A Delicious Metaphor: How ML and IL Can Address the Crisis of Trust

Abstract

Response to David Buckingham’s blog The trouble with ‘information literacy’ posted to his personal website on 01/04/2023

Keywords

Media Literacy, Information Literacy

It’s one of those perfect summer days, and nothing is sweeter after a late afternoon beach day than a cup or cone of ice cream. Standing in line for ice cream at Brickley’s, a Rhode Island institution, I’m debating both to myself and with a friend. Which should it be? Butter pecan or chocolate ripple? Or should I try that intriguing new flavor listed on the blackboard, lemon ginger? In a playful discussion, my friend tempts me to debate and prioritize the flavors to determine which one is “best,” but I know this is futile and misguided. All the flavors can be perfect, depending on the moment or situation, because frozen milk and cream mixed up, flavored, and sweetened is delicious!

Flavorful Literacies

Although you might find it surprising, I often use the flavors of ice cream as a metaphor to explain the many different “new” literacies that are now part of the landscape of elementary, secondary and higher education, ever since those teachers in Rochester, New York first developed the concept of visual literacy way back in the 1960s. 

When we examine the relationship between media literacy (ML) and information literacy (IL), they are connected in a deep and organic way, far from being merely “adjacent” or “overlapping” areas of inquiry, as some scholars claim (Buckingham, 2023).

IL and ML are like different flavors of ice cream. Their key ingredients?  Both are rooted in a shared purpose: to prepare people with the life skills they need for living in a world with media and technology. In expanding the concept of literacy, both situate the practice of literacy as a cognitive, social, and emotional process that involves accessing, analyzing, reflecting, synthesizing, and sharing.

Both terms have been crafted by passionate people with distinctive backgrounds and areas of expertise. Both IL and ML reflect a longstanding concern with forms, genres, or types of media and technology. ML and IL proponents have a distinguished history with pedagogical practices, a professional literature, and a disciplinary tradition. They both work inside contexts that are rooted in the institutional structures of higher education. Practitioners of both have made considerable effort to be responsive to people’s lived experience and have adapted to changing cultural norms and values.

Right now, there is a ripe opportunity for both ML and IL concepts to address the crisis of trust. As public trust in U.S. institutions declines, there is increasing partisan polarization, a rise in disinformation campaigns, and frequent attacks on the press from political elites. ML and IL educators must address the changing nature of credibility in a post-truth world by re-evaluating the concepts of truth, authority, and trust, analyzing media structures and power dynamics (Barton, 2019;  Ranschaert, 2020).

Rethinking Credibility and Trustworthiness

For a long time, ML and IL practitioners have benefited from sharing ideas with each other and there’s clear evidence that exposure to diverse ideas is helping to coalesce important commonalities. Just as media literacy benefitted from developing its key concepts and core principles from exposure to many theoretical perspectives from the fields of education, media studies, and the humanities, information literacy reached a “coming of age” status with the publication of the Framework for Information Literacy for Higher Education in 2016. This work proposes a cluster of interconnected core concepts, with flexible options for implementation, rather than on a set of standards or learning outcomes, or any prescriptive enumeration of skills (ACRL, 2015).

One of the key concepts in IL directly addresses a problem that David Buckingam identifies  when suggesting that the so-called “fake news crisis” has led policymakers to narrow and dualistic thinking about differentiating between “good” and “bad” information. He makes a good point. In ML, some approaches create hierarchies of quality in easy-to-use charts that put quality news content at the top and the work of bloggers at the bottom. In IL, some approaches point out that scholarly sources have been peer-reviewed and other sources have not, stating that content in library databases is more reliable than stuff available on the open internet. 

To rebut these problematic approaches, educators and librarians who embrace the ACRL framework emphasize this key idea: Authority is constructed and contextual. Because information resources reflect the expertise, knowledge base, and point of view of their creators, the credibility and trustworthiness of the content cannot be understood apart from the user’s own purpose for using it as well as the context of the use.

Think of it this way: When I am trying to write about the cultural history of ice cream, I will want to rely on scholarly sources that I find in library databases. When I am trying to buy an at-home ice cream maker, I will need to view and read reviews on YouTube, Amazon and Google. When I’m trying to find a great ice cream shop in Prague, I will search on Google Maps –but I will read travel blogs, too. The quality of these sources is not predetermined: my judgments of quality are situational and contextual in relation to my own needs. Teaching students to be metacognitive as they search can be a valuable component of ML and IL learning (Gabaree, 2022).

But to be frank, all of this searching, reviewing, and analyzing takes time –and effort. You may be overwhelmed just by reading about them. But because IL and ML have not yet become routine and habitual practices of everyday life, many people simply dislike being faced with “too much information.” Google is working hard to simplify search – so much so, that

1 in 4 searches result in zero clicks as someone enters a query on a search engine but doesn’t end up clicking on any of the results (Tober, 2022). So people are not spending a great deal of time analyzing results. Instead, they make quick decisions to get to what they want and refine and iterate as they go. The machine’s algorithms provide them with what they want.

Networks of Trust

To avoid being overwhelmed by information, people now rely on their emotions and their social relationships to help them determine who and what to trust. Researchers have found that if your friends distrust the mainstream media, you will too (Ognyanova, 2019). Moving forward, both IL and ML scholars will need more exposure to concepts from psychology, interpersonal communication, human development, mental health, organizational behavior, and sociology to understand how networks of trust are re-shaping the meaning-making process.

Finally, it’s important to ask: Who benefits from pitting chocolate against strawberry? Make no mistake: even as we recognize the similarities between IL and ML, people definitely have their favorite terms –and they tend to be loyal to them. Networks of trust can also perpetuate us-versus-them frameworks, after all. There are numerous reward systems in place for staying inside the disciplines (of librarianship or communication/media studies, or education) as well as many risks in attempting to synthesize or cross boundaries. And scholars can get away with throwing shade, shaming, or blaming colleagues, particularly when they publish outside of scholarly and professional journals.

So, we all need much more interdisciplinarity to address the crisis of trust we’re experiencing now. Without it, we may miss out on opportunities to see how deeply the ideas at the heart of new literacies intersect and entwine. We may miss out on some of the paradoxes and inconsistencies that have escaped our blind spots. For this reason, let’s choose to focus on the commonalities between IL and ML rather than see them as competitors. It may be far more productive to mix-and-match the many new flavors of literacy to meet the complex phenomena that are changing under our feet. Of course, we will need data literacy and algorithm literacy and AI literacy – and more new literacies yet to be conceptualized. Perhaps working collaboratively, we can scoop up and serve customized ice-cream sundaes with flavorful elements of all the new literacies.

References

Barton, C. (2019). Critical Literacy in the Post-Truth Media Landscape. Policy Futures in Education, 17, 1024 – 1036. https://doi.org/10.1177/1478210319831569.

Buckingham, D. (2023, January 4). The trouble with information literacy. https://davidbuckingham.net/2023/01/04/the-trouble-with-information-literacy/

Gabaree, S. (2022). Mitigating the spread of online misinformation through metacognition. Journal of Media Literacy. https://ic4ml.org/journal-article/a-metacognitive-approach-to-reduce-the-spread-of-online-misinformation/

Ognyanova, K. (2019). The social context of media trust: A network influence model. Journal of Communication 69(5), 539–562. https://doi.org/10.1093/joc/jqz031.

Ranschaert, R. (2020). Authority and carnival: Preservice teachers’ media literacy education in a time of Truth Decay. Educational Studies, 56, 519 – 536. https://doi.org/10.1080/00131946.2020.1799219.

Tober, M. (2022, October 22). Zero Clicks Study. SemRush.  https://www.semrush.com/blog/zero-clicks-study/