The challenge point framework, created by Mark A. Guadagnoli and Timothy D. Lee, provides a theoretical basis to conceptualize the effects of various practice conditions in motor learning. This framework relates practice variables to the skill level of the individual, task difficulty, and information theory concepts. The fundamental idea is that “motor tasks represent different challenges for performers of different abilities”. Any task will present the individual with a certain degree of challenge. However, the learning potential from this task difficulty level will differ based on the: Importantly, though increases in task difficulty may increase learning potential, increased task difficulty is also expected to decrease performance. Thus, an optimal challenge point exists when learning is maximized and detriment to performance in practice is minimized.
Importance and applications
Practice has been proposed as the most important factor for the “relatively permanent” improvement in the ability to perform motor skills. With all other variables held constant, skill increases with practice. However, time devoted to practice can be made more efficient by careful consideration of practice conditions. The challenge point framework presents a theoretical perspective to consider the roles of the level of the performer, the complexity of the task and the environment in regulating the learning potential during practice. Adjustment of these components to enhance motor learning can be applied to variety of contexts, including rehabilitation and simulation-based health professions education.
History
The challenge point framework involves concepts generated through various lines of research including information theory, communications theory, and information processing. Specific notions borrowed from prior research important to understanding the theoretical framework include:
Components
It follows from the description of the challenge point framework that:
Information available and task difficulty
Learning is fundamentally a problem-solving process. It has been proposed that with practice, there is reduced information available to the participant because better expectations are formed. However, increasing functional task difficulty results in less certainty about the predicted success of the action plan and the nature of the feedback. At low levels of functional difficulty, the potential available information is low for performers in all skill levels. As functional task difficulty increases, the potential information available increases exponentially for beginners and less rapidly for intermediate and skilled performers. For experts, the potential information available increases only at the highest levels of functional task difficulty.
Task difficulty and skill
Task difficulty has received considerable attention in prior research. Important to the challenge point framework, task difficulty is not explicitly defined. Alternately, two broad categories can encompass these elements:
Nominal task difficulty
* Difficulty due to the characteristics of the task only, reflecting a constant amount of task difficulty ; includes perceptual and motor performance requirements.
Functional task difficulty
* Difficulty due to the person performing the task and the environment.
Performance of a task with low nominal difficulty will be expected to be high in all groups of performers. However, beginner performance will be expected to decline rapidly as nominal difficulty increases, whereas intermediate and skilled performance will decline less rapidly, and expert performance is expected to decline only at the highest nominal difficulty levels. Although the "Expert" skill level is useful to explain this framework, one may argue that experts should have a high level of predicted success for all nominal task difficulties. It is possible that once expertise is attained, these individuals are able to predict the outcome of the ongoing task and modify ongoing processes in order to reach a suitable outcome.
Optimal challenge points
The optimal challenge point represents the degree of functional task difficulty an individual of a specific skill level would need to optimize learning. However, this learning depends on the amount of interpretable information. Therefore, although increases in task difficulty may increase learning potential, only so much is interpretable, and task performance is expected to decrease. Thus, an optimal challenge point exists when learning is maximized and detriment to performance in practice is minimized. With increased practice it is assumed that one's information-processing capabilities will increase. Therefore, the optimal challenge point will change as the individual's ability to use information changes, requiring further changes in functional difficulties in task to facilitate learning.
Practice variables and framework predictions
Contextual interference (CI) and action planning
Predictions from the challenge point framework with respect to CI :
