Yoav Bergner
ABSTRACT
We report results of a design-research effort to develop a culturally-relevant educational experience that can engage high school dancers in statistics and data science. In partnership with a local high school and members of its step team, we explore quantitative analysis of both visual and acoustic data captured from student dance. We describe prototype visualizations and interactive applications for evaluating pose precision, tempo, and timbre. With educational goals in mind, we have constrained our design to using only interpretable features and simple, accessible algorithms.
- Dor Abrahamson and Arthur Bakker. 2016. Making sense of movement in embodied design for mathematics learning. Cognitive research: principles and implications 1, 1 (2016), 33.Google Scholar
- Brittany Aronson. 2016. The Theory and Practice of Culturally Relevant Education: A Synthesis of Research Across Content Areas. Review of Educational Research 86, 1 (2016), 163--206. https://doi.org/10.3102/0034654315582066Google ScholarCross Ref
- Dani Ben-Zvi, Katie Makar, and Joan Garfield (Eds.). 2018. International handbook of research in statistics education. Springer. https://doi.org/10.1080/13569783.2010.495279Google Scholar
- Ran Bernstein, Tal Shafir, Rachelle Tsachor, Karen Studd, and Assaf Schuster. 2015. Laban Movement Analysis Using Kinect. International Journal of Computer, Electrical, Automation, Control and Information Engineering (2015).Google Scholar
- Sebastian Böck, Florian Krebs, and Markus Schedl. 2012. Evaluating the Online Capabilities Of Onset Detection Methods. In ISMIR. 49--54.Google Scholar
- Sebastian Böck and Gerhard Widmer. 2013. Maximum Filter Vibrato Suppression for Onset Detection. In Proc. of the 16th Int. Conf. on Digital Audio Effects (DAFx). Maynooth, Ireland.Google Scholar
- Antonio Camurri, Gualtiero Volpe, Stefano Piana, Maurizio Mancini, Radoslaw Niewiadomski, Nicola Ferrari, and Corrado Canepa. 2016. The Dancer in the Eye: Towards a Multi-Layered Computational Framework of Qualities in Movement. Proceedings of the 3rd International Symposium on Movement and Computing (2016), 6:1--6:7.Google ScholarDigital Library
- Jacky C P Chan, Howard Leung, Jeff K T Tang, and Taku Komura. 2011. A virtual reality dance training system using motion capture technology. IEEE Transactions on Learning Technologies 4, 2 (2011), 187--195. https://doi.org/10.1109/TLT.2010.27Google ScholarDigital Library
- Seyed Hossein Chavoshi, Bernard De Baets, Tijs Neutens, Guy De Tré, and Nico Van De Weghe. 2015. Exploring dance movement data using sequence alignment methods. PLoS ONE 10, 7 (2015), 1--25. https://doi.org/10.1371/journal.pone.0132452Google ScholarCross Ref
- Thomas H. Davenport and D.J. Patil. 2012. Data scientist: The sexiest job of the 21st century. Harvard Business Review (2012).Google Scholar
- Kayla DesPortes, Monet Spells, and Betsy DiSalvo. 2016. The MoveLab: Developing Congruence Between Students' Self-Concepts and Computing. Proceedings of the 47th ACM Technical Symposium on Computing Science Education - SIGCSE '16 (2016), 267--272. https://doi.org/10.1145/2839509.2844586Google ScholarDigital Library
- Helen M. Doerr, Robert Delmas, and Katie Makar. 2017. A modeling approach to the development of students' informal inferential reasoning1. Statistics Education Research Journal 16, 2 (2017), 86--115.Google Scholar
- Augusto dos Santos, Kalina Yacef, and Roberto Martinez-Maldonado. 2017. Forró Trainer: Automated Feedback for Partner Dance Learning. Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization - UMAP '17 (2017), 103--104. https://doi.org/10.1145/3099023.3099032Google Scholar
- Daniel C Edelson and Diana M Joseph. 2004. The interest-driven learning design framework: motivating learning through usefulness. In Proceedings of the 6th international conference on Learning sciences. International Society of the Learning Sciences, 166--173.Google Scholar
- Daniel P.W. Ellis. 2007. Beat tracking by dynamic programming. Journal of New Music Research (2007). https://doi.org/10.1080/09298210701653344Google Scholar
- Elizabeth C Fine. 1991. Stepping, saluting, cracking, and freaking: The cultural politics of African-American step shows. TDR 35, 2 (1991), 39--59.Google ScholarCross Ref
- Elizabeth Calvert Fine. 2003. Soulstepping: African American Step Shows. University of Illinois Press.Google Scholar
- Joan Garfield. 2002. The challenge of developing statistical reasoning. Journal of Statistics Education 10, 3 (2002).Google ScholarCross Ref
- Norma González, Rosi Andrade, Marta Civil, and Luis Moll. 2004. Bridging Funds of Distributed Knowledge: Creating Zones of Practices in Mathematics., 115--132 pages. https://doi.org/10.1207/s15327671espr0601-2{_}7Google Scholar
- Perfecto Herrera, Alexandre Yeterian, and Fabien Gouyon. 2002. Automatic Classification of Drum Sounds: A Comparison of Feature Selection Methods and Classification Techniques. In International Conference on Music and Artificial Intelligence. Springer, 69--80. https://doi.org/10.1007/3-540-45722-4{_}8Google Scholar
- G. Hidalgo, Z. Cao, T. Simon, S.-E. Wei, H.Joo, and Y. Sheikh. [n. d.]. OpenPose library.Google Scholar
- Clifford Konold. 2007. Designing a Data Analysis Tool for Learners. In Thinking with data: The 33rd Annual Carnegie Symposium on Cognition, Marsha Lovett and P Shah (Eds.). Lawrence Erlbaum Associates, Hillside, NJ.Google Scholar
- Sohaib Laraba and JoÃńlle Tilmanne. 2012. VideoâĂŘdriven stateâĂŘaware facial animation. Animation and Virtual Worlds (2012), 321--329. https://doi.org/10.1002/cavGoogle Scholar
- Victor R. Lee and Joel Drake. 2013. Quantified Recess: Design of an Activity for Elementary Students Involving Analyses of Their Own Movement Data. Proceedings of the 12th International Conference on Interaction Design and Children 2013 (2013), 273--276. https://doi.org/10.1145/2485760.2485822Google Scholar
- Richard Lehrer, Min Joung Kim, and Ryan Seth Jones. 2011. Developing conceptions of statistics by designing measures of distribution. ZDM - International Journal on Mathematics Education 43, 5 (2011), 723--736. https://doi.org/10.1007/s11858-011-0347-0Google ScholarCross Ref
- Yotam Mann. 2015. Interactive Music with Tone.js. In Proceedings of the 1st annual Web Audio Conference.Google Scholar
- Brian McFee, Matt McVicar, Colin Raffel, Dawen Liang, Oriol Nieto, Josh Moore, Dan Ellis, Douglas Repetto, Petr Viktorin, JoÃčo Felipe Santos, and Adrian Holovaty. 2015. librosa: v0.4.0. (6 2015). https://doi.org/10.5281/ZENODO.18369Google Scholar
- Django Paris. 2012. Culturally sustaining pedagogy: A needed change in stance, terminology, and practice. Educational Researcher 41, 3 (2012), 93--97. https://doi.org/10.3102/0013189X12441244Google ScholarCross Ref
- Herbert J Rubin and Irene S Rubin. 2011. Qualitative interviewing: The art of hearing data. Sage.Google Scholar
- Takaaki Shiratori, A. Nakazawa, and K. Ikeuchi. 2004. Detecting Dance Motion Structure Using Motion. Proc. 10th Int. Conf. on Virtual Systems and Multimedia, VSMM 4 (2004), 1287--1296.Google Scholar
- Jennifer Uharriet. 1996. From Gumboots and Greek Letters Preserving African American heritage through stepping. (1996).Google Scholar
- Barbara Y White and John R Frederiksen. 1998. Inquiry, Modeling, and Metacognition: Making Science Accessible to All Students. Cognition and Instruction 16, 1 (1998), 3--118. https://doi.org/10.1207/s1532690xci1601{_}2Google ScholarCross Ref
- Margaret Wilson. 2002. Six views of embodied cognition. Psychonomic Bulletin & Review 9, 4 (2002), 625--636.Google ScholarCross Ref
Index Terms
- First Steps in Dance Data Science: Educational Design
Recommendations
Movement Computing Education for Middle Grades
MOCO '20: Proceedings of the 7th International Conference on Movement and ComputingThis paper takes a theoretical approach to movement computing education for young learners, with a focus on middle grades (grades 6-8, ages 11-14). This age group is targeted as a lower bound because, while some elements of computational thinking may be ...
Drafting a Data Science Curriculum for Secondary Schools
Koli Calling '18: Proceedings of the 18th Koli Calling International Conference on Computing Education ResearchData science as the art of generating information and knowledge from data is increasingly becoming an important part of most operational processes. But up to now, data science is hardly an issue in German computer science education at secondary schools. ...
Data Science Landscape in Preservice Teacher Education
SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2Tangential to the efforts to bring computer science (CS) into K-12 education, there has been increasing recognition of the critical role of data science (DS) in preparing future citizens to be able to gather, analyze, and represent data. With only 51% ...
Comments