Image-Based Research Via New Media Data Collection

Abstract
Imagery is the crux of research in art. This presentation details the results of 2 visually driven pilot projects that used Image-based research via new media data collection to explore informal learning and changing viewpoints in a global visual cultural context. Image-based research should be the fundamental method for investigating visual, media and digital literacies, yet it has only seen a modest amount of interest.

In pursuing this imbalance, 2 small studies were conducted availing of Amazon’s Mechanical Turk. This crowd sourcing technology allows researcher requests to be submitted to a database where they are made available for individual members to select and complete. These are known as Human Intelligence Tasks, or HITs. Using Mechanical Turk, image-based data was gathered to explore the crowd sourcing mechanism itself with visual literacy as the pretext and insight into understanding visual culture and the visual interpretation of words as the intended outcome. Along with imagery, the second project looked at video interpretation as well as collecting more detailed demographic information and using more culturally ingrained concepts in word selection. The research and image data has yielded some very interesting results of how people perceive and represent concepts visually. The conclusions, although preliminary, suggest a globalizing effect on imagery might be taking place. This research is being developed further into a doctoral thesis that could help inform visually based literacy/media studies and usher in a new method of online data collection. The use of Mechanical Turk and similar methods that employ new media technologies have the potential to promote and further image-based research and inform methodologies in visual literacy, art education and other areas.