Enhancing Algorithmic Literacy: Experimental Study on Communication Students’ Awareness of Algorithm-Driven News
Abstract
This article addresses the need for algorithmic literacy in the field of journalism and media education. Amid the escalating complexity of disinformation in the media landscape, the aim is to enhance users’ awareness and understanding of algorithm-driven content. Through focused research on communication students, the study investigates attitudes, beliefs and knowledge relating to the influence of algorithmic systems on news consumption. Existing scholarship is surveyed to establish the evolving nature of algorithmic literacy, ranging from optimizing search engines to countering misconceptions among digital natives. The relevance of digital information dissemination theories such as incidental consumption, news-finds-me perception, echo chambers and filter bubbles is highlighted in understanding algorithm-driven news selection. Methodologically, two focus groups of communication students from universities in Spain and the United States engage in discussions on critical consumption attitudes, algorithmic beliefs and knowledge. The outcomes reveal the students’ skepticism towards algorithmic news selection and their awareness of emotional triggers shaping news dissemination. Notably, they differentiate between valuable news and trends influenced by algorithms. Conclusions underscore the significance of the “WITH” (Why-Is-This-Here) perception as an indicator of critical consumption and the need for algorithmic literacy. The insights of communication students contribute to algorithmic systems, and their familiarity varies, yet they recognize the impact on news consumption. This study advocates for algorithmic literacy to empower citizens for responsible news consumption and journalism.
Keywords
algorithmic literacy, media education, news consumption, algorithmic systemsReferences
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