danceON: Culturally Responsive Creative Computing

Title of the Paper

danceON: Culturally Responsive Creative Computing

Paper Information

• Subject Area: Interdisciplinary Learning, Programming Education, and Creative Computing
• Keywords: Computing Education, Data Literacy, Dance, Culturally Responsive Pedagogy, Design-Based Research

Research Background and Issues

• Problems and Challenges:

  1. There is a significant lack of inclusivity in computer science and data literacy education, particularly for women and minority groups.
  2. Students' individuality and cultural characteristics are not effectively reflected in traditional classroom teaching.
  3. Creative computing education has yet to fully explore learning approaches that integrate embodied learning, cultural themes, and data relevance.

• Research Importance: Investigating how culturally relevant educational methods, combined with students' familiar and valued backgrounds and issues, can help them perceive computer and data science as personally meaningful and practically valuable learning content.

• Research Motivation and Related Work:

  1. Inspired by the integration of dance and programming, providing learners with a platform for empowerment and self-expression.
  2. Building on existing research foundations, including culturally relevant pedagogy, embodied learning, and domain-specific programming languages, to offer students creative and cutting-edge tools for data science and programming.

Solution

• Proposed Solution: The authors developed a system called "danceON" that enables learners to use their physical movements to create at the intersection of data science, computing, and dance. Its core components include:

  1. A domain-specific programming language (DSL) with declarative syntax and responsive features.
  2. A media player supporting posture detection and classification for video and real-time interaction.
  3. A web-based real-time integrated development environment (IDE).

• Innovations:

  1. The system reduces programming language complexity through declarative syntax, making it suitable for beginners.
  2. It combines real-world body data with creative visualizations, helping learners intuitively understand, learn, and manipulate their own body data.
  3. It supports culturally responsive learning, enabling students to express cultural identity, social issues, or artistic creativity.

• Implementation Steps and Technologies:

  1. Using a simple DSL syntax to bind virtual graphics to actual body movements.
  2. Employing open-source posture detection tools (e.g., PoseNet and OpenPose) to process body position and motion data.
  3. Developing a real-time feedback-enabled coding environment with features like syntax highlighting, real-time error checking, and code completion.

Research Outcomes

• Experiments and Analysis: The authors deployed the danceON system in collaboration with STEM From Dance (SFD). Two remote summer camp activities included 21 participants (all minority high school females), with outcome analysis focusing on the system's expressive capabilities and participants' artistic creations.

• Key Findings:

  1. Cultural Responsiveness: The system was effectively applied to social themes, personalized expressions (e.g., "Black Lives Matter"), and aesthetics-driven creative practices.
  2. Lowering Entry Barriers: Learners were able to quickly write code to generate animations and engage in interdisciplinary exploration.
  3. Creative Coding: The system supported deriving programming inspiration from art and encouraged students to use code to drive artistic creation.

• Advantages: Compared to traditional computing education, danceON demonstrated stronger cultural relevance and was more beginner-friendly. The authors observed that students were more willing to explore, showcase, and code their creativity.

• Experimental or Evaluation Results: Students completed diverse dance projects, such as using code to represent song lyrics, enhance dance expressiveness, or choreograph animations related to specific content. The code was integrated with body movements or music in real time.

• Limitations and Future Directions:

  1. The current system still requires significant support from teachers and project designers, such as code examples and debugging assistance.
  2. Data errors in camera-based posture recognition (e.g., limb occlusion) may pose challenges to the learning experience.
  3. Future improvements should focus on optimizing the IDE, error reporting, and learning progress tracking fields, as well as increasing support for learners to process and understand "messy data."
  4. Exploring how extended timelines or narrowed project scopes can support students in deeper engagement with the complex interactions between dance and data-driven systems.