Assessing Algorithmic Media Content Awareness Among Third-grade Students: First Insights from an Exploratory Study

When our interaction with the world becomes more and more mediated by screens, digital and physical realities are intertwined. It is important to understand how the nature of this new reality affects us in our everyday lives. In this paper we explore third-grade school children’s level of understanding of the algorithmic nature of the digital platforms they use daily and influence on their behavior. The growing use of Artificial Intelligence (AI), algorithms and machine learning, in applications popular among children, are changing the ways they see the world and themselves. To understand how the applications are affecting their experience we wanted to study precisely children’s understanding of the role of algorithms in their use of digital media content. Therefore, we wanted to study one aspect of media and digital literacy, algorithmic literacy.
Understanding of digital literacy lies beyond mere use of digital application, simple ability to use them. To be literate, to read more than what is seen, one should be aware of the underlying algorithms affecting our experiences of interaction with the applications. Recent research, dedicated to the distinctions between multi-platform and single-platform users, has demonstrated how diverse platform engagement significantly enhances algorithmic understanding (Espinoza-Rojas et al., 2023; Shin et al., 2020; Andersen, 2020). These studies underline the factor of users’ adaptive behaviors in response to algorithmic outputs and highlight the importance of emotional and ethical considerations of digital interactions.
Algorithm literacy (AL) can be defined as having an understanding of the utilization of algorithms in online applications, platforms, and services. It involves knowledge of the functioning of algorithms, the ability to critically assess algorithmic decision-making, and possessing the skills necessary to navigate and potentially impact algorithmic operations (Andersen, 2020; Dogruel, 2021; Shin et al., 2022). Algorithmic literacy can be considered the informed ability to critically examine, interrogate, propose solutions for, contest and agree with digital services (Long & Magerko 2020). At the core of algorithmic literacy is explicability, which shapes individuals’ attitudes towards and views on algorithmic decision-making technologies (Hermann 2021).
To explore childrens as users of algorithmic media we conducted a study with a teaching experiment in a third-grade classroom (9 to 10 years old) in [nation]. In the beginning of the experiment the students (N=18) filled a questionnaire measuring the awareness of algorithmic media content. The same questionnaire was filled after the teaching experiment.
In the core of the teaching experiment was the student's own project work done in small teams (2-3 in each). During the classes the students designed advertisements consisting of two photos taken by them and two slogans invented by them and attached to the photos. The task was (1) to design a good advertisement of carrots and (2) a bad advertisement of carrots. To work on their photos each team got a bag of carrots.
In the second class the students voted for the best five advertisements. Then children were provided with a calculation of votes and selection of the top five advertisements with a number of votes each got. Based on the results, the students were asked to share media time for each advertisement. This way the children in teams were acting like a human-algorithm. For the task we didn’t give them any math examples for calculating the shares, but rather let them figure it out (or not) by themselves. The small team discussions were audio recorded during the design of the advertisements as well during making decisions on how long each advertisement should get media time. In the end of the second class we demonstrated how a computer-algorithm would share the media time, based on the votes given.