Tag: new literacy

Week 10 – Extending the Discussion: New Literacies

A.M. Ternullo

Extending the Discussion – Week 11 New Literacies

Technology has shaped and reshaped the way people interact with and create information. Up until the late 1990s, information was gate-kept by publishers. People had to be bona fide experts who paid their dues in the formal education process. Scholars published works on politics, health, science, etc. Conspiracy theories were relegated to cheap tabloids found at check out counters. There was limited information available, as the experts could only supply so much information at one time. But the internet changed that (Leu et al., 2012). Especially in the wake of Web 2.0 technologies of the early 2000s and 2010s – blogs, wikis, Facebook, and Twitter – changed the ways users created and interacted with content. Anyone could post anything. In 2008, I was a newly minted college instructor and would warn my students not to use Wikipedia. I’d set up assignments where I would have them look up things on Wikipedia and then edit the pages to feature outlandish nonsense to prove it couldn’t be trusted – because what would twinklestar099 know about literature of the Cold War that Richard Slotkin didn’t know better? We were wary of authority of sources in the early days of Web 2.0 because those of us teaching and working had grown up with card catalogues and library collections that could only be used on campus, even if the catalogue was now digitized on the computer. There were processes in place to make sure disseminated information was as accurate and well composed as was possible (most of the time).

Teaching literacy in writing classes used to be the difference between an encyclopedia, a trade journal, a scholarly peer-reviewed source, and the difference between .com and .edu sources. But once Web 2.0 emerged – more was demanded. Yi (2021) get at this in his definition of AI competency. As the technologies we have become more complex, so do the means of critical thinking and reflection of the tool. And then to add to that, people have to be cognizant of how the information they find and the tools they use to find it shape them and their possible futures. We have to simultaneously evaluate the material we get, plus the source of the material, and it’s future effect on us, our culture, and our opportunities (Leander et al, 2020; Yi, 2021). Generative AI has the capacity to shape our world more than any Wikipedia article ever did. At some point, the AI is going to become indistinguishable from reality and people are going to have to be critical observers and critical participants in their world. Leu et al. (2012) articulated that the youth will drive the change and the way language happens. But in the past, language change and social change were driven by youth in a social context where fact checking was always going to be possible; I’m not sure that with AI that will be the same. Not to mention that algorithms shape what we see online and there is not a single Internet or ChatGPT or TikTok we encounter (Leander et al, 2020). Every single thing we do online is shaped by our specific interactions with the Internet. Knobel et al. (2014) discuss the ways people work to collaborate to create knowledge, and de-centralize knowledge making, but don’t talk about the pitfalls. We’re living them in 2023. Anyone can post anything online. People give credibility to the person with the camera or the blog post, I think, because we’re still stuck with the old gate-keeping mentality of we can trust published things because their published. Being published used to mean an entire vetting process of credentials, veracity of claims, research validation – now anyone with a smartphone and opinion can post anything. We have witnessed what happens when arm chair experts dominate the discourse an so many important topics with a sharp intensity in this last five years, especially. And if people do not learn to approach digital texts, digital searches, and the technologies that facilitate our access to that information with a critical eye – especially with all generative AI can do – there are problems on the horizon we cannot even articulate today.

References:

Knobel, M., & Lankshear, C. (2014). Studying new literacies. Journal of Adolescent & Adult Literacy, 57(9), 1-5.

Leu, D. J., & Forzani, E. (2012). New literacies in a Web 2.0, 3.0, 4.0, …∞ world. Research in the Schools, 19(1), 75-81.

Leander, K. M., & Burriss, S. K. (2020). Critical literacy for a posthuman world: When people read, and become, with machines. British Journal of Educational Technology, 51(4), 1262-1276.

Yi, Y. (2021). Establishing the concept of AI literacy: Focusing on competence and purpose. JAHR, 12(2), 353-368. https://doi.org/10.21860/j.12.2.8

Week 10 Annotation – Establishing the concept of AI literacy: Focusing on competence and purpose.

A.M. Ternullo

Yi, Y. (2021). Establishing the concept of AI literacy: Focusing on competence and purpose. JAHR, 12(2), 353-368. https://doi.org/10.21860/j.12.2.8

Yi (2021) establishes AI literacy using traditional literacy as a foundation. Yi situates the concept within the every expanding realm of literacies, which emerge as new technologies emerge. Within his framework, Yi calls basic reading, writing, and arithmetic skills functional literacy. Social literacy is new literacy, which takes into account social practice and critical thinking, Technological literacy encompasses technological intimacy and future literacy (the ways technology could be used in the future). He argues that we have moved beyond the realm of simply understanding signifiers and signifieds in printed texts; reading and writing are not sufficient to participate in today’s world. Communication media extends functional literacy to include technology as a means of communication. However, to communicate effectively using a technology, the user has to understand the changing nature of technology and the ways technology is used to communicate in a specific time and place. Yi rejects the idea that AI literacy definitions belong as an extension of digital literacy discussions because they all “set goals for artificial intelligence education” (p. 359). Yi’s definition centers on competency in being adaptable. AI literate individuals will use AI, adapt AI to help them create life, and recognize the change to culture that comes as a result of AI usage. AI literacy also requires that a person be able to maintain their privacy and leverage the AI tool to help them realize their goals. Using AI helps humans grow using non-human technology. AI literacy is inclusive of functional literacy, technological literacy, and new literacy. AI competence literacy is demonstrated by the use through metacognition and anticipation of future needs. In order to be successful, people need to consider the ways AI could alter future prospects and educate themselves accordingly. This also means learners can use AI to create personalized learning, while teachers remain along side to mentor and guide.

Yi does a good job of grounding his theory in the traditions of literacy studies, new literacy, and technological literacy. He establishes clearly how AI literacy is the next evolution of new literacy, and emphasizes that adaptability will be at the core of a human non-human interaction. The sources he cited to articulate his point are grounded in literacy studies, motivational research, and work in artificial intelligence. The concept forms from the literature.

As a doctoral student, educator, and higher education administrator, this new view on AI literacy opens up conversation about what it means to partner with non-human technology in a learning setting. New Literacies up to this point were focused on technologies that served as repositories of knowledge or allowed users to create and interact with knowledge – all at the human level. The shift to AI is different than the shift from traditionally published material to digital material that anyone could produce. AI not only has the capacity to allow humans short cuts in consuming information, it can take human information and create new information and make new knowledge. As a doctoral student, I think this is s fascinating thing to study. As a writing teacher, it’s important to understand so I can prepare my students. As an administrator – this is going to make writing AI policy very difficult because policies are slow to form, the future has to be taking into account. AI is so new that it’s also almost impossible for any one to claim to be AI literate.