One common mistake I see among online content developers is to build videos that simply roll through content from start to finish. This is a “covering content” vision of teaching that expects students to grasp anything that is pitched to them. The model likens the human mind to a database that can download whatever information it is given without error.
But the human mind is not like a computer. Whereas a computer can record one million Social Security numbers without fail, those numbers are nine digits long because that is the maximum length that people can remember as a string of digits.
Human learning involves a complicated process of moving information from our working memory to our long-term memory (Oakley & Sejnowski 2015). This requires building connections in our long-term memory, which takes time, repetition, interpretation, assignment of significance, and so on. Thus, following a few simple principles drawn from neurology that will vastly improve your online videos.
Shorter is better
Our working memory that we use to perform immediate tasks can only hold up to four discrete items of information. If we try to add another item to that memory, then one of the other items needs to get pushed out. Thus, covering 20 different items in one talk does not leave the audience with any more information than does covering four items.
Faculty are used to covering material for the complete 50-75 minutes of a class, and they often assume that their online videos should be lectures of a similar length. But long video lectures are a waste of time. The students are only going to walk away with four points at most, which might be the ones that they think are most important, not the ones that you think are most important. More likely, they are just going to be four random points that the students picked up while they were paying attention—or before they turned the video off.
One of the reasons why TED Talks are such great educational devices is that they are strictly limited to eighteen and a half minutes. The speaker also focuses on one—and only one—message. Similarly, the best educational videos are broken into short pieces that cover one topic per video.
Integrating videos with questions
We can only move information from our working memory to our long-term memory by reflecting on it. A good way to facilitate this reflection in videos is with periodic questions. Researchers suggest that questions should be used before, during, and after viewing videos (Williams, 2013).
Pre-module framing questions help prepare students for the content by connecting it to something that the student already knows. Student in a statistics class might be told, “Explain what you already know about normal distributions,” or asked, “What is a normal distribution useful for?” This is important because we learn at the periphery of what we already know by connecting new information to old information. We need to set new information within the context of our wider bundle of knowledge to give it meaning, and forcing students to draw up information about what they know about the subject prior to a lesson encourages this process.
Students can also be asked questions during a video. This can be done either by asking the student to pause the video at various junctures to answer a question or by breaking up a module into multiple short videos, each followed by a question that can be as simple as a multiple-choice question about the material. Just drawing up information helps harden it in long-term memory.
Another option is to ask questions that force students to synthesize the information in some way. For instance, students can be required to explain in their own words a concept that was just covered. This helps put the information into context for the students and shows them whether they need to go back and watch the video again. Students can also be asked to anticipate where the video is going by making predictions about what will be covered next. This engages the student in the content and as a result helps move it to long-term memory.
Finally, post-module questions are valuable for drawing up information that was just covered, again helping to move it to long-term memory. These questions can require students to apply the material to a new situation. The act of application requires connection with what the student already knows and demonstrates the importance of the information.
Chunking
An essential component of deep learning is tying together different bits of information into meaningful chunks. All competitors in memory competitions use the exact same strategy. They break random sequences of numbers into chunks and assign each a significance, such as a birthday. Now they can recall the number by drawing up the meaning. Similarly, students need to ascribe a common meaning to different bits of information they are given to retain it.
An instructor can help form these meaning chunks by repeating underlying concepts across a sequence of learning modules. One fundamental principle that guides medical ethics decision-making is the tension between medical paternalism and respect for patient autonomy. Thus, I try to apply this concept to each new example that I cover in the course. This will help students apply the underlying concept to new situations.
Connecting by common principles also allows for repetition over time. If you want to remember 20 words over the course of 20 days, instead of repeating one of the words 20 times each day to learn them in sequence, it is better to repeat each word once a day over 20 days (Dunlosky, 2015). This draws up the words out of long-term memory each day, which reinforces them in that memory. Thus, returning to common concepts over time, rather than simply moving from one concept to the next, helps harden them into memory.
Metaphors
Finally, metaphors are powerful learning devices because they allow for a connection between ideas, and they should be used liberally in any lesson. For example, the mathematician Kalid Azad helped himself understand the relation between imaginary and real numbers by likening imaginary numbers to a second vertical axis on the number line. He then imagined the graph as a clock. This accurately represents how powers of imaginary numbers move them from positive, to imaginary, to negative, to negative imaginary, and back again. That strategy made it easy for him to understand the relationship between imaginary and real numbers. Thus, you should adopt metaphors to illustrate your concepts as you discuss them.
Apply these principles to your videos to greatly improve your students’ learning.
References
Dunlosky, J. “Strengthening the Student Toolbox.” In Learning How to Learn, Coursera, 2015.
Oakley, B. and T. Sejnowski. Learning How to Learn, Coursera, 2015.
Williams, J. J. (2013). “Applying Cognitive Science to Online Learning.” Paper presented at the Data Driven Education Workshop at Conference on Neural Information Processing Systems.
