Today’s article is written by Mitja Jermol
Mitja Jermol is the holder of the UNESCO Chair on Open Technologies for Open Educational Resources and Open Learning and the member of the board of the International Research Center on Artificial Intelligence under auspices of UNESCO (IRCAI), both at Jozef Stefan Institute, Ljubljana Slovenia.
According to a study conducted by Stanford in 2016, more than 80% of middle school students struggle to distinguish between fabricated content and real news stories online (Wineburg et al., 2016). The study has been regularly adapted since (https://purl.stanford.edu/gf151tb4868 ) and results are getting worse not better.
This alarming statistic underscores a growing crisis in education – the production of misinformation and its impact on student learning.
The digital age that brought unprecedented access to information comes with the challenge of navigating an increasingly complex landscape of truth and falsehood. Educational and academic institutions, traditionally bastions of knowledge and critical thinking, are facing the difficult task to prepare students to distinguish fact from fiction in an environment where misinformation spreads at unprecedented speeds through social media, apps, and digital platforms.
With the appearance of more and more powerful generative AI that allows everyone to create millions of compelling but untruth stories the challenge is becoming increasingly complex as the line between authentic and artificially generated content becomes ever thinner.
Several studies revealed the complex nature of misinformation and its impact on learning. Researchers (Ecker et all 2022) found that exposure to misinformation can create persistent misconceptions that resist correction, even when students are later presented with accurate information. Study firstly published in Scientific American in 2018 (Greenemeier 2018) demonstrated that misinformation spreads up to six times faster on social media platforms than facts, making it particularly challenging for students to maintain accurate understanding of current events.
Figure generated by AI
It looks like humanity is rapidly moving from the real world based on data, facts and common truth devised through a scientific method to a pure fiction and narrative-based reality, where the line between truth and fabrication becomes increasingly blurred. These challenges pose significant risks to the educational process. Students who cannot effectively evaluate information sources may develop misconceptions that hamper their learning, make decisions based on false baselines, and propagate the spread of misinformation. In addition, the inability to distinguish credible from non-credible information undermines the fundamental goals of education – developing informed, critical thinkers.
Several studies (Centola et all, 2018, Xie J et all, 2011) demonstrated that only from 10-25% of the whole population in a country can be enough to flip social conventions or establish new norms. So, if one combines the power of Generative AI, with the amplifying effect of social media and use them strategically on population that grew in the complex world of fake and truth without proper mechanisms and methods to distinguish between them, the potential for manipulation and erosion of trust in institutions and information itself becomes incredibly dangerous.
However, there are already several mechanisms in place to address misinformation and several new attempts to address these challenges in education combining traditional critical thinking skills with modern digital literacy techniques, supported by systematic curriculum integration, critical pedagogy and continuous assessment.
The SIFT method (Stop, Investigate, Find better coverage, Trace claims) for example, developed by Caulfield (Caufield 2023) has shown promising results in improving students’ ability to evaluate online information. The CRAAP test (Currency, Relevance, Authority, Accuracy, Purpose) developed by (Blakeslee 2004) mainly used by librarians might be properly adapted to address information platform-specific factors such as algorithmic bias, user-generated content, and the spread of misinformation within closed networks. This adaptation might include motivation and author’s credibility as well, emotional impact and more.
Several more traditional approaches include various combinations of inquiry-based learning, lateral reading and source evaluation, collaborative fact-checking projects, simulations and role-playing, critical analysis of media narratives.
Finally, we always like to conclude with teachers and put all the burden on them. It is true that teachers should serve as models of critical evaluation while teaching students. It is also advisable that their professional development should involve being informed about emerging misinformation trends, they should learn and teach evaluation techniques, should develop skills in guiding student discussions about controversial topics, and more. While teachers, schools, and educational systems are crucial, the issue of separating fake from truth in education extends far beyond the classroom. The teachers are only one component of a broader societal challenge that requires a coordinated approach. Addressing this complex issue demands a comprehensive strategy that involves family involvement, community engagement, media literacy initiatives, platform accountability, and ongoing research into the nature and impact of misinformation.
The ability to separate fake from truth has become a fundamental skill for the 21st century. The future of informed citizenship and democratic discourse depends on our ability to prepare students for an increasingly complex information landscape. The truth is that we are not very good at it today and that the rapid development of technologies, fast dissolvement of norms and practicing miss-information at the highest levels of society without accountability does not serve as an example.
References
Blakeslee S, (2004) “The CRAAP Test,” LOEX Quarterly: Vol. 31: No. 3, Article 4.
Available at: https://commons.emich.edu/loexquarterly/vol31/iss3/4
Caulfield M, Wineburg S, (2023), “How to Think Straight, Get Duped Less, and Make Better Decisions about What to Believe”, University of Chicago Press; First Edition (November 16, 2023)
Centola D, Becker J, Brackbill D, Baronchelli A. (2018) “Experimental evidence for tipping points in social convention” .Science 360,1116-1119(2018).DOI:10.1126/science.aas8827
Ecker U.K.H., Lewandowsky S., Cook J. et al (2022). “The psychological drivers of misinformation belief and its resistance to correction”. Nat Rev Psychol 1, 13–29 (2022). https://doi.org/10.1038/s44159-021-00006-y
Greenemeier L (2018), “False news travels 6 times faster on Twitter than truthful news”, https://www.pbs.org/newshour/science/false-news-travels-6-times-faster-on-twitter-than-truthful-news
Wineburg S, McGrew S, Breakstone J, Ortega T. (2016).” Evaluating Information: The Cornerstone of Civic Online Reasoning”. Stanford Digital Repository. Available at: http://purl.stanford.edu/fv751yt5934
Xie J, Sreenivasan S, Korniss G, Zhang W, Lim C, Szymanski BK. (2011) “Social consensus through the influence of committed minorities”. Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Jul;84(1 Pt 1):011130. doi: 10.1103/PhysRevE.84.011130. Epub 2011 Jul 22. PMID: 21
