Abstract:

Recent education policy changes in the U.S. and globally are pushing for computer science and artificial intelligence (A.I.) instruction for young people in K-12 grade bands. At the same time, student outcomes in these initiatives have varied widely depending on implementation. At stake is whether such programs can motivate students not only to succeed in the classroom but to advance beyond introductory classes and develop satisfying professional pathways. The computational action framework, proposed by Tissenbaum,Sheldon, and Abelson in 2018, offers a way of scaffolding young people in creating technology projects that address real issues in their communities, rather than “just coding.” This paper presents the computational action process, a curriculum and set of tools that fully flesh out the original framework, and the results of a human-subject research study on the computational action process with U.S. and international students aged 11 to 18. Analyses of pre/post surveys on the Likert scale show that after the intervention, students showed an increase in computation skill and identity, an increase in confidence in their ability to make a prosocial impact,and an increase in their confidence in solving ambiguous problems on their own. Students’ responses post-intervention demonstrated more impact-driven, community-oriented thinking. These promising results indicate that the computational action process can be a helpful addition to computer science and A.I. education programs to motivate student learners.

Keywords:

Constructionism, artificial intelligence, computational thinking, K12 Computer Science.