Algorithmic Learning While Creating and Sharing Content on Social Media - Keune and Hurtado
0Computer science continues to face lopsided access for all youth. Identifying youth practices that can be leveraged for computational learning can contribute to a transformed participation in computer science because a wider range of people can see themselves in this field and are ready to contribute to shaping it. In this research, we investigate social media practices as youth-driven practices and rich contexts for computational learning. We thematically analyzed 13 semi-structured interviews with girls (ages 13-18) in Latin America and Europe that also included social media walkthroughs. We translated the youth-practices on social media into pseudo-code to show the computational depth of their everyday, repeated practices, and, in some cases, mundane practices. We found three youth-driven social media practices that can inform the design of youth-driven computational learning activities. These are: (a) Content sharing as flow control structures, (b) content curation as a loop, and (c) playing with algorithms. We highlight the computational themes with data excerpts to illustrate the possibilities of social media as a context for computational learning. We present implications for the design of computational learning opportunities in the form of connected algorithmic learning workshops that are part of future plans for this research and are promising for broadening computing cultures.