Inferring task difficulty in motor skill learning situations based on multitasking approaches: A systematic review
Creators: name: Luong, Liem Gia
name: Immink, Maarten
name: Richards, Jesse
name: Fernandes, Glen
Publisher: name: OSF Registries
Year: 2023
Subjects: subject: Sports Sciences
subject: Physical Sciences and Mathematics
subject: Medicine and Health Sciences
subject: Rehabilitation and Therapy
subject: Social and Behavioral Sciences

description: Skill acquisition is prevalent amongst all perceptual and motor skill-based activities. Motor skill practice is crucial in the development of desirable performance outcomes. Subsequently, optimizing a training regime necessary for skill acquisition has been heavily researched over the last few decades. Aspects related to motor skill learning were quickly identified such as training frequency, intensity, types of feedback, contextual interference, etc. They have since been examined to identify the optimal dosage/ modality to elicit optimal performance benefit. A distinct influence over perceptual and motor skill learning is the individual’s level of challenge in practice. The relationship between practice difficulty and motor learning has been highly debated. Particularly in defining challenge, its optimal dosage, and quantifying the level of challenge the learner perceives. Guadagnoli &amp; Lee’s (2004) Challenge Point Framework conceptualizes optimal motor skill learning as challenging the learner to the optimal amount. This is because challenge is described as the amount of available information presented to the learner. Too much challenge causes too great complexity of information which cannot be processed by the learner. Too little difficulty, there is little new information to be learned. This framework works to expose the learner to the right dosage of challenge to achieve optimal skill learning. The distinct trade off in the Challenge Point Framework is negatively altering practice performance for future performance benefits. While the Challenge Point Framework is useful to conceptualize the need for functional task difficulty in practice for future performance benefits (at the cost of practice performance). There is no clear way to assess task difficulty. Notably, Akizuki and Ohashi (2015) have attempted to investigate the attentional demands to quantify challenge by measuring the amylase content in saliva as well as the NASA-TLX questionnaire which encompasses 6 different domains that may contribute to Functional Task Difficulty. Although this method of quantifying challenge shows promising results, it does not offer immediate feedback for the learner since it can only be measured after the skill has been performed. Multi-task has previously been applied in the context of quantifying task difficulty. Adler &amp; Benbunan-Fich (2015) observed a similar effect of practice performance cost when multi-task was mandatory for training which also yielded future performance benefits compared to its easier practice counterparts (those with optional multi-task and sequential task practice). It is thus hypothesised that complex tasks such as multi-tasking stimulates cognitive workload and attention, through which information can be processed because of performance outcomes Adler &amp; Benbunan-Fich (2015). Multi-task is therefore a measurable outcome in which can infer attentional and cognitive workload to quantify task difficulty. Yet Fischer &amp; Plessow (2015) claim that there is more research needed to determine which modality of multi-tasking brings the most benefit to the individual. Fischer &amp; Plessow (2015) argue that the specific modality of multi-task training is subjective to the learner. This concept is closely aligned with Guadagnoli &amp; Lee’s (2004) explanation that nominal task difficulty (in this context, mode of multi-task practice) must be adopted to best align with the learner’s functional task difficulty (time taken to complete task/reaction time). Thus, cognitive/attentional workloads scale and adapt with different levels of difficulty (Fischer &amp; Plessow, 2015). Lohse and Hodges (2022) describe that practice performance and task difficulty can be varied depending on the desired outcome of the individual/practitioner. It is described that the individual can practice with the intention to learn, intention to transfer, or intention to maintain. Each type of desired outcome requires a different level of task difficulty. Since cognitive and attentional workloads scale to the level of difficulty, monitoring psychological refractory period may also infer the type learning benefit the learner will obtain. In other words, by manipulating nominal task difficulty and monitoring functional task difficulty using time-based measures of attentional allocation can be a useful measure of quantifying the individuals perceived challenge in infer that the individual is practice intention.