When it comes to learners that require speed over depth, it is usually the case that this particular type of learning encompasses repetitive tasks that do not require any advanced form of analytical thinking. Instead, it is expected that learners are supposed to perform tasks as illustrated and make slight alterations as need be but at the same time not diverging from the overall framework of task execution that they have been taught. Such a method of learning is normally seen in the manufacturing industry or tasks involving blue collar workers (Al-Dayaa & Megherbi, 2012).
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It is normally the case that learners (ex: blue collar workers) are only expected to do the tasks they have been taught in a quick and expedient manner. Given the high rate of attrition in such industries, it is not surprising that a new batch of workers may be working in the same factory within 6 months time (Al-Dayaa & Megherbi, 2012). As a result, workers are normally required to be “up to speed” regarding the processes they have to manage without heed for any other technicalities in other aspects of the production line. It is based on this example that it can be stated that in speed learning is applicable in situations where analytic thought and problem solving is eschewed in favor of adaptability and the rate in which certain tasks can be internalized quickly and efficiently.
If speed learning is a state where analytic thought and problem solving is eschewed in favor of adaptability then depth learning can be considered its opposite wherein an individual is subject to a method of education where they are meant to understand every aspect of the topic/course that they are being taught (Dunlosky et al., 2013). Learners for depth learning are often composed of university graduates or specialists in particular fields such as engineering and architecture where it is necessary, over a period of several years, to help the learner internalize aspects related to problem solving, analytic thinking and creativity when it comes to a particular subject matter. It is in such situations speed learning is considered less important since learners are expected to be able to not only perform a set task but they are meant to enhance it based on what they have learned (Dunlosky et al., 2013). Whereas speed learning has a distinctly more physical application, depth learning is more mental in its application and, as such, both learning processes are not interchangeable (Dunlosky et al., 2013).
When it comes to speed learning, quick adaptability is its primary concern wherein a learner is expected to be able to immediately internalize what is being taught and apply it within a short amount of time. Such a method of instant learning and application cannot be performed in the case depth learning due to the complicated nature of the subject matter involved and the fact that learners are expect to apply it analytically whereas speed learners do not need to concern themselves with too much analytic thought regarding what they are doing (Furman & Sibthorp, 2013).
On the other hand, it should be noted that depth learning often enables a learner to better understand a process and implement a better and more creative way of accomplishing it as compared to a speed learner whose limited amount of knowledge results in the ability to perform a task but not understand its ramifications or how to perform it independently from the purpose that was taught to them (Furman & Sibthorp, 2013). For example, an electrical engineer would be able to design an electrical system on all manner of cars whereas an ordinary worker would be able to work on only a select few models to install their electrical systems given the differences in design.
Al-Dayaa, H. H., & Megherbi, D. D. (2012). Reinforcement learning technique using agent state occurrence frequency with analysis of knowledge sharing on the agent’s learning process in multiagent environments. Journal Of Supercomputing, 59(1), 526-547
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013).
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Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology. Psychological Science In The Public Interest (Sage Publications Inc.), 14(1), 4-58.
Furman, N., & Sibthorp, J. (2013). Leveraging Experiential Learning Techniques for Transfer. New Directions For Adult & Continuing Education, (137), 17-26.