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Jack Kuhns and Dayna R. Touron

The study of aging and cognitive skill learning is concerned with age-related changes and differences in how we gather, store, and use information and abilities. As life expectancy continues to rise, resulting in greater numbers and proportions of older individuals in the population, understanding the development and retention of skills across the lifespan is increasingly important. Older adults’ task performance in cognitive skill learning is often equal to that of young adults, albeit not as efficient, where older adults often require more time to complete training. Investigations of age differences in fundamental cognitive processes of attention, memory, or executive functioning generally reveal declines in older adults. These are related to a slowing of cognitive processing. Slowing in cognitive processing results in longer time necessary to complete tasks which can interfere with the fidelity of older adults’ cognitive processes in time-limited scenarios. Despite this, older adults maintain comparable rates of learning with young adults, albeit with some reduced efficiency in more complex tasks. The effectiveness of older adults’ learning is also impacted by a lesser tendency to recognize and adopt efficient learning strategies, as well as less flexibility in strategy use relative to younger adults. In learning tasks that involve a transition from using a complex initial strategy to relying on memory retrieval, older adults show a volitional avoidance of memory that is related to lower memory confidence and an impoverished mental model of the task. Declines in learning are not entirely problematic from a functional perspective, however, as older adults can often rely upon their extensive knowledge to compensate for certain deficiencies, particularly in everyday tasks. Indeed, domains where older adults have maintained expertise are somewhat insulated from other age-related declines.


Barbi Law, Phillip Post, and Penny McCullagh

Modeling and imagery are distinct but related psychological skills. However, despite sharing similar cognitive processes, they have traditionally been investigated separately. While modeling has shown similar psychological and physical performance benefits as imagery, it remains an understudied technique within applied sport psychology. Social cognitive and direct perception approaches remain often-used explanations for the effectiveness of modeling on skill acquisition; however, emergent neuropsychological explanations provide evidence to support these earlier theories and a link to the imagery literature. With advances in technology and the development of applied frameworks, there is renewed interest in exploring modeling effects and how they parallel imagery use in applied settings. Specifically, modeling research has expanded beyond controlled laboratory settings to explore the effect of various theoretical models on motor performance and related cognitions within practice and competitive settings. The emergence of affordable video editing technology makes it easy for coaches and athletes to incorporate modeling into practice. The accessibility of video technology has sparked applied research on how various forms of modeling influence motor performance and cognitions, such as confidence and motivation. These applied investigations demonstrate the complementary nature of modeling and imagery in enhancing sport performance and skill acquisition, while highlighting the challenges in separating modeling and imagery effects. Both literatures offer possibilities for new methodological approaches and directions for studying these psychological skills in tandem as well as independently. Thus, there is much that imagery and modeling researchers can learn from each other in sport and other performance settings.