Dancing Across Boundaries of Computing Education

Sun, 12 Apr 2020 00:00:00 +0000

Overview

The project examines how to integrate machine learning, data science, and physical computing in the context of dance and cheerleading. The work is part of a collaborative grant between NYU and University of Colorado Boulder, which uses both locations to explore across a number of dance and cheerleading environments. The goal is to understand how to help learners leverage their expertise and cultural practices in order to engage them in authentic and personally meaningful computing. The dancers and cheerleaders will learn to create computing systems with programmable electronics worn on the body (physical computing), use those systems to create statistical models of movement and gesture (data science and machine learning), and then apply the models in a digital experiential learning environment. We are working closely with dance educators and learners to produce design principles, curricula, new educational technologies, and comparative analyses across contexts. In NYC, we have a partnership with the non-profit organization STEM From Dance and its founder and CEO Yamilee Toussaint Beach. The organization “gives girls of color access to a STEM education by using dance to empower, educate, and encourage them as our next generation of engineers, scientists, and techies.” Through working with Yamilee, their instructors, and learners we are building on the powerful programming they have already developed to expand the types of concepts the learners can encounter within a computational dance environment.

Research Questions Explored

This project addresses four main research questions:

How can computing be leveraged to build expertise in dance and cheerleading?
How can dance and cheerleading be leveraged to build expertise in computing?
What are the challenges of integrating computing into dance and cheerleading practices?
How can we meaningfully assess learning outcomes and dispositional shifts with respect to computing in the context of dance and cheerleading applications?

This research will produce curriculum and technology to support learning modules in machine learning, data science, and, physical computing, integrating multiple levels of abstraction across the boundaries of hardware and software (i.e., cyber-physical systems). Through this collaborative inquiry researchers will develop transformative knowledge about how to embed computing into established dance practices, resulting in computing curricula and tools that build on the learners’ and educators’ authentic practices and needs.

Research Team

Yamilee Toussaint Beach - CEO & Founder of STEM From Dance
Willie Payne - PhD Student in Music Technology @ NYU
Dr. Kayla DesPortes (PI) - Assistant Professor of HCI and the Learning Sciences @ NYU
Dr. Yoav Bergner (Co-PI) - Assistant Professor of Learning Sciences and Educational Technology @ NYU
Dr. Ben Shapiro (Co-PI) - Assistant Professor of Computer Science @ CUB

Funders

This project has been funded by the National Science Foundation (STEM+C 1933961).

Data+Art Literacy Curriculum Co-Design

Sun, 12 Apr 2020 00:00:00 +0000

Overview

This project explores an art-based perspective on data literacy to promote student relevance, accessibility, engagement, reasoning, and meaning-making with data. Data literacy, or interpreting and reasoning about data, is an essential skill set to be able to inform decisions and actions in today’s society. Collaborating with In collaboration nwith with middle school art and math teachers, we are co-designing curriculum that leverages diverse representational forms, ways of knowing and understanding data.

Research Questions Explored

The work examines:

How do we support effective co-design of data literacy units among art teachers, mathematics teachers, and researchers?
How can we develop educational materials and technology to leverage the representational opportunities across artistic and mathematical practices?
How can we build synergistic curricula for art and math to conceptually support one another?

Answers to these questions will build an understanding of how to support interdisciplinary curriculum design collaborations among researchers and teachers. They will also show how art-integrated, maker-oriented activities can support middle school learners’ data literacy development; and how to design technologies that are accessible and powerful to teachers and learners in these interdisciplinary environments.

Research Team

The work is a collaborative project across New York University, Education Development Center, and Fordham University.

Anna Amato - PhD Student Educational Communication & Technology @ NYU
Marian Tes - PhD Student Educational Communication & Technology @ NYU
Camillia Matuk - Assistant Professor @ NYU (PI)
Kayla DesPortes (Co-PI) - Assistant Professor of HCI and the Learning Sciences @ NYU
Ralph Vacca - Assistant Professor @ Fordham (Co-PI)
Megan Silander - Research Scientist @ EDC (Co-PI)
Veena Vasudevan - Post-Doc @ NYU
Peter Woods Consultant PhD Candidate @ University of Wisconsin-Madison

Funders

This project has been funded by the National Science Foundation (DRK12 1908557).

Data Science | Dr. Kayla DesPortes

Dancing Across Boundaries of Computing Education

Overview

Research Questions Explored

Research Team

Funders

Data+Art Literacy Curriculum Co-Design

Overview

Research Questions Explored

Research Team

Funders