Understanding Black, Asian, Latinx, and White College Students’ Views of Nature: Frequent Thoughts About Wild, Remote, Rural, and Urban Landscapes

Abstract

Nature and landscapes are essential elements of American culture. Consequently, many scholars have examined the public’s perceptions of nature and landscapes. Some posit that Blacks are averse to wildlands and prefer urban settings. Despite the plethora of research, few studies investigate what comes to people’s minds when contemplating nature. This study of 287 American college students examines what students think about when they reflect on nature. Furthermore, the study investigates whether there are significant racial/ethnic differences in the way students think about nature. The study also investigates how gender, social class, age, educational attainment, and academic interests are related to what students think about when they reflect on nature. Data presented here were collected in 2017 from a national sample of students who attend colleges and universities all over the country. The study used a purposive sampling technique to identify students in various majors. The sample contains undergraduates and graduate students. It comprises 102 Whites, 63 Asians, 62 Blacks, and 60 Latinx/other students. The study found that respondents from all racial backgrounds reported thinking about urban landscapes when they contemplated nature. Though the racial differences were significant, the results show that ethnic minority students do not fixate on urban landscapes; less than half of the students of color said they thought about urban landscapes regularly when they thought about nature. Instead, more than 90% of the respondents regularly thought about the wild, wilderness, and untamed lands when they cogitated nature. Respondents were also much more likely to say that they thought about connectedness to nature rather than disconnection from it. The article found that the students’ educational attainment and parental/guardian education were significant in more multivariate models than other explanatory variables. The article urges researchers to investigate a broader range of explanatory variables in future studies.