories of learning and memory (e.g., Anderson, 1983; Fitts & Posner, 1967; Schneider & Shiffrin, 1977; Shiffrin & Schneider, 1977; Squire, 1987). Declarative knowledge consists of sets of facts or lists of words or sentences. Declarative knowledge is what we are testing when we ask someone to remember a list of words or the list of things we need at the supermarket. Declarative knowledge is knowledge of, for instance, (a) What did you do yesterday? (b) What is your nephew's name? (c) What is the capital of North Dakota?
Procedural knowledge is memory for the procedures used to do things. We usually demonstrate procedural knowledge by performing a skill, rather than retrieving a set of facts. Procedural knowledge asks how to rather than requiring knowledge of. Procedural skills include (a) how to ride a bicycle, (b) how to balance a checkbook, and (c) how to find one's way home from the doctor's office.
Another important distinction is between explicit and implicit memory (Squire, 1987). Explicit memory is open to conscious introspection and is usually volitional (that is, it involves a conscious attempt to recall or recognize something). Declarative knowledge is usually associated with explicit memory. Implicit memory is not open
P.45
to conscious introspection and is nonvolitional (that is, it does not require a conscious attempt to recall or recognize something). Procedural knowledge is usually associated with implicit memory.
In this chapter, we describe methods of improving cognitive skills that are procedural, and the parameters that affect such methods. Thus, we deal with procedural knowledge and implicit memory. In the real world, however, the distinction is not as clear-cut as it might seem at first. Even though cognitive skills are primarily procedural knowledge in the form of implicit memory, these skills must make use of and interact with declarative knowledge in the form of explicit memory. Thus, deficits in both kinds of knowledge (and types of memory) are relevant to the acquisition, maintenance, transfer, and performance of the skill. In this chapter, we focus our discussion on cognitive skill issues relating to the normal course of aging. We do not address problems related to neuropsychological conditions such as Alzheimer's disease, stroke, and dementia. While such conditions undoubtedly affect cognitive skills, an analysis of their impact on skill acquisition, maintenance, and transfer is beyond the scope of this chapter.
Cognitive Problems Associated With Normal Aging
A number of cognitive problems are associated with normal aging. We briefly review them in this section because these deficits impact what strategies are effective in training cognitive skills in the elderly.
Fluid Versus Crystallized Abilities
Cattell and Horn (Cattell, 1963, 1971; Horn, 1970, 1982; Horn & Cattell, 1966) proposed a theory of intelligence that divides general intelligence into two related types: fluid intelligence and crystallized intelligence. Fluid intelligence represents the basic biological capacity to learn (including the ability to acquire new skills), and crystallized intelligence represents the products of acculturation or acquired knowledge (Gardner & Clark, 1992; Kausler, 1991). Horn and Cattell (1966) initially reported different developmental courses for fluid and crystallized intelligence. Fluid intelligence peaks somewhere during the 20s, and declines thereafter, while crystallized intelligence appears to increase in the 20s and 30s then remain stable throughout the life span (Gilinksy & Judd, 1994; Sternberg & Powell, 1983), although some research has suggested that in very late life (70+ years), even crystallized intelligence declines (B ckman & Nilsson, 1996; Giambra, Arenberg, Zonderman, Kawas, & Costa, 1995; Lindenberger & Baltes, 1997). The evidence in support of the fluid-crystallized intelligence distinction comes primarily from cross-sectional studies using traditional intelligence tests (LaRue, 1992; Lindenberger & Baltes, 1997), such as the various Wechsler scales (Wechsler, 1944, 1955, 1981). More specifically, the performance subtests (e.g., Picture Completion, Picture Arrangement, Block Design, Object Assembly, and Digit Symbol) have been taken as measures of fluid ability, while the Information, Vocabulary, Similarities, and Comprehension subtests have been taken as measures of crystallized intelligence (see Kausler, 1991; LaRue, 1992; Salthouse, 1991b). Note
P.46
that fluid tests generally place a premium on speed of correct responding, while crystallized tests tend to place greater emphasis on correctness of the response.
The decline in fluid ability is important to the extent that it indicates a reduced capacity to acquire new cognitive skills. The Horn and Cattell theory attributes this reduced capacity to a deterioration of the underlying neural systems that support new learning. However, the true state of affairs is considerably more complicated. First, does the picture that Horn and Cattell initially presented reveal itself in longitudinal studies as well as in the cross-sectional studies that gave rise to the theory? The answer is not exactly. Longitudinal studies (e.g., Schaie, 1979, 1983a, 1983b; Schaie & Hertzog, 1986; Schaie & Strother, 1968) have found that many fluid abilities are relatively stable in young adulthood in some instances until age 50 and then decline in very old age (Schaie & Willis, 1991). As noted earlier, research suggests that in very old age, even crystallized abilities appear to decline (see B ckman & Nilsson, 1996; Hultsch, Hertzog, Small, McDonald-Miszczak, & Dixon, 1992; Giambra et al., 1995).
Cohort effects may influence changes in fluid ability performance (see Kausler, 1991). Cohort effects refer to the fact that in a cross-sectional study, the age of the participant is confounded with the date of birth. For instance, individuals in their 60s were all born approximately 60 years ago and had different environmental influences from those born 40 years ago. This is not the case in a longitudinal study because we follow individuals born at different times until they become a given age. The cohort effect can be important if, during certain periods of time, certain skills were emphasized by society or, conversely, were neglected by society. In that case, effects that we would wish to attribute to aging might really be due to differences in the sociocultural context over time. Schaie (1990; see also Schaie & Willis, 1991; Nilsson et al., 1997) has shown that cohort effects do indeed exist, with some abilities increasing over cohorts as we move toward the present, some decreasing, and others remaining relatively stable. The existence of these cohort effects argues for caution in drawing too strong a conclusion from the cross-sectional data that indicate a decline in fluid ability after early adulthood.
Given that there is a precipitous decline in fluid ability in very old age particularly, at least after age 60, any attempt to teach new cognitive skills must take this decline into account. This decline cannot be attributed solely to older individuals' having a slower rate of processing. Two studies (Doppelt & Wallace, 1955; Storandt, 1977) compared older and younger samples on timed and untimed versions of the performance subtests of the WAIS. Although older samples benefited more than younger subjects from the removal of the time constraints, their performance level did not reach that of the younger sample (LaRue, 1992); likewise, performance in timed and untimed conditions was highly correlated (greater than 0.85). Some hope is offered by training studies that have intervened in an attempt to improve the fluid ability performance of the elderly (e.g., Plemons, Willis, & Baltes, 1978; Willis, Blieszner, & Baltes, 1981). These studies have generally shown an improvement in the fluid ability measure after training. While these studies are promising, it is often difficult to assess what led to the performance improvement: new strategies for performing the skill, increased motivation, or a genuine improvement in a more basic underlying ability.
P.47
Working Memory and Attention
Memory and attention are important cognitive resources utilized in learning new skills. These resources also decline with increasing age. With regard to attention, Stankov (1988) performed a factor-analytic study investigating changes in attention over the ages of 20 70. He administered numerous traditional and experimental tests to his subjects, including the WAIS-R, 9 tests believed to tap fluid or crystallized intelligence, and 11 tests of attention. His factor analysis identified three dimensions of attention search, concentration, and attentional flexibility that were different from the dimensions of fluid and crystallized intelligence. All three attentional factors declined with advancing age. Indeed, Stankov (1988) concluded that the decline in attentional flexibility was primarily responsible for the decrease in fluid intelligence over age. When attentional flexibility was held constant, fluid ability was no longer negatively correlated with age.
Working memory, or one's immediate capacity to store and manipulate information, is another aspect of attention that shows a decline with advancing age. Working memory is strongly related to general intelligence (Kyllonen & Christal, 1990) and fluid ability in particular (see Kausler, 1991). The model of working memory accepted by most researchers in cognition is the one put forth by Alan Baddeley (1986, 1990; Baddeley & Hitch, 1974). According to Baddeley, working memory consists of three components: (a) a visuospatial sketchpad for dealing with visual images; (b) an auditory phonological loop for maintaining auditory/verbal information; and (c) a central executive that directs attention for the processing of information and oversees and coordinates the visuospatial and auditory subsystems. According to Baddeley (1986), it is the central executive that is negatively impacted by aging. He noted that forward digit span (primarily indexing the phonological loop) shows relatively little decline (e.g., Craik, 1977), while backward digit span (which involves both the phonological loop and manipulation by the central executive) shows a much greater decline (e.g., Bromley, 1958). Other experiments are consistent in showing that tasks that require either reorganization of the material before output or coordinating attention over different channels (i.e., time-sharing attentional resources) display declining performance with advancing age. As an example of the former, Talland (1965) studied performance on a task that required subjects to listen to sequences of words. Every word in the first half of the presentation was repeated in the second half, except one. Subjects were to output the single word first and then repeat the sequence of words. Older subjects performed this task more poorly than younger subjects did. As an example of the latter, Broadbent and Heron (1962) had subjects cross out certain target digits in a display while simultaneously listening to sequences of 10 letters and responding when a sequence repeated itself. Older subjects were capable of performing the two tasks separately, but their performance declined much more than younger subjects' when the two tasks were performed in tandem (Baddeley, 1986). These results are in agreement with Stankov's (1988) finding of a decline in attentional flexibility in old age.
This possible age-related decline in attentional ability may also be linked to declines in performance flexibility. The elderly seem less able to make use of feedback to modify their performance, which is critical in learning a new skill. Rabbit (1981) has shown that individuals use error feedback in reaction time tasks to modify and
P.48
optimize their performance. Individuals typically speed up until they make an error and then slow down. This process continues until some optimal trade-off between speed and accuracy is achieved. Rabbit (1981) found that while the elderly can respond as quickly as younger subjects, their responses to error are much less finely tuned (Baddeley, 1986). As a group, older adults are more likely to make more errors and have longer reaction times. As Baddeley (1986) pointed out, this finding is consistent with the view that the working-memory central executive is impaired with advancing age. Although it seems able to monitor performance, its ability to intervene to successfully modify performance is reduced. Such an inability to modify performance on the basis of error feedback would have to be accommodated in any cognitive skill-training program.
Explicit Memory
Memory difficulties associated with aging are not limited to working memory. The elderly also exhibit difficulty remembering things over more extended periods of time, and this is particularly problematic when older adults are attempting to learn the content contained within new skill sequences (e.g., remembering the street address to a doctor's office). Indeed, the memory complaints of older adults that are most likely to affect skill acquisition usually center on these kinds of memory problems. In this section, we discuss memory problems within the context of explicit memory (or declarative knowledge; see Anderson, 1983).
Older subjects appear to have problems encoding information for storage in explicit memory (Schaie & Willis, 1991). For instance, the elderly do not spontaneously organize information that is to be recalled later (Craik & Rabinowitz, 1984; Gillund & Perlmutter, 1988), even though such organization is strongly correlated with amount recalled. However, if older subjects are trained in organizational techniques (Hill, Storandt, & Simeone, 1989; Hultsch, 1971; Schmitt, Murphy, & Sanders, 1981) or other kinds of mnemonic strategies (e.g., Hill, Allen, & McWhorter, 1991; Kliegl, Smith, & Baltes, 1989; Robertson-Tchabo, Hausman, & Arenberg, 1976; Stigsdotter Neely & B ckman, 1989, 1993a, 1993b, 1995; Yesavage, Lapp, & Sheikh, 1989, see also the chapters by Hill & Backman, as well as Stigsdotter Neely and Verhaeghen in this text), they seem to improve their recall ability.
Older individuals also have difficulty with retrieval of information from explicit memory. These retrieval difficulties are revealed in comparisons between performances on free recall and recognition memory tests (e.g., Craik, 1986; Craik & McDowd, 1987; Kaszniak, Poon, & Riege, 1986; Poon, 1985) and between performances on free recall and cued memory tests (Craik, 1986; Hultsch, 1985; Poon, 1985). In both cases, the relative advantage of either recognition (in which the items themselves are cues) or cued recall (in which a relevant cue is used to stimulate retrieval) over free (or unsupported) recall is greater for older subjects than for younger subjects (B ckman, M ntyl , & Herlitz, 1990). This finding indicates that older individuals are less likely than younger individuals to generate effective retrieval cues on their own either because they have not adequately encoded the material, or because they are unable or unwilling to generate cues.
One hypothesis advanced to explain the retrieval difficulties experienced by older adults, and particularly the very old, involves the role that the aging process plays in
P.49
limiting the amount of processing resources required to successfully complete the task relative to the amount required by younger subjects (see Backman et al., 1990; Craik, 1977, 1986). According to this hypothesis, the elderly will be disadvantaged at any task that requires a high outlay of cognitive resources or effort (e.g., Craik, 1983; Craik & Byrd, 1982; Hasher & Zacks, 1979, 1984). As an example, free recall requires a higher effort level, during both encoding and retrieval, than recognition and cued recall, which are more heavily supported tasks (Wahlin et al., 1993; Wahlin, B ckman, & Winblad, 1995). Some evidence has been found for this hypothesis in dual-task studies where subjects engaged in both recognition and recall while performing a secondary task such as choice reaction time (e.g., Craik & McDowd, 1987; Macht & Buschke, 1983). Reaction times are slower for both older and younger subjects during recall than during recognition, but the relative effect is much greater for older subjects, a finding indicating a greater mental cost for free recall of declarative information for older subjects (see Kausler, 1991; Salthouse, 1991a).
Speed of Information Processing
Salthouse (1985, 1991a, 1991b, 1993, 1996) has proposed that many of the decrements in cognitive ability associated with aging are the result of a reduction in the speed of performing basic information processes such as comparing two items or incrementing position in a serial list. Through detailed structural equation analyses of ability test data, Salthouse (1993, 1996) has demonstrated that the negative relationship between age and fluid ability, and between age and explicit memory, is attenuated when speed of performing elementary information processes is held constant. Furthermore, he has demonstrated that the controlling variable is not simply motor speed, but speed of performing elementary cognitive operations.
The reduction in the speed of performing elementary cognitive operations with increasing age is also related to working memory ability. Salthouse (1991a) found that age was strongly predictive of processing speed, and that processing speed was predictive of working memory, but that age was only mildly to moderately predictive of working memory. In our opinion, it is difficult to conclusively disentangle the effects of processing speed, working memory, and attentional flexibility. It may be that a reduction in processing speed increases demands upon working memory to keep information available for ongoing processes, thus stressing working memory. Or it may be that declines in the working memory executive make it difficult to execute sets of basic information processes quickly and efficiently. A third possibility is that a reduction in attentional flexibility both impairs the working memory executive and reduces the ability to move among basic information processes, the result being an effective reduction in their average speed of execution. In any case, a reduction in the speed of basic information processes, for whatever reason, needs to be taken into account in designing skills-training programs for the elderly, especially when one is setting the pace at which skills are initially learned by older adults.
Summary
The normal course of aging includes declines in many cognitive abilities. Such declines must be taken into account by any cognitive skill acquisition program aimed at this population. The following general points should be kept in mind:
P.50
There appears to be a decline in fluid ability, which is necessary for new learning. There is, however, some debate about the size of this decline after controlling for confounding factors such as cohort effects. The locus of the decline may be a reduction in attentional flexibility.
There is a decline in at least three aspects of attention: search, concentration, and attentional flexibility. The decline in attentional flexibility may be particularly problematic, as the acquisition of new skills often involves attending to many aspects of the new task until performance automaticity is achieved.
There is a decline in working-memory ability that appears to be localized in the central executive. This may in fact be describing the attentional flexibility problem in different terms. Since the central executive is associated with active manipulation of information in working memory, as well as with time-sharing of attentional resources, impairment of this function will limit the capacity of older adults to learn a skill at any single point in time.
With regard to explicit memory, there is a decline in the extent to which to-be-remembered material is encoded during study time, and there is a corresponding decline in the extent to which effective retrieval cues are self-generated. However, when the older learner is induced to encode effectively and/or is provided support in the form of cues at study or test (see B ckman et al., 1990), recall should improve.
There is a reduction in the speed of performing basic information processes. This is tied to the decline in working memory and attentional flexibility (the direction of causality is not completely certain) and impacts fluid ability, which can be critical in the initial acquisition of declarative information contained in a given skill.
Strategies for Skill Training in Older Populations Derived From Traditional Approaches
In this section, we will explore several recommendations for the development of skill-training programs for older populations. These recommendations are drawn broadly from the traditional literature in skill acquisition and task analysis. We begin by considering the interaction between diversity and complexity of training environment, on the one hand, and the learner's amount of available cognitive resources (described in the previous section), on the other.
The Paradox of Skill Training
When training a new skill, the number and variety of procedures and situations used during training plays an important role in the subsequent level and quality of the skill performance. If small numbers of procedures and situations are used during training, skill acquisition will be fast and relatively error-free. Furthermore, training will engender relatively low levels of frustration in the learner. While these would seem to be desirable attributes of any training program, the ultimate level of skill acquisition will be relatively circumscribed, leading to good performance in situations that were similar to training, but with relatively little generalization to different situations. In addition, focused training is likely to lead to relatively high levels of transfer errors, that is, mistakes made in situations where we would hope to find generalization (see Salomon & Perkins, 1989). Oddly enough, many skill-training programs that are designed in just this way often produce disappointing results inasmuch as the learner is unable
P.51
to use his or her new skills to deal with a variety of issues in everyday living (e.g., skill training for using a computer does not generalize to accessing one's account through an ATM machine).
The alternative to a limited training program would be training involving a large number of procedures and situations. Such a program leads to slower acquisition of the trained skill and higher error rates during training, but it results in far greater generalization and fewer transfer errors (e.g., learning the fundamentals of organizing one's day by prioritizing the most important tasks). What are the problems in such programs? They take longer for the learner to complete, and they tend to lead to higher levels of frustration on the part of the learner. They also sometimes require prerequisite levels of cognitive skill on the part of the learner. If the program is too difficult (i.e., requires more cognitive skills than the learner has), the learner may never complete the program.
The last point suggests that the complexity of the skill-training program is not a variable that can be considered in isolation. It interacts with the level of cognitive resources of the learner. An ideal skill-learning program matches the complexity of the training to the cognitive level of the learner; that is, it is adaptive. With a high level of cognitive resources available, it is possible to increase the complexity of the training environment, and therefore to increase generalizability and reduce transfer errors. With a low level of cognitive resources available, we may need to reduce the level of complexity of the training environment, at least during early acquisition. Later, after early skills have been mastered, greater complexity may be introduced without overloading the learner's cognitive resources. Such an individualized training strategy would require a thorough task analysis of the skill to be learned. We provide an example of this kind of training below.
In sum, the paradox of skill training is this: Those training environments that tend to maximize acquisition tend to minimize generalization. In general, we want to begin at the highest level of complexity possible, while not overloading the learner's cognitive system, and while not producing unacceptably high levels of frustration. Two things help achieve this goal: (a) a detailed evaluation of the cognitive resources of the learner (e.g., neuropsychological tests, traditional psychometric instruments, and possibly laboratory-based measures of relevant cognitive capabilities) and (b) a flexible training system that can be adjusted to the cognitive resource level of the learner.
Task Analysis
The traditional approach to providing flexibility in the training environment is known as task analysis. Task-analytic approaches have been proposed from both behavioral (e.g., Briggs, 1968, 1970; Gagne, 1962, 1967, 1970a, 1970b; Gagne & Briggs, 1979) and cognitive (e.g., Gardner, 1985; M. D. Merrill, 1973; P. F. Merrill, 1978, 1980) theoretical perspectives. The essence of task analysis is to analyze the to-be-trained skill into its underlying prerequisite skills, knowledge components, and/or behaviors. These underlying components may either be trained directly or be further analyzed into a hierarchy of prerequisites. Eventually the trainer understands what pieces are required to perform the skill and can determine which pieces the learner already has and which pieces need to be taught. Training is then aimed at two goals: (a) imparting
P.52
missing component skills, knowledge, and/or behaviors and (b) blending the components into a fluid performance of the high-level skill.
The latter point needs to be stressed. It is quite possible to possess all the component skills and still be unable to combine them into the higher level skill (see Anderson, 1983). For instance, in tennis one may know how to toss a ball and swing a racket for serve but may be unable to produce an acceptable serve due to the inability to perform the toss and swing in synchrony and with the correct timing. Often a good deal of training is devoted to putting the parts together into an acceptable whole.
There has been a debate in psychology over what has been termed part/whole learning (Carlson, Khoo, & Elliot, 1990; Schneider & Detweiler, 1988). Under what circumstances is it better to teach a skill as a whole rather than to teach the skill via the teaching of its component parts? In general, it is better to teach a skill as a whole because the problem of how to blend components is avoided (the blending is implicit in the instruction of the whole skill; see Lintern, & Gopher, 1980). However, there are circumstances that would favor the part skill approach (see Ash, & Holding, 1990; Carlson, Sullivan, & Schneider, 1989). If the learner has an insufficient repertoire of underlying component skills to allow direct training of the whole skill, part skill training would be preferable. Also, if the skill being taught is infrequent in the context of some larger training program, direct instruction in the infrequent skill would be likely to produce competence in the skill, given the small number of chances for practice within the larger training program. Finally, if the cognitive resources of the learner are too few for her or him to learn the skill as a whole, part skill training might be the only feasible route to skill acquisition. The first and last of these situations are applicable to older learners.
Concrete Suggestions
In this section, we will make some concrete suggestions based on the traditional (primarily decomposition) approaches to skill learning. These suggestions should foster more effective skill-learning programs for the elderly. To illustrate the suggestions, we will apply them to a hypothetical problem: teaching older individuals how to utilize a city bus system. We should point out that we have not actually developed such a training program; we merely wish to show how the suggestions could be applied.
To facilitate skill acquisition, early instructions in the skill-training program should be kept to a minimum. For instance, when older people are beginning to be taught to use a bus system, they might be taken on a bus ride rather than be given verbal instructions on the necessary steps. During the early phases of skill training, individuals are attempting to take declarative knowledge (i.e., rules about how to perform the skill) and apply it to problems at hand. It is this process of repeated application of the declarative rules that builds procedural knowledge of the skills themselves. But the declarative knowledge takes up working memory and attentional resources that may already be in short supply in the elderly. Minimizing instructions will help to free up these cognitive resources for use in building the skill. Later in training, instructions may have to be lengthened, especially as the training program encounters more complex situations needed to establish generalization, but by this time, the procedural skill
P.53
should be well established, and more working memory and attention should be available for dealing with the heavier verbal instruction load. For example, after older individuals have mastered the basics of bus riding, the process of obtaining and utilizing bus transfers might have to be explained.
Feedback is an important component of our skill acquisition example. To acquire a skill correctly, the learner must know when he or she has succeed and/or failed. Early sessions of training should include high levels of performance feedback. This is beneficial to all learners, but especially to the elderly, who may not modify their behavior as readily to comply with performance feedback (see the findings of Rabbit, 1981, discussed above). As training continues, feedback must eventually be reduced, and finally eliminated, because most skills require performance in an environment that does not provide direct feedback. High levels of feedback early ensure efficient skill acquisition; low levels of feedback later ensure skill transfer to the environment. With regard to our bus-riding example, early bus rides might be with a trainer who follows a checklist (e.g., Does the person know the intended destination? Does the person know when the next bus is scheduled to arrive? Does the person have the exact fare? ), while later rides might require only spot checks prior to departure.
Variability needs to be programmed into skill learning. Without this variability, the skill acquired may be overly specific and may not generalize to new environments and tasks. Early in training, variability should be relatively limited. For instance, training conditions might be blocked within sessions, with each session representing a unique skill or subskill. Keeping variability limited early in the training minimizes the strain on cognitive resources and thus allows these resources to be available for acquiring the skill. When people are learning to ride the bus system, early rides might all be on one particular route. Later in training, variability should be systematically increased. For instance, training conditions might be mixed so that each new trial or problem requires a different skill or subskill. This variability will increase the likelihood of transfer and generalization from the conditions of training to the real world. Later in the process of learning to ride the bus system, bus rides would probably encompass several connecting bus routes.
Variability in the scheduling of training sessions is also important for facilitating maintenance of the to-be-learned skill. In general, it's been found that distributed practice produces superior recall over massed practice (Bahrick & Phelps, 1987; Ebbinghaus, 1885; Glenberg, 1977, 1979; Leicht & Overton, 1987). It is for this reason that students who cram for an exam typically have poor memory for the material after the course is over. The superiority of distributed practice seems to be linked to multiple opportunities to encode new material in slightly different contexts. Each of these contexts provides an additional retrieval cue that may be useful in retrieving the material. To maximize retention, one wants to have relatively short practice sessions spaced with intervening rest periods. This may be especially important for the older learner because, as we noted earlier in the chapter, aging is associated with reduced information-processing resources. While these findings are based primarily on memory for verbal declarative material, we believe they apply equally to the early stages of skill learning that involve translating declarative knowledge into procedural skills. For example, when older people are trained to ride the bus, training sessions should be limited to 30 minutes but could be scheduled during different days of the week
P.54
and different times of day. These differences in day and time should provide additional retrieval cues to stimulate appropriate processes to maximize retrieval of necessary information.
Several other things can be done to improve skill maintenance. First, any skill taught must be used regularly if it is to be maintained. The old adage Practice makes perfect is close to the mark. Practice makes for better fluid skill performance and facilitates skill maintenance. In our bus-riding example, elderly trainees should be encouraged (health permitting) to take one bus ride a week. Skills that do not have high baseline usage in the real world may require booster sessions of training. These would involve bringing individuals back at prespecified intervals (such as 6 and 12 months) for additional training on the skill. An example of such a skill might be financial planning: It might be used only once or twice a year, but doing it correctly is crucial; therefore booster sessions might be necessary. Thus, encouraging our older learners to make bus travel a regular part of their daily routine would be important to preserving their newly acquired skills.
To maintain a skill after training, prompts for the skill should be gradually faded into the environment. At first, the skill might have to be prompted explicitly by instruction to use it. Eventually, the prompt for the skill should be the situation in real life that calls for the skill. The process of fading must be gradual, however, with instruction about when to use the skill. Hopefully, the skill will be instrumentally conditioned through the reinforcement inherent in being able to accomplish tasks successfully. With regard to bus riding, the environment of the bus stop should eventually lead the elderly individual to mentally go through the checklist of bus-riding steps that were previously explicitly covered by the trainer. If riding the bus leads to the accomplishment of important personal goals, we would expect that the bus-riding environment would come to cue bus-riding skills in memory.
Finally, using external memory aids to prompt usage of the skill can enhance maintenance. The individual can be given something as simple as a sheet of paper with the steps of the skill written on it. Given the encoding and retrieval difficulties of the elderly, external memory aids form a viable adjunct to direct skill training. Without skill training, the steps could not be performed fluidly and competently, but, the cheat sheet can serve to initiate skill usage. We would point out that even the most seasoned bus rider, young or old, keeps a bus schedule in case he or she needs to catch a bus at an unusual time.
Several things can also be done to improve skill generalization and transfer. First, it is important to teach individuals where and when the skill will (and won't) be useful. This is essentially teaching the parameters of acceptable skill application. Without direct instruction in generalization, the trainer leaves the issue up to induction on the part of the learner. This is a poor practice for all but the most able of learners. In teaching an older person how to ride the bus, we would probably point out which steps would transfer to riding a subway train, and which wouldn't (e.g., how fares are paid might be through exact change on the bus, but by fare card on a train).
Of course, generalization should be built into the skill training itself. The training should encompass many different types of problems and contexts of skill usage. The greater the universe of problem types and contexts encountered in training, the greater the degree of generalizability built into the skill. In bus riding, for example, we would
P.55
want individuals to practice catching the bus at many locations, including bus stations, in addition to bus stops.
Table 3.1 A Skill-Training Framework for Learning How to Travel by Bus | ||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Just as booster sessions encourage maintenance, periodic review of the individual's current skill needs can encourage transfer. A yearly meeting with each of the elderly residents of a retirement home might point out different problems for different people. The meeting would be an opportunity for reminding individuals which of their current skills might be applicable to their current problems, as well as pointing out new areas that require new training. In the case of riding the bus, just where does the individual want or need to go? Is there a bus route to the desired destination? Or is there some alternative means of transportation for reaching that destination (e.g., taxi)? The use of external memory aids is also relevant to generalization. A list of a bag of tricks that one can make periodic reference to makes it easier to decide which trick to apply to which problem situation.
Summary
Table 3.1 outlines the strategies we have previously described, above and we have linked them to specific bus-usage training examples. What is highlighted in this table is the overarching concept that when providing skill-based training it is useful to think of three fundamental domains: acquisition, maintenance, and generalizability. As we noted in the beginning of this chapter, it is important to keep in mind that older adults may have some unique attributes by virtue of the aging process that should be considered when applying a skills-training approach to their everyday problems. However, we believe that utilizing principles from the skill-training literature may represent the kind of approach to training that will lead to the most usable, durable, and transferable kinds of learning for the older adult in our contemporary society.
P.56
References
Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.
Ash, D. W., & Holding, D. H. (1990). Backward versus forward chaining in the acquisition of a keyboard skill. Human Factors, 32, 139 146.
Atchley, R. (1980). The social forces in later life: An introduction to social gerontology (3rd Ed.) Belmont, CA: Wadsworth.
B ckman, L., & Nilsson, L.-G. (1996). Semantic memory functioning across the adult life span. European Psychologist, 1, 27 33.
B ckman, L., M ntyl , T., & Herlitz, A. (1990). The optimization of episodic remembering in old age. In P. B. Baltes & M. M. Baltes (Eds.). Successful aging: Perspectives from the behavioral sciences (pp. 118 163). New York: Cambridge University Press.
Baddeley, A. D. (1986). Working memory. Oxford: Oxford University Press.
Baddeley, A. D. (1990). Human memory: Theory and practice. Boston: Allyn & Bacon.
Baddeley, A. D., & Hitch, G. (1974). Working memory. In G. A. Bower (Ed.), Recent advances in learning and motivation (Vol. VIII, pp. 47 90). New York: Academic Press.
Bahrick, H. P., & Phelps, E. (1987). Retention of Spanish vocabulary over eight years. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13, 344 349.
Briggs, L. J. (1968). Sequencing of instruction in relation to hierarchies of competence. AIR Monograph, No. 3.
Briggs, L. J. (1970). Handbook of procedures for the design of instruction. AIR Monograph, No. 4.
Broadbent, D. E., & Heron, A. (1962). Effects of a subsidiary task on performance involving intermediate memory in younger and older men. British Journal of Psychology, 53, 189 198.
Bromley, D. B. (1958). Some effects of age on short-term learning and memory. Journal of Gerontology, 13, 398 406.
Carlson, R. A., Khoo, H., & Elliot, R. G. (1990). Component practice and exposure to a problem-solving context. Human Factors, 32, 267 286.
Carlson, R. A., Sullivan, M. A., & Schneider, W. (1989). Component fluency in a problem-solving context. Human Factors, 31, 489 502.
Cattell, R. B. (1963). Theory of fluid and crystallized intelligence: An initial experiment. Journal of Educational Psychology, 54, 105 111.
Cattell, R. B. (1971). Abilities: Their structure, growth, and action. Boston: Houghton Mifflin.
Craik, F. I. M. (1977). Age differences in human memory. In J. E. Birren & K. W. Schaie (Eds.), Handbook of the psychology of aging. New York: Van Nostrand Reinhold.
Craik, F. I. M. (1983). On the transfer of information from temporary to permanent memory. Philosophical Transactions of the Royal Society, London, Series B, 302, 341 359.
Craik, F. I. M. (1986). A functional account of age differences in memory. In F. Klix & H. Hagendorf (Eds.), Human memory and cognitive capabilities. Amsterdam: Van Nostrand Reinhold.
Craik, F. I. M., & Byrd, M. (1982). Aging and cognitive deficits: The role of attentional processes. In F. I. M. Craik & S. Trehub (Eds.), Aging and cognitive processes (pp. 191 211). New York: Plenum Press.
Craik, F. I. M., & McDowd, J. M. (1987). Age differences in recall and recognition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13, 474 479.
Craik, F. I. M., & Rabinowitz, J. C. (1984). Age differences in the acquisition and use of verbal information. In J. Long and A. Baddeley (Eds.), Attention and performance X. Hillsdale, NJ: Erlbaum.
P.57
Doppelt, J. E., & Wallace, W. L. (1955). Standardization of the Wechsler Adult Intelligence Scale for older persons. Journal of Abnormal and Social Psychology, 51, 312 330.
Ebbinghaus, H. (1885). Uber das Ged chtnis. Leipzig, Germany: Duncker & Humblot.
Fancher, C. (1996, August). Smart Cards. Scientific American, pp. 30 35.
Fitts, P. M., & Posner, M. I. (1967). Human performance. Belmont, CA: Brooks/Cole.
Gagne, R. M. (1962). The acquisition of knowledge. Psychological Review, 69, 355 365.
Gagne, R. M. (Ed.). (1967). Learning and individual differences. A symposium of the Learning Research and Development Center, University of Pittsburgh, Columbus, OH: Charles E. Merrill.
Gagne, R. M. (1970a). The conditions of learning. New York: Holt, Rinehart, & Winston.
Gagne, R. M. (1970b). Some new views of learning and instruction. Phi Delta Kappan, 51, 468 472.
Gagne, R. M., & Briggs, L. J. (1979). Principles of instructional design (2nd ed.). New York: Holt, Rinehart, & Winston.
Gardner, M. K. (1985). Cognitive psychological approaches to instructional task analysis. In E. W. Gordon (Ed.), Review of research in education (Vol. 12, pp. 157 195). Washington, DC: American Educational Research Association.
Gardner, M. K., & Clark, E. (1992). The psychometric perspective on intellectual development in childhood and adolescence. In R. J. Sternberg & C. A. Berg (Eds.), Intellectual development (pp. 16 43). Cambridge: Cambridge University Press.
Gauthier, P. (1996, May). Get Set! Smartcards are coming to America. Portable Design, 1, 31 34, May.
Giambra, L. M., Arenberg, D., Zonderman, A. B., Kawas, C, & Costa, P. T. (1995). Adult life span changes in immediate visual memory and verbal intelligence. Psychology and Aging, 10, 123 139.
Gilinsky, A. S., & Judd, B. B. (1994). Working memory and bias in reasoning across the adult lie span. Psychology and Aging, 9, 356 371.
Gillund, G., & Perlmutter, M. (1988). Episodic memory and knowledge interactions across adulthood. In L. L. Light & D. M. Burke (Eds.), Language, memory and aging. Cambridge: Cambridge University Press.
Glenberg, A. M. (1977). Influences of retrieval processes on the spacing effect in free recall. Journal of Experimental Psychology: Human Learning & Memory, 3, 282 294.
Glenberg, A. M. (1979). Component-levels theory of the effects of spacing of repetitions on recall and recognition. Memory & Cognition, 7, 95 112.
Hasher, L., & Zacks, R. T. (1979). Automatic and effortful processes in memory. Journal of Experimental Psychology: General, 120, 301 309.
Hasher, L., & Zacks, R. T. (1984). Automaticity processing of fundamental information: The case of frequency of occurrence. American Psychologist, 39, 1372 1388.
Hill, R. D., Allen, C, & McWhorter, P. (1991). Stories as a mnemonic aid for older learners. Psychology and Aging, 6, 484 486.
Hill, R. D., Storandt, M., & Simeone, C. (1989). The effects of memory skills training and incentives on free recall in older learners. Journal of Gerontology: Psychological Sciences, 45, 227 242.
Horn, J. L. (1970). Organization of data on life-span development of human abilities. In L. R. Goulet & P. B. Baltes (Eds.), Life-span developmental psychology: Research and theory (pp. 423 466). New York: Academic Press.
Horn, J. L. (1982). The aging of human abilities. In B. B. Wolman (Ed.), Handbook of developmental psychology (pp. 267 300). New York: Wiley.
Horn, J. L., & Cattell, R. B. (1966). Refinement and test of the theory of fluid and crystallized general intelligences. Journal of Educational Psychology, 51, 253 270.
P.58
Hultsch, D. (1971). Adult age differences in tree classification and tree recall. Developmental Psychology, 4, 338 342.
Hultsch, D. (1985). Adult memory: What are the limits? In E. M. Gee & G. M. Gutman (Eds.), Canadian gerontological collection V (pp. 20 52). Winnipeg: Canadian Association on Gerontology.
Hultsch, D. F., Hertzog, C, Small, B. J., McDonald-Miszczak, L., & Dixon, R. A. (1992). Short-term longitudinal change in cognitive performance in later life. Psychology and Aging, 7, 571 584.
Kaszniak, A. W., Poon, L. W., & Riege, W. (1986). Assessing memory deficits: An information-processing approach. In L. W. Poon (Ed.), Handbook for clinical memory assessment of older adults (pp. 168 188). Washington, DC: American Psychological Association.
Kausler, D. H. (1991). Experimental psychology, cognition, and human aging (2nd ed.). New York: Springer-Verlag.
Kliegl, R., Smith, J., & Baltes, P. B. (1989). Testing the limits and the study of adult age differences in cognitive plasticity of a mnemonic skill. Developmental Psychology, 25, 247 256.
Kyllonen, P. C, & Christal, R. E. (1990). Reasoning ability is (little more than) working-memory capacity?! Intelligence, 14, 389 433.
LaRue, A. (1992). Aging and neuropsychological assessment. New York: Plenum Press.
Leicht, K. L., & Overton, R. (1987). Encoding variability and spacing repetitions. American Journal of Psychology, 100, 61 68.
Lindenberger, U., & Baltes, P. B. (1997). Intellectual functioning in old and very old age: Cross-sectional results from the Berlin Aging Study. Psychology and Aging, 12, 410 432.
Lintern, G., & Gopher, D. (1980). Adaptive training of perceptual-motor skills: Issues, results, and future directions. International Journal of Man-Machine studies, 10, 521 551.
Macht, M. L., & Buschke, H. (1983). Age differences in cognitive effort in recall. Journal of Gerontology, 38, 695 700.
Merrill, M. D. (1973). Content and instructional analysis for cognitive transfer tasks. A. V. Communications Review, 21, 109 125.
Merrill, P. F. (1978). Hierarchical and information processing task analysis: A comparison. Journal of Instructional Design, 1, 35 40.
Merrill, P. F. (1980). Analysis of a procedural task. NSPI Journal, 19, 11 15.
Michio, K. (1997). Visions: How science will revolutionize the 21st century. New York: Anchor Books.
Nilsson, L.-G., B ckman, L., Erngrund, K., Nyberg, L., Adolfsson, R., Bucht, G., Karlsson, S., Widing, M., & Winblad, B. (1997). The Betula prospective cohort study: Memory, health, and aging. Aging, Neuropsychology, and Cognition, 4, 1 32.
Park, D. C, Willis, S. L., Morrow, D., Diehl, M. et al. (1994). Cognitive function and medication usage in older adults. Journal of Applied Gerontology, 13, 39 57.
Pickover, C. A. (1992). Visions of the future: Art, technology, and computing in the twenty-first century. New York: St. Martin's Press.
Plemons, J. K., Willis, S. L., & Baltes, P. B. (1978). Modifiability of fluid intelligence in aging: A short-term longitudinal training approach. Journal of Gerontology, 33, 224 231.
Poon, L. W. (1985). Differences in human memory with aging: Nature, causes, and clinical implications. In J. E. Birren & K. W. Schaie (Eds.), Handbook of the psychology of aging (2nd ed.). New York: Van Nostrand Reinhold.
Rabbit, P. (1981). Cognitive psychology needs models for changes in performance with old age. In J. B. Long & A. D. Baddeley (Eds.), Attention and performance X. Hillsdale, NJ: Erlbaum.
Robertson-Tchabo, E. A., Hausman, C. P., & Arenberg, D. A. (1976). A classic mnemonic for old learners: A trick that works. Educational Gerontology, 1, 215 226.
P.59
Salomon, G., & Perkins, D. N. (1989). Rocky roads to transfer: Rethinking mechanisms of a neglected phenomenon. Educational Psychologist, 24, 113 142.
Salthouse, T. A. (1985). A theory of cognitive aging. Amsterdam: North-Holland.
Salthouse, T. A. (1991a). Mediation of adult age differences in cognition by reductions in working memory and speed of processing. Psychological Science, 2, 179 183.
Salthouse, T. A. (1991b). A theory of cognitive aging. Amsterdam: Elsevier.
Salthouse, T. A. (1993). Speed mediation of adult age differences in cognition. Developmental Psychology, 29, 722 738.
Salthouse, T. A. (1996). The processing-speed theory of adult age differences in cognition. Psychological Review, 103, 403 428.
Schaie, K. W. (1979). The primary mental abilities in adulthood: An exploration in the development of psychometric intelligence. In P. B. Baltes & O. G. Brim, Jr. (Eds.), Life-span development and behavior (Vol. 2). New York: Academic Press.
Schaie, K. W. (Ed.). (1983a). Longitudinal studies of adult psychological development. New York: Guilford Press.
Schaie, K. W. (1983b). The Seattle Longitudinal Study: A twenty-one year exploration of psychometric intelligence in adulthood. In K. W. Schaie (Ed.), Longitudinal studies of adult psychological development. New York: Guilford Press.
Schaie, K. W. (1990). Intellectual development in adulthood. In J. E. Birren & K. W. Schaie (Eds.), Handbook of the psychology of aging (3rd ed., pp. 291 309). New York: Academic Press.
Schaie, K. W., & Hertzog, C. (1986). Toward a comprehensive model of adult intellectual development: Contributions of the Seattle Longitudinal Study. In R. J. Sternberg (Ed.), Advances in human intelligence (Vol. 3, pp. 79 118). Hillsdale, NJ: Erlbaum.
Schaie, K. W., & Strother, C. R. (1968). A cross-sectional study of age changes in cognitive behavior. Psychological Bulletin, 70, 671 680.
Schaie, K. W., & Willis, S. L. (1991). Adult development and aging (3rd ed.). New York: HarperCollins.
Schmitt, F. A., Murphy, M. D., & Sanders, R. E. (1981). Training older adult free recall rehearsal strategies. Journal of Gerontology, 36, 329 337.
Schneider, W., & Detweiler, M. (1988). The role of practice in dual-task performance: Toward workload modeling in a connectionist/control architecture. Human Factors, 30, 539 566.
Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: 1. Detection, search, and attention. Psychological Review, 84, 1 66.
Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: 2. Perceptual learning, automatic attending, and a general theory. Psychological Review, 84, 127 190.
Squire, L. R. (1987). Memory and brain. Oxford: Oxford University Press.
Stankov, L. (1988). Aging, attention, and intelligence. Psychology and Aging, 3, 59 74.
Sternberg, R. J., & Powell, J. S. (1983). The development of intelligence. In J. H. Flavell & E. M. Markman (Vol. Eds.), Handbook of child psychology: Vol. HI. Cognitive development (4th ed., pp. 341 419). New York: Wiley.
Stigsdotter Neely, A., & B ckman, L. (1989). Multifactorial memory training with older adults: How to foster maintenance of improved performance. Gerontology, 35, 260 267.
Stigsdotter Neely, A., & B ckman, L. (1993a). Long-term maintenance of gains from memory training in older adults: Two 3 1/2 years follow-up studies. Journals of Gerontology: Psychological Sciences, 48, 233 237
Stigsdotter Neely, A., & B ckman, L. (1993b). Maintenance of gains following multifactorial and unifactorial memory training in late adulthood. Educational Gerontology, 19, 105 117.
P.60
Stigsdotter Neely, A., & B ckman, L. (1995). Effects of multifactorial memory training in old age: Generalizability across tasks and individuals. Journals of Gerontology: Psychological Sciences, 50B, 209 215.
Storandt, M. (1977). Age, ability level, and method of administering and scoring the WAIS. Journal of Gerontology, 37, 602 603.
Talland, G. (1965). Three estimates of the word span and their stability over the adult years. Quarterly Journal of Experimental Psychology, 17, 301 307.
Wahlin, ., B ckman, L., & Winblad, B. (1995). Free recall and recognition of slowly and rapidly presented words in very old age. A community-based study. Experimental Aging Research, 21, 251 271.
Wahlin, ., B ckman, L., M ntyl , T., Herlitz, A., Viitanen, M., & Winblad, B. (1993). Prior knowledge and face recognition in a community-based sample of healthy, very old adults. Journal of Gerontology: Psychological Sciences, 48, P54-P61.
Wechsler, D. (1944). The measurement of adult intelligence. Baltimore: Williams & Wilkins.
Wechsler, D. (1955). Wechsler Adult Intelligence Scale. New York: Psychological Corporation.
Wechsler, D. (1981). Wechsler Adult Intelligence Scale Revised. New York: Psychological Corporation.
Willis, S. L., Blieszner, R., & Baltes, P. B. (1981). Intellectual training research in aging: Modification of performance on the fluid ability of flgural relations. Journal of Educational Psychology, 73, 41 50
Yesavage, J. A., Lapp, D., & Sheikh, J. A. (1989). Mnemonics as modified for use by the elderly. In L. W. Poon, D. Rubin, & B. Wilson (Eds.), Everyday cognition in adulthood and late life. Cambridge: Cambridge University Press.
EAN: 2147483647
Pages: 18