5 Principles of Cognitive Learning (2023)

Have you ever wondered what exactly is happening when students are staring blankly at the lecture slides or finding it difficult to respond to your on-the-spot questions? There are a variety of reasons students have trouble staying engaged and responsive in a course. Some of these reasons have to do with the architecture of the brain.

These 5 principle​s of cognitive learning are based on a comprehensive list provided in Online Teaching at Its Best by Linda Nilson and Ludwika Goodson (2018, pp. 79-82). All of these principles apply to face-to-face, online, and any type of learning environment.
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Minimize Cognitive Load
Cognitive Load Theory (Sweller, 1988) is the idea that our brains have a certain capacity and demands on this brain capacity impact our learning outcomes. In other words, if you think of a student’s cognitive capacity as a bucket and you fill up the bucket to the brim with ideas and new information, then adding more ideas may put the bucket above the student’s capacity to learn. This is one way we understand why students may miss the mark or not remember information clearly.

Cognitive Load is dynamic in many ways, if anything, because we haven’t figured out quite how the brain works exactly. Yet, what we do know is the mind has a limited capacity to gain, retain, and recall information, which calls for us to package our learning content and lessons into chunks for the most efficient learning possible.

Now, imagine the brain capacity bucket is filled with various different elements. Perhaps in this example we have dry beans, grains of rice, and water. Each of these elements represent different details of different categories of information. Right now, it’s all mixed together as if you were to plan to make a bean and rice soup. The mixture looks rather homogenous with various grains of rice, individual beans, and water to fill in the spaces between the two.

Now, imagine placing separate cups in the bucket. One cup contains beans, another contains rice, and another contains the water. Now, we have organized our ingredients in the bucket according to category. This is how students learn best, by well organized, easy-to-understand packages or chunks of information. They may not have soup at this point, but theycertainly have the ingredients in understandable cups and quantities.

Repetition and Variety of Delivery
The skills and knowledge we learn really well are those we have repeated exposure to within asafe environment. Another element of this is repeated exposure via many different methods of delivery.

We once thought learning styles were central to the way learning worked. We know now learning styles are a bit of a myth (Husmann & O’Loughlin, 2018; Khazan, 2018) and it is more about students learning information and skills through many different means (Nilson & Goodson, 2018).

Courses can be designed to have multiple activities and elements that work together to set students up for success in meeting a learning outcome. For a student named Sally, doing 45 math problems a night with targeted feedback from you in the morning may be very helpful. For another student named Kenneth, he doesn’t learn anything from the 45 math problems but from the video playlist you provide online about the real-world applications of the concepts. In this examples, both students are getting repetition with the material, yet they are learning the information well from different activities.

Now take Sally and Kenneth to a history course. In this course, Kenneth learns best by doing 45 multiple-choice practice problems after reading the textbook chapters where Sally gets more out of the video playlist you created on the same events in history.

In both scenarios, the students are completing the same activities for the course concepts, yet they both get more out of different types of activities between two course topics.​

Qualities to Attract
Ever noticed yourself more attracted to social media posts with images or videos? What about news articles with images or visuals? Human brains are attracted to qualities like human faces, color, intensity, extreme contrasts, movement, change, drama, enthusiasm, and personal relevance (Ambrose, Bridges, DiPietro, Lovett, & Norman, 2010).

In many ways, our students today are even more attracted to the visual, animated, and colorful. This is what they see on a daily basis on their own social media and in advertisements. They’re a group of individuals who have immediate rewards for many of their behaviors.

Tap into this knowledge of what students’ brains are attracted to and integrate visuals, videos, and human faces whenever possible in your course. This can be done face-to-face in lecture slides, videos, and even worksheets or group activities. In the online environment, adding a simple graphic that relates to the page or message is powerful especially if it has qualities that attract: human faces, color, intensity, extreme contrasts, movement, change, drama, enthusiasm, and personal relevance.

Evoke Emotions
​Emotions are a powerful learning tool. By evoking the emotions of our students, we can create a memorable experience they can draw upon to keep learning in the course, study for tests, complete projects, and apply their knowledge from your course in the real world.

Emotions stimulate certain parts of the brain associated with learning. From a biological view, there are synapses firing between the frontal lobe and the limbic system. The frontal lobe is our cognition and thinking. The limbic system is our emotional control center which guides our inherent drive to survive.

By stimulating both the frontal lobe and the limbic system during our students’ learning experiences, we are providing the students with a transformative learning opportunity. Through this, they may experience or understand something on a deeper, more comprehensive level.

For example, learning the timeline of the civil war by rote memorization is a much different experience for students than, say, following a married couple through their hardships of war. By highlighting the married individuals’ emotional experiences during each event of the war, the students may relate to the experience by knowing the feelings of anger, sadness, worry, and anticipation. This example also taps into the human attraction to storytelling. Simulations can work the same way.

Targeted Feedback
Targeted feedback is the course correction and information we give the students specifically related to what they have done, shown, or left out. It is true, students learn from practice, but without the instructor giving them clear performance feedback specific to them, the practice may be for nothing (Ambrose et al, 2010).

Now, there are barriers to giving targeted feedback. Not only does it take time and extra organizational efforts of the instructor, it also takes the students reading or watching the feedback. Targeted feedback is probably one of the biggest hurdles to overcome as an instructor of a course.

In the end, we know targeted feedback is effective. If we adopt the mindset of providing the students with the opportunity to learn based on their performance, than we are providing the individualized education many institutions promise students. Create student buy-in by referring to your feedback in your conversations and subsequent assignment submissions.

References
Ambrose, S. A., Bridges, M. W., DiePietro, M., Lovett, M. C., & Norman, M. K. (2010).How learning works: Seven research-based principles for smart teaching. San Francisco, CA: Jossey-Bass.

Husmann, P. R., O’Loughlin, V. D.(2018). Another nail in the coffin for learning styles? Disparities among undergraduate anatomy students’ study strategies, class performance, and reported VARK learning styles.Anatomical sciences education.

Khazan, O.(2018, Apr 11). The Myth of ‘Learning Styles’.The Atlantic.Retrieved fromhttps://www.theatlantic.com/science/archive/2018/04/the-myth-of-learning-styles/557687.

Nilson, L. B., Goodson, L. A. (2018). Online teaching at its best: Merging instructional dseign with teaching and learning research. San Francisco, CA: Jossey-Bass.

Sweller, J (June 1988). Cognitive load during problem solving: Effects on learning. Cognitive Science. 12 (2): 257–285.doi:10.1207/s15516709cog1202_4.