What Does Learning Look Like?: Data Visualization of Art Teaching and Learning

What Does Learning Look Like?: Data Visualization of Art Teaching and Learning

Pamela G. Taylor (Virginia Commonwealth University, USA)
DOI: 10.4018/978-1-4666-8142-2.ch018

Abstract

Drawing upon the data visualization work of Lev Manovich and Manuel Lima, in this chapter the author discusses ways for envisioning and representing the complex teaching and learning that is associated with the visual arts. Experiences and examples are shared that use new and old technologies to create and make connections among critically reflective collections of student learning artifacts such as research, journals, preliminary sketches, work in other classes, and realms of experience outside of school. Instead of relying on one final art product, the author explores embedded data mining and visualization as a viable approach to gauging student learning. Following the lead education notables Elliot Eisner (2002, 2004), John Dewey (1934), and Howard Gardner (1985), this research positions the visual arts as a common thread throughout disciplines. Such inherent and fundamental visual arts practices as portfolios, project-based instruction, and exhibition continue to expand instruction and learning in such classes as English, math, science, and history. The implications include the possibility that art education will lead the way to implementing authentic embedded assessment processes across education disciplines and grade levels.
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Understanding Data Visualization Through An Artist’S Eye

Much like the typical pie charts and bar graphs seen in math class and political analyses, data visualization functions as a way to visually represent data sets. Supposedly, such visualizations provide a clearer way to see and understand data analyses than through a narrative explanation alone. The idea of representing data in illustrative ways actually dates back to Prehistoric art with cave paintings, as well as to the carvings, scrolls, story vases and petroglyphs of ancient Egyptians, Greeks, Mayan, and Native Americans. Human beings have a strong need to see and understand data visually. Be it to provide directions, explanations, plans, strategies, or proof of an argument, more often than not a pen, pencil, computer stylus or touch pad is used to further an explanation. In the case of such artists as Leonardo da Vinci, the data visualized and indeed discovered stands the test of time. Cases in point may include the Vitruvian Man, images of flying machines, and the Mona Lisa’s androgyny (Boucher, 2003).

Key Terms in this Chapter

Hypertext: Text, image, parts of images, etc that is displayed and linked through a computer or other electronic device to other references. A reader may click on a hyperlink and flow to the connected reference in a hypertext. The World Wide Web is considered a large hypertext structure.

Performative: Unlike performing, performative reflects an act of becoming. One performs an act that creates a state of affairs such as when an officiant performs a wedding, two people become married.

Universal: Of, affecting, or done by all people or things in the world or in a particular group; applicable to everyone and everything.

Multidisciplinary: Refers to being composed of or combing several disciplines or subjects of study.

Multivariance: Possessing the multiple possibilities or variables of actions, ideas, or outcomes.

Problematize: To delve more critically into a situation rather than accepting for face value. To complicate in order to understand in more detail.

Backward Design: A method of designing curriculum for education that formulates what students should know and be able to do before choosing instructional strategies and evaluation instruments.

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