Charles Ungerleider, Professor Emeritus, The University of British Columbia
[permission to reproduce granted if authorship is acknowledged]
When confronted by uncertainty, my mother used to say, “it’s crazy making.” She was not unusually anxious. In fact, she was among the most placid people I have known. Nonetheless, she knew that uncertainty caused stress.
Most of us manage the stress that uncertainty engenders by seeking information. I consult the weather forecast to reduce uncertainty about whether it will rain tomorrow or the next day. I reduce my uncertainty about my retirement income by use information about company performance, economic indicators, and market trends to make investment decisions.
When my physician diagnosed a medical condition a couple of years ago, I asked her how she arrived at her diagnosis. She said that she had considered my medical history, symptoms, and the results of the diagnostic tests she had ordered to reduce her uncertainty and that, in turn, reduced my anxiety.
Education is a complex process influenced by many factors that create uncertainty. The diversity of learner characteristics, complexity of subject matter, classroom dynamics, and socio-cultural and other influences (COVID-19, for example) make the outcomes of decision-making uncertain. I often wonder why people do not make use of the information at our disposal to reduce uncertainty.
The idea that information reduces uncertainty can be traced to the foundations of information theory and the work of Claude Shannon, a mathematician and electrical engineer. Shannon introduced the concept of "entropy" as a measure of uncertainty, surprise, or information content. He used this concept to quantify the amount of uncertainty that could be reduced by a piece of information. In other words, the more information you have, the less uncertain you are.
While originally intended for communication and signal processing, Shannon’s foundational concepts can be applied to decision-making in education. As stated above, the more information you have about something, the less uncertainty there is about it. In education, this implies using information about students such as their learning progress, classroom dynamics, etc., to reduce the uncertainty about making decisions about teaching strategies, individual student interventions, curriculum adjustments, or school-wide policies.
We could apply Shannon's concept of entropy that he used to measure uncertainty of information content metaphorically to education. We might think about educational 'entropy' as the degree of uncertainty or lack of knowledge we have about a student's learning. To reduce this entropy, we need to gather more relevant 'information' through assessments, observations, and feedback—which can guide our decision-making.
We could think about Shannon's idea of channel capacity—the maximum rate of information that can be sent over a communication channel without error— in terms of cognitive load in learning. The human brain can only process a certain amount of information at once. Knowing that, we can organize instruction in manageable chunks to avoid overwhelming students.
Shannon also talked about noise as the errors or interferences that can affect the accuracy of a signal during transmission. In education, 'noise' can be any factor that impedes teaching or learning—like classroom disruptions, misconceptions, or even emotional distress. By identifying and minimizing these 'noises', we can enhance the 'signal' (i.e., the teaching-learning process).
Shannon also discussed redundancy in information, noting that redundancy can help in error detection and correction during communication. In education, we can think about redundancy as reviewing and reinforcing concepts to help students better understand and retain information.
Although Shannon's ideas were not developed for education, their
metaphorical application to education provides a way of thinking about and understanding
the complexities of educational decision-making, information management, and
effective teaching-learning processes.