What the COVID-19 Pandemic Is Teaching Us About Information Literacy

Uncertainty is a central factor in information behavior.

We are living in very uncertain times right now, and as you might have observed, a lot of people are struggling with it. We are still learning about COVID-19 and there is much we still can’t predict. Information uncertainty also goes beyond the disease itself, reaching into every corner of society and impacting all of our societal systems: public health, economic, education, legal, and so on. Of course, the nature of information (as communication) is that some uncertainty will always be present. Therefore, the main purpose of information literacy is to help people reduce that uncertainty. This isn’t easy when the information in every corner of life is uncertain.

Responses to fear and anxiety often result in Systems 1 thinking.

Systems 1 thinking is emotional-intuitive thinking and antiethical to information literacy. It’s a survival mechanism. It’s what we turn to when presented with the kind of uncertainty that results in fear and anxiety. It explains the crazy run on toilet paper, which no doubt is also due in part to social media fearmongering. It also explains the ostrich effect—denying the existence or seriousness of information. Systems 1 thinking is visceral and cannot always be overcome by logical reasoning.

Information literacy requires Systems 2 thinking.

Systems 2 thinking is logical-rational reasoning and very important for decision making processes, which makes it inherently necessary for information literacy. Since we are living in historically unprecedented times (at least in recent history), I can only hypothesize that a reduction in uncertainty might allow for Systems 2 thinking to take over and for people to start acting more rationally in response to the information around them.

You can’t always “thwart” misinformation with accurate information.

Because we operate under two thinking systems, sharing accurate information with a Systems 1 thinker is unlikely to have any effect on them. And since people are able to compartmentalize these two types of thinking, you might begin to understand how rationality about information can occur in some areas and not others (e.g., the climate change denier who recognizes the value of vaccines). This is happening with the COVID-19 pandemic. So, how do you get through to Systems 1 thinkers? Emotional appeal can work. Personal experience usually does work. We can look at UK Prime Minister Boris Johnson as an example. A few weeks before his diagnosis, he was bragging about shaking hands with everyone. Now he is in the ICU fighting the disease. I truly wish him a speedy recovery and have no doubt that this experience will change his information perspective.

Data literacy is an essential component of information literacy.

The COVID-19 pandemic has illustrated the absolutely essential role of data literacy (we can also call it math literacy) in information literacy. At a very basic level, it seems that many people simply do not “get” the concept of exponential growth. At a higher level, there appears to be a widespread misunderstanding of how the dynamic nature of modeling works. And perhaps most importantly, the lack of understanding about the purpose of measures like social distancing to reduce hospitalization rates and avoid the rippling effect of an overtaxed healthcare system indicates that there is a real struggle for the general public to understand the big picture of data as opposed to its fine points.

Final thoughts.

These observations have implications for the more mundane aspects of information literacy that librarians tackle on a daily basis. First of all, information literacy is dependent upon a duality of reasoning, so it is important that librarians become experts in the psychology of information behavior, as well as cognitive reasoning and development. These should be core requirements in the library and information studies curricula. Secondly, data literacy is inherent in information literacy, and librarians should strive to become data literate themselves. A strong foundation in statistics, plus an introduction to data science or data visualization are recommended. Thirdly, these observations demonstrate that information literacy in the academic setting is not the same as information literacy in the life world. However, both rely on Systems 2 thinking—a prerequisite skill—so that is a key skill to tackle in the classroom from the beginning. Systems 2 thinking (logic or critical thinking) must be tackled before or alongside the loftier goals of information literacy as laid out in the AASL Standards or ACRL Framework. Finally, Systems 2 thinking as a function of information literacy is a skill of practice that requires repeated experiences with the 3 R’s of reading, writing, and research. In doing so, librarians can create a strong scaffold that serves as the basis for the AASL Standards and ACRL Framework, which should ultimately produce successful information literacy learners.



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