Deliberate Practice

This blog is a bit different. I’ve been making my primary audience faculty and staff of a college. Now, while I certainly find the principles of deliberate practice helpful in my own personal growth, perhaps this article is best read not by us. It may be best read by our students.

Of course, this is a dodgy distinction. Living in the Center for Academic and Professional Excellence (CAPE) as I do, I happen to know for a fact that plenty of college employees are purposefully learning new things all the time. And, like I said, I too spend nights and weekends learning new techniques, be it attempting to learn Deep machine Learning (that’s a lot of learning in one sentence) or simply trying to adjust my thinking from a data.frame to a data.table mindset.

Nevertheless, to anyone at Victoria College who knows a student, I really hope you’ll encourage them to read this. It’s only 493 words, and it just might give them the inspiration they need to take their performance to the next level.

An activity that is central to learning is deliberate practice. Deliberate practice is designed to improve key aspects of current performance, is challenging, effortful, requires repetition and feedback, and may not be inherently enjoyable or immediately rewarding (Coughlan, 2014).

Deliberate practice is essential to significant, long term improvement for any topic. In particular, the research by Coughlan et al. shows that haphazard practice may improve the difference between pre and post test scores, deliberate practice increases scores not only on pre and post test scores but also on long term retention scores as well.

If mastery of a skill is needed, deliberate practice is needed.

What is deliberate practice? Well, for starters, it is more effortful and less enjoyable than other forms of practice (Coughlan, 2014). Based on the self-report ratings, here is the difference between the shaded deliberate practice groups versus the unshaded groups who practiced normally:

Deliberate practice bar graph of enjoyment, mental effort, and physical effort comparison.
Deliberate practice bar graph of enjoyment, mental effort, and physical effort comparison.

So what is deliberate practice? While the definitions differ slightly, overall:

  1. The learner must be motivated to exert effort to improve their performance.
  2. The learner must customize their task. Namely, build from where the learner has strengths, have a brief period of instruction, and then a lot of practice.
  3. Immediate, informative feedback is essential.
  4. Repeated performance of the same/similar tasks must be done.

Deliberate practice creates experts. Here’s how it works. The learner identifies weak and strong skills they possess. Graph a shows the results for a weaker skill while graph b shows results for a stronger skill. The control group practiced however they wanted. The ‘expert’ group learners engaged in deliberate practice. This deliberate practice focused on their weak skills. Notice how the control group really doesn’t improve much. The learners who use deliberate practice, on the other hand, do.

Pre, Post, and Retention Test Score Comparison
Pre, Post, and Retention Test Score Comparison

Final thought: Deliberate practice isn’t fun, it requires learners focus on their weaknesses. It also must be self-motivated; no one can do it for you.

Coughlan, E. K. (2014). How Experts Practice: A Novel Test of Deliberate Practice Theory. Journal Of Experimental Psychology: Learning, Memory, And Cognition, 40(2), 449-458.

Fuchs, L. S. (2010). The Effects of Strategic Counting Instruction, with and without Deliberate Practice, on Number Combination Skill among Students with Mathematics Difficulties. Learning And Individual Differences, 20(2), 89-100.

Plant, E. A., Ericsson, K. A., Hill, L., & Asberg, K. (2005). Why Study Time Does Not Predict Grade Point Average across College Students: Implications of Deliberate Practice for Academic Performance. Contemporary Educational Psychology, 30(1):96-116.



Matt Wiley is a tenured, associate professor of mathematics with awards in both mathematics education and honour student engagement. He earned an assortment of degrees in computer science, business, and pure mathematics from the University of California and Texas A&M systems. He is the director of quality enhancement at Victoria College, assisting in the development and implementation of a comprehensive assessment program to enhance institutional performance outcomes. A programmer, a published author, a mathematician, and a transformational leader, Matt has always melded his passion for writing with his joy of logical problem solving and data science. From the boardroom to the classroom, he enjoys finding dynamic ways to partner with interdisciplinary and diverse teams to make complex ideas and projects understandable and solvable.

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