Exploring the relationship between undergraduate education and sustainable transport attitudes

ABSTRACT

The objective of this study is to discuss the impact of education and environmental attitudes on the support for sustainable transport policies among civil engineering students. We surveyed a total of 524 students from Kyoto University, Japan, and asked them about the number of environment-related modules they have taken, their attitudes toward environmental issues, and their attitudes toward various transport policies. We first demonstrate that there is a positive relationship between course selection and environmental concern and discuss self-selection issues by comparing civil engineering students with students from other faculties. We then use a structural equation model (SEM) to show that education and environmental concerns also positively influence attitudes to transportation policies aimed at reducing car usage. We conclude that raising awareness of environmental problems and promoting responsibility through the university curriculum is important to educate future transport decision makers as well as to gain general support for sustainable transportation policies.

KEYWORDS:

• Environmental attitudes
• environmental concern
• sustainable transport
• transport policy
• university education

Acknowledgments

We thank the various staff who allowed us to survey in their classes. In addition, we thank Dr. Giancarlo Flores for various discussions related to literature on the vision for civil engineering.

Notes

¹ The term acceptability should be used for hypothetical or not yet implemented schemes whereas for implemented schemes the term acceptance is commonly used (see Gärling et al., 2008; Schuitema, Steg, & Forward, 2010).

² GFI (goodness-of-fit index): GFI varies from 0 to 1, but theoretically can yield meaningless negative values. By convention, GFI should be approximately 0.90 or more to accept the model. By this criterion, the present model is accepted.

³ RMSEA (root mean square error of approximation): There is adequate fit model if RMSEA is less than or equal to 0.08.

⁴ CFI (comparative fit index): In examining baseline comparisons, the CFI depends in large part on the average size of the correlations in the data. If the average correlation between variables is not high, then the CFI will not be very high. A CFI value of 0.90 or higher is desirable (Kline, 1998).