In my Statement of Proposed Study I declared my desire to get down and dirty with communities in Akwapim, Ghana to help them develop their digital literacy. As I transition from my Fulbright application to researching more about literacy (digital +) I feel like I am going to be throwing that word around a lot, which means its time to seriously start thinking about what literacy means, and how it fits into a digital future. I’ have begun collecting some texts and thoughts about that very subject, and will begin posting them sooner or later.
For now, though, I want to mention an worthwhile pair of articles found in the current SEED. These articles offer two, though not oppositional, perspectives on scientific literacy. Personally, scientific literacy is among the most important, especially as we are moving into a time when the boundary between technology on life is rapidly diminishing.
From ‘Scientific Literacy and the Habit of Discourse’ by Thomas W. Martin, SEED - September / October 2007:
We frequently hear the refrain that if our nation simply raised the level of science courses, taught our children more subjects, and / or gave them more hands-on lab work, we could ensure the production of a citizenry capable of understanding an increasingly complex world. They would then be prepared to make the difficult choices of the 21st century, etc. However, my incoming students’ technical mastery already exceeds what even the most rosy-eyed optimist could realistically dream for America (or the globe) as a whole. In other words, even if a citizenry were to achieve an impressive degree of scientific literacy–construed as raw conceptual competence–it would still be entirely possible for those same citizens to routinely subordinate scientific evidence to their own deeply-ingrained cultural suppositions.
From ‘Camelot is Only a Model: Scientific Literacy in the 21st Century’ by Steven Saus, SEED - September / October 2007:
Understanding that our scientific knowledge is “only” a model is the key to true scientific literacy. Knowing this tells us that our science has built-in limitations, but that it does resemble reality in very fundamental ways. More importantly, that understanding gives us permission to use our models when they are useful–and permission to discard them when they no longer meet our needs.
