Problem formulation, goal and objectives: Algorithms are ubiquitous in digital society, yet complex to understand and often hidden. Algorithmic literacy can be a useful concept when educating and empowering users. However, it is not uniformly defined or used, and the state of knowledge is unclear. The aim of this thesis is to examine algorithmic literacy as a concept, what other concepts are associated, and what empirical and theoretical knowledge exists on this topic. Theory and method: Information literacy research serves as theoretical perspective, focusing on the role of evaluative and explorative approaches of research. The scoping review is chosen as method. Included are peer-reviewed journal articles, published in English from 2018 to 2022, from LISA, LISTA, ERIC ProQuest, and Scopus. Empirical results: Algorithmic literacy is often placed in information, media, and/or digital literacies. Closely related terms are attitude, agency, trust, and transparency. Four themes were identified: the necessity of algorithmic literacy, algorithm awareness as the basis, teaching and learning, and studying algorithmic literacy. Demographic and socioeconomic factors play a role: lower age and higher eduaction correlated with higher levels of algorithmic literacy. Algorithmic literacy is learned via personal experiences and formal education at all levels. Conclusions: Algorithmic literacy research would benefit from a limited number of terms used, and clearly defined terminology. The relationship between closely related concepts needs to be examined further. Librarians and educators should develop and share interventions at regional or national levels. Various knowledge gaps have been identified that may serve as future research agenda.

TikTok differs from how the media audience is used to seeing other social media platforms. When opening the app, the user does not see the friends you have decided to follow. Instead, you are faced with an algorithmically decided and never-ending feed of content personified individually for the specific user. In recent years, TikTok has become a prominent and rapidly growing platform, especially among younger media users. The emergence of TikTok usage among the youth implies an increased need for examining cultural phenomena that are performed on this platform. This study will be exploring the emergence of the online phenomenon known as mediated public shaming on TikTok by critically reviewing how young Swedish TikTok users are engaging in and experiencing the mediated public shaming that is occurring on TikTok as well as its effects by taking a theoretical departure from media literacy theories. The study is a qualitative reception study where the empirical material is conducted by one-to-one interviews with nine mundane Swedish TikTok users between the ages of 16–27. It was discovered that young TikTok users have a complex relationship with the mediated public shaming they face on TikTok and engage in the concept in a rather objective and reflective manner. They do, however, express concern that the design of the media, in conjunction with mediated public shaming, may allow for subconscious effects of their opinions. Looking forward, there is an indicated compelling need for continued research within the field, proposedly further research of online cultures’ roles in the determination of platform design and construction of algorithms.

Research shows that college students are largely unaware of the impact of algorithms on their everyday lives. Also, most university students are not being taught about algorithms as part of the regular curriculum. This exploratory, qualitative study aimed to explore subject-matter experts’ insights and perceptions of the knowledge components, coping behaviors, and pedagogical considerations to aid faculty in teaching algorithmic literacy to college students. Eleven individual, semi-structured interviews and one focus group were conducted with scholars and teachers of critical algorithm studies and related fields. Findings suggested three sets of knowledge components that would contribute to students’ algorithmic literacy: general characteristics and distinguishing traits of algorithms, key domains in everyday life using algorithms (including the potential benefits and risks), and ethical considerations for the use and application of algorithms. Findings also suggested five behaviors that students could use to help them better cope with algorithmic systems and nine teaching strategies to help improve students’ algorithmic literacy. Suggestions also surfaced for alternative forms of assessment, potential placement in the curriculum, and how to distinguish between basic algorithmic awareness compared to algorithmic literacy. Recommendations for expanding on the current Association of College and Research Libraries’ Framework for Information Literacy for Higher Education (2016) to more explicitly include algorithmic literacy were presented.