Abstracts
Abstract
This article documents how I came to combine autoethnographic accounting with visual arts practice. I developed this mixed methods approach for my PhD study which explores the interdisciplinary possibilities offered by combining visual arts practice with STEM (science, technology, engineering, and mathematics). Visual arts practices as narrative forms tend toward the non-linear (Anae, 2014), whilst autoethnography offers self-reflection. Writing an autoethnographic account for an artwork has the potential to generate a wealth of data, some of which are visible, some of which are not. The invisible data become available only when the artist speaks to/writes about the artwork. If some content/context of a visual artwork is only visible through background information provided by the art maker, this discovery troubles another issue concerning our notions of what a good visual artwork is. Finally, I test this article’s autoethnographic authenticity against Adam’s four characteristics of autoethnography.
Keywords:
- autoethnography,
- visual arts,
- STEM,
- positionality,
- invisible data