Understanding audience participation patterns using digital image recognition and data mining of in gallery experiences

Paper
Nicolaas Earnshaw, Australia

Museum interactives are often designed to engage the visitor in a process of meaningful and ‘experienced’ learning. Learning-by-doing is a strong method to educate, entertain and prompt visitors to seek a deeper connection to the stories being shared. Hence, interactive experiences can ask the visitor to contribute their own ‘meaningful’ story. But how does one measure the success of this type of co-creational learning through experience? And what would a digitally enabled and tracked experience tells us?

This paper uses eight months of web analytic data, user pattern analysis and image recognition techniques (developed by Carlos Arroyo of the Powerhouse Museum) to demonstrate how visitor behaviour and engagement with in a gallery interactive experience can be better understood and thus refined to meet specific, well defined and achievable objectives. The project looks at over 7000 images contributed as part of the Faith Fashion Fusion interactive photo-booth. It seeks to find patterns of visitor behaviour and asses their alignment to the curators targeted thematic and learning objectives.

This paper demonstrates the value of data driven approaches, themselves founded on web and digital analytical tools, in improving the effectives of how Museums engage its visitors.