BROKEN

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BROKEN was an immersive exhibition of 10 exhibits focusing on society’s systems, underpinned by a framework of alternative futures and hope theory. The themes emerged from MOD.’s Future Themes Forum in 2022 and explored nature and Country, collaboration, universal services, housing, democracy and time, and the meaning of learning. Each exhibit prompted consideration of alternative systems to help solve underlying societal issues and was supported by an overarching “what if” provocation. BROKEN was underpinned by Snyder’s Hope Theory, which outlines setting goals, acting with agency, and imagining multiple pathways as core elements of cultivating hope (Snyder, 2012). As visitors interacted with the exhibition, they built a personal narrative aligned with goals, pathways, and agency through the use of unique tokens. They scanned these tokens at stations in each gallery to answer questions related to each exhibit. Upon finishing the exhibition, their answers were presented back in text which aligns with hope theory capabilities. Visitors were able to save this personalised text to their mobile device. BROKEN was over two floors: the ground level included a touch screen game simulating rewilding of land, a collaborative sticker puzzle, and introduction video. Level 1 visualised current and alternative private, public and volunteer expenditure in an interactive light sculpture, examined participation of non-humans in democracy through visualising correlation between tree health and policy changes, a touch screen interactive that allowed the design of homes based on needs, interactive video showcasing the opinions of speculative time commissioners, and a projected visual landscape comprised of drawings that represented visitor’s personal passions. The exhibition was executed in collaboration with researchers and institutions, representing a broad spectrum of knowledge and competencies, to provoke hopeful imaginations of alternatives systems and futures.

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Data source: Supplementary information, Dataset is available at link above, https://data.unisa.edu.au/dap/Dataset.aspx?DatasetID=851396

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