Botany through the Looking Glass: Cognitive Neuroscience and its Role in the Use of Art in Botanical Education


  • William Swann Uni SYdney
  • Matthew Pye Sydney



Student engagement within the discipline of Botany is not always limited to scientific content. The patterns, colours and shapes that are produced when investigating plant anatomy via sectioning are highly aesthetic and can immediately engage students. The boundaries between aesthetics and science are often blurred or, more correctly, imagined. Nurturing and developing the inspiration drawn from the integration of these two worlds provides an alternative way of engaging students in the theoretical content of the discipline. Student exposure and engagement with native Australian Flora and botanical education is too often limited and finding novel ways to engage students with Botany is critically important; even more so in this current era of Plant Blindness and climate change denial (Jacobson et al., 2016; Wandersee & Schussler, 2000). To combat this, contemporary neuroscience and cognitive psychology research show promise toward the use of visual mediums to enhance memory, leading to an improvement in educational outcomes (Bigelow & Poremba, 2014; Cohen, Horowitz, & Wolfe, 2009; Corballis, 1966; Gloede, 2015; Jensen, 1971; Kim & Olaciregui, 2008). Therefore, encouraging students to engage with botanical content, via microscopic imagery, scientific/artistic depictions, and more specifically, the production of drawings and artworks (Fernandes et al., 2018; Rosier, Locker, & Naufel, 2013) should be further incorporated into curricula to increase engagement and establish a deeper connection to Botanical subdisciplines such as plant taxonomy, morphology and systematics. In this paper, with reference to established research and an example of a science-art project, we discuss the ways in which the fusion of the aesthetic and scientific worlds creates a feedback loop from which the creative process inspired from scientific material develops a deeper enquiry-based understanding of the material itself






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