Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-26T22:05:04.967Z Has data issue: false hasContentIssue false
  • English
  • Français

From Thoughts to Actions: The Importance of Climate Change Education in Enhancing Students’ Self-Efficacy

Published online by Cambridge University Press:  13 November 2019

Subaru Ken Muroi  and
Edoardo Bertone Open the ORCID record for Edoardo Bertone [Opens in a new window]
Subaru Ken Muroi
Affiliation:
Faculty of Society and Design, Bond University, Gold Coast, Queensland, Australia
Edoardo Bertone*
Affiliation:
School of Engineering and Built Environment & Cities Research Institute, Griffith University, Southport, Queensland, Australia
*
*Corresponding author. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

The relation between the understanding and belief of the site-specific dangers of climate change and the behaviour that individuals take to mitigate their impacts was assessed to investigate the psychological antecedent to pro-environmental behaviour; a necessity to mitigate anthropogenic climate change at the individual level. A quantitative cross-sectional design was employed to measure beliefs and behaviour of university students. Correlation was measured between the belief in one’s ability to affect change and pro-environmental behaviour. The hypothesis that nations facing greater climate threat would behave accordingly was tested on the two largest national representatives of the sample, China and Australia. In addition, a naïve Bayesian network, coupled with a self-organising map, was developed to explore correlations between self-efficacy and participants’ socio-demographic features. Results showed that Chinese students are more likely to have higher self-efficacy, while such trend was not noticed for Australians. Similarly, participants with higher educational qualifications, older, and with higher paid jobs also have a higher chance of presenting pro-environmental behaviour. Despite the study limitations, there seems to be evidence suggesting that educational and climate change policies have affected students’ self-efficacy and individual commitment to mitigation.

Keywords

Bayesian networksclimate change educationnational education policyself-efficacy
Type
Article
Information
Australian Journal of Environmental Education , Volume 35 , Issue 2 , July 2019 , pp. 123 - 144
Copyright
© The Author(s) 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anderson, A. (2013). Climate change education for mitigation and adaptation. Journal of Education for Sustainable Development, 6, 191–206.CrossRefGoogle Scholar
Antonio, R.J., & Brulle, R.J. (2011). The unbearable lightness of politics: Climate change denial and political polarization. The Sociological Quarterly, 52, 195–202.CrossRefGoogle Scholar
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 24.CrossRefGoogle Scholar
Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37, 122–147.CrossRefGoogle Scholar
Bandura, A. (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28, 117–148.CrossRefGoogle Scholar
Bandura, A. (2006). Guide for constructing self-efficacy scales. In Pajares, F. & Urdan, T.S. (Eds.), Self-efficacy beliefs of adolescents (pp. 307–337). Greenwich, CT: Information Age.Google Scholar
Bertone, E., Sahin, O., Richards, R., & Roiko, A. (2016). Extreme events, water quality and health: A participatory Bayesian risk assessment tool for managers of reservoirs. Journal of Cleaner Production, 135, 657–667.CrossRefGoogle Scholar
Bertone, E., Sahin, O., Stewart, R.A., Zou, P.X.W., Alam, M., Hampson, K., & Blair, E. (2018). Role of financial mechanisms for accelerating the rate of water and energy efficiency retrofits in Australian public buildings: Hybrid Bayesian network and system dynamics modelling approach. Applied Energy, 210, 409–419.CrossRefGoogle Scholar
Birkmann, J., & Welle, T. (2016). The WorldRiskIndex 2016: Reveals the necessity for regional cooperation in vulnerability reduction. Journal of Extreme Events, 3, 1650005.CrossRefGoogle Scholar
Carleton, T.A., & Hsiang, S.M. (2016). Social and economic impacts of climate. Science, 353, (6304):aad9837.CrossRefGoogle ScholarPubMed
Chen, S.H., & Pollino, C.A. (2012). Good practice in Bayesian network modelling. Environmental Modelling & Software, 37, 134–145.CrossRefGoogle Scholar
Cook, J., & Lewandowsky, S. (2016). Rational irrationality: Modeling climate change belief polarization using Bayesian networks. Topics in Cognitive Science, 8, 160–179.CrossRefGoogle ScholarPubMed
Coutenay-Hall, P., & Rogers, L. (2002). Gaps in mind: Problems in environmental knowledge-behaviour modelling research. Environmental Education Research, 8, 283–297.CrossRefGoogle Scholar
Curran, G., & Hollander, R. (2015). 25 years of ecologically sustainable development in Australia: Paradigm shift or business as usual? Taylor & Francis.Google Scholar
Dai, H., Xie, X., Xie, Y., Liu, J., & Masui, T. (2016). Green growth: The economic impacts of large-scale renewable energy development in China. Applied Energy, 162, 435–449.CrossRefGoogle Scholar
Dasgupta, P. (2008). Discounting climate change. Journal of Risk and Uncertainty, 37, 141–169.CrossRefGoogle Scholar
Fenton, N., & Neil, M. (2013). Risk assessment and decision analysis with Bayesian networks. New York, NY: CRC Press.Google Scholar
Fernández, A., Morales, M., Rodríguez, C., & Salmerón, A. (2011). A system for relevance analysis of performance indicators in higher education using Bayesian networks. Knowledge and Information Systems, 27, 327–344.CrossRefGoogle Scholar
García, P., Amandi, A., Schiaffino, S., & Campo, M. (2007). Evaluating Bayesian networks’ precision for detecting students’ learning styles. Computers & Education, 49, 794–808.CrossRefGoogle Scholar
Garschagen, M., Hagenlocher, M., Comes, M., Dubbert, M., Sabelfeld, R., Lee, Y.J., … Neuschäfer, O. (2016). World risk report 2016. In World Risk Report. Berlin.Google Scholar
Hall, C., & Allan, F. (2014). Influencing carbon behaviours: What psychological and demographic factors contribute to individual differences in home energy use reduction and transportation mode decisions? Energy and Environment Research, 4, 1.CrossRefGoogle Scholar
Han, Q. (2015). Education for sustainable development and climate change education in China: A status report. Journal of Education for Sustainable Development, 9, 62–77.CrossRefGoogle Scholar
Harring, N., & Jagers, S.C. (2018). Why do people accept environmental policies? The prospects of higher education and changes in norms, beliefs and policy preferences. Environmental Education Research, 24, 791–806.CrossRefGoogle Scholar
He, L. (2010). China’s climate-change policy from Kyoto to Copenhagen: Domestic needs and international aspirations. Asian Perspective, 34, 5–33.CrossRefGoogle Scholar
Heimlich, J.E., Mony, P., & Yocco, V. (2014). Belief to behavior: A vital link. In Stevenson, R., Brody, M., Dillon, J. & Wals, A. (Eds.), International handbook of research on environmental education (pp. 262–274). London: Taylor & Francis.Google Scholar
Hines, J.M., Hungerford, H.R., & Tomera, A.N. (1986/87). Analysis and synthesis of research on responsible environmental behavior: A meta-analysis. Journal of Environmental Education, 18, 1–8.CrossRefGoogle Scholar
Howell, R.A. (2014). Investigating the long-term impacts of climate change communications on individuals’ attitudes and behavior. Environment and Behavior, 46, 70–101.CrossRefGoogle Scholar
Hungerford, H.R, & Volk, T.L. (1990). Changing learner behavior through environmental education. The Journal of Environmental Education, 21, 8–21.CrossRefGoogle Scholar
Hunt, A., & Watkiss, P. (2011). Climate change impacts and adaptation in cities: A review of the literature. Climatic Change, 104, 13–49.CrossRefGoogle Scholar
Intergovernmental Panel on Climate Change. (2014). Climate change 2014. In Fifth Assessment Report (AR5). Geneva: Author.Google Scholar
Kim, S.Y., & Wolinsky-Nahmias, Y. (2014). Cross-national public opinion on climate change: The effects of affluence and vulnerability. Global Environmental Politics, 14, 79–106.CrossRefGoogle Scholar
Knight, K.W. (2016). Public awareness and perception of climate change: A quantitative cross-national study. Environmental Sociology, 2, 101–113.CrossRefGoogle Scholar
Kohonen, T. (1998). The self-organizing map. Neurocomputing, 21, 1–6.CrossRefGoogle Scholar
Lauren, N., Fielding, K.S., Smith, L., & Louis, W.R. (2016). You did, so you can and you will: Self-efficacy as a mediator of spillover from easy to more difficult pro-environmental behaviour. Journal of Environmental Psychology, 48, 191–199.CrossRefGoogle Scholar
Leiserowitz, A. (2007). International public opinion, perception, and understanding of global climate change. In Human development report 2007/2008. New York, NY: United Nations Development Programme.Google Scholar
Lo, A.Y., & Chow, A.T. (2015). The relationship between climate change concern and national wealth. Climatic Change, 131, 335–348.CrossRefGoogle Scholar
Longhi, S. (2013). Individual pro-environmental behaviour in the household context . In ISER Working Paper Series 2013–21. Colchester, UK: University of Essex.Google Scholar
Lynn, P., & Longhi, S. (2011). Environmental attitudes and behaviour: who cares about climate change? In McFall, S.L. & Garrington, C. (Eds.), Understanding society: Early findings from the first wave of the UK’s household longitudinal study (pp. 109–116). Colchester, UK: Institute for Social and Economic Research, University of Essex.Google Scholar
Marquart-Pyatt, S.T. (2015). Public opinion about the environment: Testing measurement equivalence across countries. International Journal of Sociology, 45, 309–326.CrossRefGoogle Scholar
Marx, S.M., Weber, E.U., Orlove, B.S., Leiserowitz, A., Krantz, D.H., Roncoli, C., & Phillips, J. (2007). Communication and mental processes: Experiential and analytic processing of uncertain climate information. Global Environmental Change, 17, 47–58.CrossRefGoogle Scholar
McFall, S.L., & Garrington, C. (Eds.). (2011). Understanding society: Early findings from the first wave of the UK’s Household Longitudinal Study. Colchester, UK: Institute for Social and Economic Research, University of Essex.Google Scholar
Meinhold, J.L., & Malkus, A.J. (2005). Adolescent environmental behaviors: Can knowledge, attitudes, and self-efficacy make a difference? Environment and Behavior, 37, 511–532.CrossRefGoogle Scholar
Mochizuki, Y., & Bryan, A. (2015). Climate change education in the context of education for sustainable development: Rationale and principles. Journal of Education for Sustainable Development, 9, 4–26.CrossRefGoogle Scholar
Moisander, J. (2007). Motivational complexity of green consumerism. International Journal of Consumer Studies, 31, 404–409.CrossRefGoogle Scholar
Mondiana, Y.Q., Pramoedyo, H., & Sumarminingsih, E. (2018). Structural equation modeling on Likert scale data with transformation by successive interval method and with no transformation. International Journal of Scientific and Research Publications, 8, 398–405 Google Scholar
Noyes, N., Cho, K.-C., Ravel, J., Forney, L.J., & Abdo, Z. (2018). Associations between sexual habits, menstrual hygiene practices, demographics and the vaginal microbiome as revealed by Bayesian network analysis. PloS One, 13, e0191625.CrossRefGoogle ScholarPubMed
Ockwell, D., Whitmarsh, L., & O’Neill, S. (2009). Reorienting climate change communication for effective mitigation: forcing people to be green or fostering grass-roots engagement? Science Communication, 30, 305–327.CrossRefGoogle Scholar
Pachauri, R.K., Allen, M.R., Barros, V.R., John Broome, J., Cramer, W., Christ, R., … Dasgupta, P. (2014). Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. Geneva: IPCC.Google Scholar
Panno, A., Carrus, G, Maricchiolo, F., & Mannetti, L. (2015). Cognitive reappraisal and pro-environmental behavior: The role of global climate change perception. European Journal of Social Psychology, 45, 858–867.CrossRefGoogle Scholar
Pruneau, D., Gravel, H., Bourque, W., & Langis, J. (2003). Experimentation with a socio-constructivist process for climate change education. Environmental Education Research, 9, 429–446.CrossRefGoogle Scholar
Santer, B.D, Taylor, K.E., Wigley, T.M.L., & Johns, T.C. (1996). A search for human influences on the thermal structure of the atmosphere. Nature, 382, 39–46.CrossRefGoogle Scholar
Semenza, J.C., Hall, D.E., Wilson, D.J., Bontempo, B.D., Sailor, D.J., & George, L.A. (2008). Public perception of climate change: voluntary mitigation and barriers to behavior change. American Journal of Preventive Medicine, 35, 479–487.CrossRefGoogle ScholarPubMed
Shove, E. (2010). Beyond the ABC: Climate change policy and theories of social change. Environment and planning A: Economy and Space, 42, 1273–1285.CrossRefGoogle Scholar
Sjøberg, S., & Schreiner, C. (2010). The ROSE Project: An overview and key findings. Oslo, Norway: University of Oslo:.Google Scholar
Smith, N., & Leiserowitz, A. (2014). The role of emotion in global warming policy support and opposition. Risk Analysis, 34, 937–948.CrossRefGoogle ScholarPubMed
Sternäng, L., & Lundholm, C. (2011). Climate change and morality: Students’ perspectives on the individual and society. International Journal of Science Education, 33, 1131–1148.CrossRefGoogle Scholar
Stevenson, R.B. (2007). Schooling and environmental education: Contradictions in purpose and practice.” Environmental Education Research, 13, 139–153.CrossRefGoogle Scholar
Stevenson, R.B, Brody, M., Dillon, J., & Wals, A.E.J. (Eds.). (2013). International handbook of research on environmental education. New York, NY: Routledge.Google Scholar
Stokes, B., Wike, R., & Carle, J. (2015). Global concern about climate change, broad support for limiting emissions. Washington, DC: Pew Research Center.Google Scholar
Swim, J., Clayton, S., Doherty, T., Gifford, R., Howard, G., Reser, J., Stern, P., & Weber, E. (2009). Psychology and global climate change: Addressing a multi-faceted phenomenon and set of challenges. In A report by the American Psychological Association’s task force on the interface between psychology and global climate change (pp. 241–250). Washington, DC: American Psychological Association.Google Scholar
Tikir, A., & Lehmann, B. (2011). Climate change, theory of planned behavior and values: A structural equation model with mediation analysis. Climatic Change, 104, 389–402.CrossRefGoogle Scholar
Tranter, B. (2014). Social and political influences on environmentalism in Australia. Journal of Sociology, 50, 331–348.CrossRefGoogle Scholar
UNESCO. (2015). Not just hot air: Putting climate change education into practice. Paris: Author.Google Scholar
UNESCO. (2016). Education for people and planet: Creating sustainable futures for all. Paris: Author.Google Scholar
Uusitalo, L. (2007). Advantages and challenges of Bayesian networks in environmental modelling. Ecological Modelling, 203, 312–318.CrossRefGoogle Scholar
Van der Sluijs, J.P. (2012). Uncertainty and dissent in climate risk assessment: A post-normal perspective. Nature and Culture, 7, 174–195.CrossRefGoogle Scholar
Vesanto, J. (2000). Neural network tool for data mining: SOM toolbox. In Proceedings of Symposium on Tool Environments and Development Methods for Intelligent Systems (TOOLMET2000) (pp. 184–196).Google Scholar
Vitousek, P.M, Mooney, H.A., Lubchenco, J., & Melillo, J.M. (1997). Human domination of Earth’s ecosystems. Science, 277, 494–499.CrossRefGoogle Scholar
Witoszek, N. (2018). Teaching sustainability in Norway, China and Ghana: Challenges to the UN programme. Environmental Education Research, 24, 831–844.CrossRefGoogle Scholar
Xenos, M. (2004). Prediction and assessment of student behaviour in open and distance education in computers using Bayesian networks. Computers & Education, 43, 345–359.CrossRefGoogle Scholar
Zhang, P., Deschenes, O., Meng, K., & Zhang, J. (2017). Temperature effects on productivity and factor reallocation: Evidence from a half million Chinese manufacturing plants. Bonn, Germany: IZA Institute of Labor Economics.CrossRefGoogle Scholar