Lab Director: Nathan Holbert, PhD

At the Snow Day Learning Lab, our goal is to understand how children make sense of their world through play. We make and study games, toys, and technologies that both offer children opportunities to experience and explore personally interesting phenomena, and further our understanding of cognition.

Snow Day Learning Lab is the name of the research group and a makerspace housed in the basement of Teachers College, Columbia University.

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My current research projects:

Bots of Tots: Exploring the role of meaning and personal values on interest, engagement, and learning of girls in engineering and maker activities at school. The study will contribute to the limited research on young girls’ self-perception in technology and factors that support girls’ participation in engineering activities, as recent data from National Center for Women & Information Technology (2015) reveals that women make up only 15% of practicing engineers and only 26% are in computing occupations.

The Computer Science by Design (CSxD): (grant writing process) is a collaboration between Columbia University and Stanford University. The project aims to uses the domain of computational design both as an exploratory space for developing alternative models merging mathematical and computing experiences as well as a design space for developing and studying the potential of learning environments, designed for novice CS learners, for broadening exposure to and deepening thinking and reasoning with core CS concepts.

In order to study the nature and practice of computing and mathematics in creative domains, we will design a tool specifically for children to easily design and fabricate personally meaningful artifacts. Existing tools (Grasshopper, Auto CAD,  and Tinker CAD) are not designed for novices , focus on general computing practices, or lack support for both design and fabrication. While tools such as BeetleBlocks and Madeup have simplified some aspects of digital 2D and 3D modeling, they have failed to do the same for the mathematics as the core of computational design. For example, if you want to explore parametric equations, you would have to create a considerable amount of code from scratch — there are no supports for deeper mathematical exploration.