Democratizing Children's Computation: Learning Computational Science as Aesthetic Experience

TL;DR

This paper advocates for integrating aesthetic experience into children's computational science education to promote democratic, inclusive, and engaging learning environments inspired by Dewey's educational philosophy.

Contribution

It introduces a Deweyan aesthetic framework to make computational science more accessible and appealing to diverse children, emphasizing the importance of experience in STEM education.

Findings

Aesthetic experience can enhance engagement in computational science.

Dewey's philosophy offers a new perspective for inclusive STEM education.

Aesthetic approach helps reach disinterested or marginalized children.

Abstract

In this paper, we argue that a democratic approach to children's computing education in a science class must focus on the aesthetics of children's experience. In Democracy and Education, Dewey links "democracy" with a distinctive understanding of "experience". For Dewey, the value of educational experiences lies in "the unity or integrity of experience" (DE, 248). In Art as Experience, Dewey presents aesthetic experience as the fundamental form of human experience that undergirds all other forms of experiences, and can also bring together multiple forms of experiences, locating this form of experience in the work of artists. Particularly relevant to our current concern (computational literacy), Dewey calls the process through which a person transforms a material into an expressive medium an aesthetic experience (AE, 68-69). We argue here that the kind of experience that is appropriate for a democratic education in the context of children's computational science is essentially aesthetic in nature. Given that aesthetics has received relatively little attention in STEM education research, our purpose here is to highlight the power of Deweyan aesthetic experience in making computational thinking available to and attractive to all children, including those who are disinterested in computing, and especially those who are likely to be discounted by virtue of location, gender or race.